Tag Archives: AWS Management Console

Implementing just-in-time privileged access to AWS with Microsoft Entra and AWS IAM Identity Center

Post Syndicated from Rodney Underkoffler original https://aws.amazon.com/blogs/security/implementing-just-in-time-privileged-access-to-aws-with-microsoft-entra-and-aws-iam-identity-center/

Controlling access to your privileged and sensitive resources is critical for all AWS customers. Preventing direct human interaction with services and systems through automation is the primary means of accomplishing this. For those infrequent times when automation is not yet possible or implemented, providing a secure method for temporary elevated access is the next best option. In a privileged access management solution, there are several elements that should be included:

  • User access should follow the principle of least privileged
  • Users should be granted only the minimum amount of access required to perform their job duties
  • Access granted should persist only for the time necessary to perform the assigned tasks
  • The solution should include:
    • An eligibility process for granting access
    • An approval process for granting access
    • Auditing of the access grants and activities taken

Entra Privileged Identity Management (PIM) is a third-party solution that provides dynamic group management, access control, and audit capabilities that integrate with AWS IAM Identity Center.

In this post, we show you how to configure just-in-time access to AWS using Entra PIM’s integration with IAM Identity Center.

Just-in-time privileged access with Entra PIM and IAM Identity Center

Privileged Identity Management is a Microsoft Entra ID feature that enables management, control, and access monitoring of your important cloud resources. There are many different configuration options when it comes to eligibility and assignment to privileged security groups, including time-bound access with start and end dates, multi-factor authentication (MFA) enforcement, justification tracking, and so on. You can read more about those options in Microsoft’s product documentation.

Figure 1 shows the just-in-time access solution powered by Entra PIM group activation requests. In this solution, Entra PIM is integrated with IAM Identity Center to provide temporary, limited access to AWS resources based on user requests and approvals. Entra ID users can submit requests for specific access to specific AWS permissions sets, which are then automatically granted for a set duration.

Figure 1 – Entra PIM solution integrated with IAM Identity Center

Figure 1 – Entra PIM solution integrated with IAM Identity Center

Prerequisites

To try the solution described in this post, you need to have the following in place:

Step-by-step configuration

In the following steps, you create configurations to enable Entra PIM for Groups to automatically assign users to groups based on approval criteria. The groups will be Entra ID security groups that use direct assignment. Note that, at the time of this writing, dynamic groups and groups that you have synchronized from a self-managed Active Directory cannot be used with Microsoft Entra PIM. While it might be possible to also populate these groups using a third-party synchronization tool, for the purposes of this exercise, we assume that administration is occurring solely within Entra ID.

In the example scenario, the role corresponds to a specific job function within your organization. We use a group called AWS – Amazon EC2 Admin, which corresponds to a DevOps on-call site reliability engineer (SRE) lead.

Step 1: Create a group representing a specific privilege level.

Create a group in Entra ID that represents a specific privilege level that your employees can request for access to the AWS Management Console.

  1. Sign in to the Microsoft Entra admin center with your credentials.
  2. Select Groups and then All groups.
  3. Choose New group.
  4. Specify Security in the Group type dropdown list.
    • In the Group name field, enter AWS - Amazon EC2 Admin.
    • In the Group description field, enter Amazon EC2 administrator permissions.
    • Choose Create.

Step 2: Assign access for the group in Entra ID

Now you need to assign the newly created group to your enterprise application.

  1. Sign in to the Microsoft Entra admin center with your credentials
  2. Select Applications and then Enterprise applications and select the IAM Identity Center application that you created.
  3. Select Users and groups from the Manage menu group and select + Add user/group.
  4. Select the None selected option from the Users and groups section.
  5. Select the AWS – Amazon EC2 Admin group checkbox.
  6. Choose Select and then choose Assign.
  7. Select Provisioning from the Manage menu group and begin synchronizing the empty group by selecting the Start provisioning option.

When you first enable provisioning, the initial Microsoft Entra ID sync is triggered immediately. After that, subsequent syncs are triggered every 40 minutes, with the exact frequency depending on the number of users and groups in the application.

When the initial sync completes, the AWS – Amazon EC2 Admin group will be ready for configuration in IAM Identity Center.

Step 3: Create permission sets in IAM Identity Center

As you prepare to configure your permission set, let’s consider session duration from both the AWS and Entra PIM perspectives. There are two session durations on the AWS side: AWS access portal session duration and permission set session duration. The AWS access portal session duration defines the maximum length of time that a user can be signed in to the AWS access portal without reauthenticating. The default session duration is 8 hours but can be configured anywhere between 15 minutes and 7 days.

Note: Entra does not pass the SessionNotOnOrAfter attribute to IAM Identity Center as part of the SAML assertion. Meaning the duration of the AWS access portal session is controlled by the duration set in IAM Identity Center.

The session duration defined within a permission set specifies the length of time that a user can have a session for an AWS account. The default and minimum value is 1 hour (with a maximum value of 12). Entra PIM allows you to configure an activation maximum duration. The activation maximum duration is the length of time that the specified group will contain the activated user account. The activation maximum duration has a default value of 8 hours but can be configured between 30 minutes and 24 hours.

You should carefully consider the values that you provide for each of these durations. The AWS access portal will display permission sets that the user had access to at the time that they signed in for the duration of the active AWS access portal session.

When you set the permission set session duration, you need to keep in mind that active sessions are not terminated when the Entra PIM activation maximum duration has been reached. Let’s look at an example:

  • AWS access portal session duration: default (8 hours)
  • Session duration defined in the permission set: 1 hour
  • Entra PIM group activation maximum duration: 1 hour

You might be inclined to think that an hour after being added to the group in Entra, the user would no longer have access to AWS resources. This is not necessarily the case. A user could authenticate to the AWS access portal, wait up to 8 hours, and still successfully access AWS through the permission set link. Their session would be active for the duration of the session setting defined in the permission set, which is 1 hour in this case. In this example, we have a potential window of access of 10 hours, as shown in Figure 2 that follows.

Figure 2 – Calculating session duration

Figure 2 – Calculating session duration

With this in mind, configure your test environment with the default setting of 8 hours for the AWS access portal and 1 hour for the permission set session duration value.

  1. Open the IAM Identity Center console.
  2. Under Multi-account permissions, choose Permission sets.
  3. Choose Create permission set.
  4. On the Select permission set type page, under Permission set type, select Custom permission set, and then choose Next.
  5. On the Specify policies and permissions boundary page, expand AWS managed policies.
  6. Search for and select AmazonEC2FullAccess policy, and then choose Next.
  7. On the Specify permission set details page, enter EC2AdminAccess for the Permission set name and choose Next.
  8. On the Review and create page, review the selections, and choose Create.

Step 4: Assign group access in your organization

At this point, you’re ready to assign the Microsoft Entra group to the corresponding permission set in IAM Identity Center. This allows users who are members of the group to be granted the appropriate access level in AWS.

  1. In the navigation pane, under Multi-account permissions, choose AWS accounts.
  2. On the AWS accounts page, select the check box next to one or more AWS accounts to which you want to assign access.
  3. Choose Assign users or groups.
  4. On the Groups tab, select AWS – Amazon EC2 Admin and choose Next
  5. On the Assign permission sets to “<AWS-account-name>” page, select the EC2AdminAccess permission set.
  6. Check that the correct permission set was selected and choose Next.
  7. On the Review and submit page, verify that the correct group and permission set are selected, and choose Submit.

Step 5: Configure Entra PIM

To use this Microsoft Entra group with Entra PIM, you bring the group under the management of PIM by using the Entra admin console to activate the group. You can read more about group management with PIM in the Microsoft documentation. Begin by activating the Entra group that you created.

  1. Sign in to the Microsoft Entra admin center with your credentials.
  2. Select Groups and then All groups
  3. Select the AWS – Amazon EC2 Admin group.
    Figure 3 – Selecting groups for PIM enablement

    Figure 3 – Selecting groups for PIM enablement

  4. Select Privileged Identity Management under the Activity menu list.
  5. Choose Enable PIM for this group.
    Figure 4 – Enable PIM for this group

    Figure 4 – Enable PIM for this group

Now, you will configure the PIM settings for the group. These settings define Member or Owner properties and requirements. It’s here that you can establish MFA requirements, configure notifications, conditional access, approvals, durations, and so on. The Owner role can elevate their permissions using just-in-time access to manage a group, while the Member role is limited to requesting just-in-time membership within the group. In this example, you use the Member properties to demonstrate group membership level temporary elevated access and set a 1-hour duration for the group assignment.

  1. Sign in to the Microsoft Entra admin center with your credentials.
  2. Select Identity Governance, Privileged Identity Management, and then Groups.
  3. Select the AWS – Amazon EC2 Admin group.
    Figure 5 – Selecting groups for PIM configuration

    Figure 5 – Selecting groups for PIM configuration

  4. From the Manage menu select Settings.
  5. Choose Member to view the default role setting details.
    Figure 6 – Settings option for the Member role

    Figure 6 – Settings option for the Member role

  6. Review the default settings. The activation maximum duration should be set to 1 hour and require a justification from the user.
  7. Close the Role setting details – Member blade.
    Figure 7 – Closing the Role setting details – Member blade

    Figure 7 – Closing the Role setting details – Member blade

  8. From the Manage menu select Assignments and choose + Add assignments.
    Figure 8 – Adding eligibility assignments to the PIM enabled groups

    Figure 8 – Adding eligibility assignments to the PIM enabled groups

  9. Select Member from the Select role dropdown menu and choose No member selected. Select the test account, Rich Roe in this example, and then choose Select.
    Figure 9 – Adding the test user as an eligible identity for PIM activation to the group

    Figure 9 – Adding the test user as an eligible identity for PIM activation to the group

  10. Choose Next and leave the default setting of 1 year of eligibility. Duration eligibility defines the period that the user can request activation for the group. Depending on your use case, you will define this as permanent or for a set period. For testing purposes, keep the default setting. Choose Assign.
    Figure 10 – Completing the eligibility assignment

    Figure 10 – Completing the eligibility assignment

Test the configuration

You should now have a test configuration of Entra PIM and IAM Identity Center. Use the test account to verify just-in-time access.

  1. Sign in to the Microsoft Entra admin center using the test account (Rich Roe in this example).
  2. Select Identity Governance, Privileged Identity Management, and then My roles.
    Figure 11 – Browsing to the My Roles section of the Entra admin center

    Figure 11 – Browsing to the My Roles section of the Entra admin center

  3. From the Activate menu list, select Groups. Your eligible group assignments should be listed.
  4. Choose Activate for the AWS – Amazon EC2 Admin group.
    Figure 12 – Activating the just-in-time group membership

    Figure 12 – Activating the just-in-time group membership

  5. In the Activate – Member blade, enter a justification for the access request and choose Activate.
    Figure 13 – Providing a justification for access

    Figure 13 – Providing a justification for access

In this example, there are no approval workflow processes configured for the group, so Entra validates the eligibility requirements and adds the test account to the AWS – Amazon EC2 Admin group. If you want to dive deeper into the approval workflow process, you can read more about it on the Configure PIM for Groups settings page. Because the group is assigned to the enterprise application and configured for provisioning, the updated group membership is automatically synchronized using the SCIM protocol with the connected IAM Identity Center instance. The provisioning time can vary based on the number of PIM enabled users that are activating their memberships within a given 10-second period. In most situations, group memberships are synchronized within 2–10 minutes, but can revert to the standard 40-minute interval if activity runs up against Entra PIM throttling limits. IAM Identity Center responds to SCIM requests as they arrive from Entra ID.

To test access with the newly activated group assignment, use a separate browser or a private window.

  1. Sign in to the My Apps portal with the test user credentials and select the IAM Identity Center app that you created for testing. If you experience an error or don’t see the expected permission set, wait a few minutes until the group membership has synchronized to IAM Identity Center and try again.
    Figure 14 – Accessing IAM Identity Center through the My apps portal

    Figure 14 – Accessing IAM Identity Center through the My apps portal

  2. Expand the associated AWS account and confirm the EC2ReadOnly permission set has been granted.
  3. Close the AWS tab. Wait for the access to be revoked, which has been set to 60 minutes in this example.
    Figure 15 – Just-in-time access to the EC2AdminAccess permission set

    Figure 15 – Just-in-time access to the EC2AdminAccess permission set

  4. Sign back in to the My Apps portal and select the AWS IAM Identity Center app. Notice that the EC2ReadOnly permission set has been revoked.

Conclusion

The combination of AWS IAM Identity Center and Entra PIM provides a robust solution for managing just-in-time elevated access to AWS. By using security groups in Entra and mapping them to permission sets in IAM Identity Center, you can automate the provisioning and deprovisioning of privileged access based on defined policies and approval workflows. This approach helps to make sure the principle of least privilege is enforced, with access granted only for the duration required to complete a task. The detailed auditing capabilities of both services also provide comprehensive visibility into privileged access activities.

For AWS customers seeking a comprehensive, secure, and scalable privileged access management solution, the Entra PIM and IAM Identity Center integration is a common option that’s worth investigating to see if it’s a good fit for your use case.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, contact AWS Support.

Rodney Underkoffler

Rodney Underkoffler

Rodney is a Senior Solutions Architect at Amazon Web Services, focused on guiding enterprise customers on their cloud journey. He has a background in infrastructure, security, and IT business practices. He is passionate about technology and enjoys building and exploring new solutions and methodologies.

Aidan Keane

Aidan Keane

Aidan is a Senior Specialist Solutions Architect at Amazon Web Services, focused on Microsoft Workloads. He partners with enterprise customers to optimize their Microsoft environments on AWS and accelerate their cloud journey. Outside of work, he is a sports enthusiast who enjoys golf, biking, and watching Liverpool FC, while also enjoying family time and travelling to Ireland and South America.

AWS Weekly Roundup: New AWS Mexico (Central) Region, simultaneous sign-in for multiple AWS accounts, and more (January 20, 2025)

Post Syndicated from Esra Kayabali original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-new-aws-mexico-central-region-simultaneous-sign-in-for-multiple-aws-accounts-and-more-january-20-2025/

As winter maintains its hold over where I live in the Netherlands, rare moments of sunlight become precious gifts. This weekend offered one such treasure—while cycling along a quiet canal, golden rays broke through the typically gray Dutch sky, creating a perfect moment of serenity. These glimpses of brightness feel particularly special during January, when daylight can be scarce in our corner of Europe. As we move deeper into 2025, the third week of the new year brings both reflection and forward momentum. While global conversations swirl around technological advancements, it’s these small, personal moments that remind us to pause and appreciate the simple pleasures among our rapidly evolving world.

Let’s look at the last week’s new announcements.

Last week’s launches
Here are the launches that got my attention.

AWS Mexico (Central) Region – In February 2024, we announced plans to expand infrastructure in Mexico, and we’ve now launched the AWS Mexico (Central) Region with three Availability Zones and API code mx-central-1. This marks the first AWS infrastructure Region in Mexico and adds to our growing presence in Latin America. The new Region provides you with local workload management, data storage capabilities, enhanced performance with lower latency, and robust security standards. It features advanced cloud technologies, including cutting-edge artificial intelligence and machine learning (AI/ML) capabilities with purpose-built processors, comprehensive security capabilities with support for 143 security standards and compliance certifications. With this launch, AWS now spans 114 Availability Zones within 36 geographic Regions.

AWS Management Console now supports simultaneous sign-in for multiple AWS accounts – Using multi-session capability in the AWS Management Console, you can now sign-in to multiple AWS accounts and manage your resources in a single browser. You can sign in to up to 5 sessions and this can be any combination of root, AWS Identity and Access Management (IAM), or federated roles in different accounts or in the same account. You can scale your applications using multiple accounts following AWS best-practice guidelines. You can use accounts for different environments, such as development, testing, and production, and compare resource configurations and status across multiple accounts for troubleshooting application issues and other application related jobs.

Introducing new larger sizes on Amazon EC2 Flex instances – We’re announcing the general availability of two new larger sizes (12xlarge and 16xlarge) on Amazon Elastic Compute Cloud (Amazon EC2) Flex (C7i-flex and M7i-flex) instances. The new sizes expand the EC2 Flex portfolio, providing additional compute options to scale up existing workloads or run larger-sized applications that need additional memory. These instances are powered by custom 4th Gen Intel Xeon Scalable processors, which are available only on AWS, and offer up to 15% better performance over comparable x86-based Intel processors used by other cloud providers. Flex instances are the easiest way to get price performance benefits and lower prices for a majority of compute-intensive and general-purpose workloads. They deliver up to 19% better price performance than comparable previous generation instances and are a great first choice for applications that don’t fully utilize the compute resources. Flex instances are ideal for web and application servers, batch processing, enterprise applications, databases, and more. For compute-intensive and general-purpose workloads that need even larger instance sizes (up to 192 vCPUs and 768 GiB memory) or continuous high CPU usage, you can use Amazon EC2 C7i and M7i instances.

Announcing AWS User Notifications general availability on AWS CloudFormation – You can use AWS User Notifications to configure notifications to be sent using the AWS Management Console Notifications Center, email, AWS Chatbot, or mobile push notifications to the AWS Console Mobile App to keep you informed about important events such as Amazon CloudWatch alarms. With this capability, you can define notification configurations as part of your infrastructure-as-code (IaC) practices and specify notification configurations for specific resource types within your AWS CloudFormation templates. For example, you can set up notifications to trigger when an Amazon EC2 Auto Scaling group scales out, an Elastic Load Balancing (ELB) load balancer is provisioned, or an Amazon Relational Database Service (Amazon RDS) database is modified. You have granular control over which events will trigger notifications and who should receive them.

For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.

We launched existing services and instance types in additional Regions:

Other AWS events
Check your calendar and sign up for upcoming AWS events.

AWS Summits are free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. Stay updated by visiting the official AWS Summit website and sign up for notifications to learn when registration opens for events in your area.

AWS GenAI Lofts are collaborative spaces and immersive experiences that showcase AWS expertise in cloud computing and AI. They provide startups and developers with hands-on access to AI products and services, exclusive sessions with industry leaders, and valuable networking opportunities with investors and peers. Find a GenAI Loft location near you and don’t forget to register.

Browse all upcoming AWS led in-person and virtual events here.

That’s all for this week. Check back next Monday for another Weekly Roundup!

— Esra

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

Unlocking AWS Console: Diagnosing Errors with Amazon Q Developer

Post Syndicated from Marco Frattallone original https://aws.amazon.com/blogs/devops/unlocking-aws-console-diagnosing-errors-with-amazon-q-developer/

Introduction

Developers, IT Operators, and in some cases, Site Reliability Engineers (SREs) are responsible for deploying and operating infrastructure and applications, as well as responding to and resolving incidents effectively and in a timely manner. Effective incident management requires quick diagnosis, root cause analysis, and implementation of corrective actions. Diagnosing the root cause can be challenging in the context of modern systems that involve multiple resources deployed across distributed environments. Amazon Q Developer, a generative AI-powered assistant, can help simplify this process by diagnosing errors you receive in the AWS Management Console.

Amazon Q Developer can save you critical time when dealing with production issues by helping to diagnose errors related to your AWS environment. These errors could be the result of potential misconfiguration across multiple resources, and usually requires you to navigate between several service consoles to identify the root cause. Amazon Q Developer applies machine learning models to automate diagnosis of errors that arise in the AWS Console interface. This reduces the mean time to repair (MTTR) and minimizes the impact of incidents on business operations.

This blog post explores the Amazon Q Developer feature to diagnose errors in AWS Console while working with AWS services. We describe how this feature works in order to provide you guidance on troubleshooting. We take a look behind-the-scenes to show the processes that power this feature.

Diagnose with Amazon Q

The Diagnose with Amazon Q feature is activated when an error occurs in the console for an AWS service that is currently supported by this functionality, and a user with appropriate permissions clicks the Diagnose with Amazon Q button next to the error message. Amazon Q provides a natural language explanation that analyzes the root cause of the error. With a second click on Help me resolve, Amazon Q displays an ordered list of instructions which can be used to resolve the error condition. Once completed, you can provide feedback on whether the resolution provided by Amazon Q was helpful.

To make things concrete, we consider two running examples.

Example 1: Assume that you try to delete an S3 bucket which is not empty. This results in an error message:

This bucket is not empty. Buckets must be empty before they can be deleted. To
delete all objects in the bucket, use the empty bucket configuration.

Example 2: Suppose that you try to list objects in a particular S3 bucket, but lack IAM permissions to do so. This results in an error message:

Insufficient permissions to list objects. After you or your AWS administrator has updated your permissions to allow the s3:ListBucketaction, refresh the page. Learn more about Identity and access management in
Amazon S3.

User clicks on “Launch Instances” button In the EC2 service console in the AWS Management console. User enters all the required information, and clicks on “Launch Instance” button. This results in “Instance launch failed” error appearing in the console along with a “Diagnose with Amazon Q” button. User clicks on the button. this brings up a new window titled “Diagnose console errors with Amazon Q”. Soon an “Analysis” section appears with the message describing the issue with IAM permissions to launch new EC2 instances using natural language. User clicks on “Help me resolve” button. After few seconds, “Resolution” section along with the steps to resolve the error appears.

Diagnose with Amazon Q IAM permissions related to EC2 instance launch error

Behind the Scenes: How Amazon Q generates a diagnosis

When you click on Diagnose with Amazon Q button next to the error message in the AWS Management Console, Amazon Q generates an Analysis that expresses the root cause of the error in natural language. This step is assisted by Large Language Models (LLMs) and is based on context information only. The context provided to the LLM includes the error message shown in the console, the URL of the triggering action, and the IAM role of the user signed in the AWS Console. The service always operates within the permissions granted by your role as you operate in the AWS Console, ensuring that privileges are never escalated beyond what are assigned to you.

When you click on Help me resolve button after you have reviewed the analysis, Amazon Q retrieves additional information about the state of the resources in the AWS Account where the error occurred. This is accomplished by interrogating the customer account in various ways. In this phase, the system actively decides which information is still missing and issues interrogation requests against internal services to fulfil the information need. Interrogation is not needed for simple errors, such as Example 1 above, but becomes essential in order to resolve more complex errors, where information from the context proves insufficient.

Given the context, error analysis, user permissions, and results of account interrogation, Amazon Q generates step-by-step Resolution instructions. This step is assisted by LLMs.

After implementing and validating the steps provided by Amazon Q to resolve the error in the console, you have the option to provide feedback of your experience.

A flow diagram illustrating an error resolution process using Amazon Q. The process begins with an error. The user then diagnoses the issue with Amazon Q, which gets context information from the AWS Console and provide an Analysis. The user requests help to resolve the error. The system enriches the prompt interrogation the signed-in user's account. The model generates step-by-step resolution instructions. These instructions go through a validation process before being presented to the user for implementation.

Diagram showing Interactions between User, AWS Console and Amazon Q Developer

Context Information

Contextual information helps the LLMs to generate more relevant and informed outputs. Context is provided to Amazon Q as input from the console automatically. As the basis for all further analysis and decisions, it should be as rich as possible. At a minimum, Amazon Q obtains the error message, the URL for the triggering action, and the IAM role that the signed-in user assumes. The system automatically extracts relevant identifiers from the context. In our running Example 1, the URL may be https://s3.console.aws.amazon.com/s3/bucket/my-bucket-123456/delete?region=us-west-2, from which Amazon Q extracts aws_region = "us-west-2" and s3_bucket_name = "my-bucket-123456".

Beyond this minimum context, Amazon Q can obtain additional information from the console, pertaining to what the user sees on the screen when the error happens, such as content of text fields or widgets in the current UI. Amazon Q can also make use of specific context provided by the underlying service. In the case of Example 2 above, the bucket name is extracted from the URL, the action s3:ListBucket from the error message, and Amazon Q may obtain additional information from IAM about related policies and accept or deny statements.

Interrogating the signed-in user’s Account

Diagnose with Amazon Q functionality is not just a passive receiver of context information, it has built-in capabilities of actively asking for additional information. This includes developing an understanding of resources in the AWS account, and their relationship with the resource experiencing the error. Such interrogation queries are planned by a subsystem based on context information. It provides a low-latency and deterministic approach to find resources and their relationships. This relationship context provided to the LLM, such as EBS volumes attached to an EC2 instance or policies included in the attached IAM role, improves the accuracy of root cause analysis for diagnosing the error.

In the simple running Example 1 where error is due to non-empty S3 bucket, the error message and the console URL contain all the necessary information to proceed, and active interrogation is not required. On the other hand, for the IAM permission error in Example 2, it’s helpful to understand the permissions on the IAM role associated with the resource experiencing the error. Amazon Q can fetch identity-level policies for the role and resource-level policies for the affected resource, based on which it can diagnose the cause of the error, using internal IAM services. To be concrete, the URL for Example 2 may be https://s3.console.aws.amazon.com/s3/buckets/my-bucket-123456?region=us-west-2&bucketType=general&tab=objects, from which Amazon Q extracts region and S3 bucket name. It can also extract the action s3:ListBucket from the error message itself. Based on this information, Amazon Q can fetch bucket policies for my-bucket-123456, identity-level policies for the role, then scan those for presence or absence of the s3:ListBucket action, or call internal IAM services to provide additional information about the cause of access being denied.

This subsystem uses AWS Cloud Control API (CCAPI) which is called on your behalf by Amazon Q with the permissions granted by your IAM Role. As part of onboarding to Amazon Q, the AmazonQFullAccess managed policy is attached to the Role that can access Amazon Q. This managed policy contains the ListResources and GetResource CCAPI IAM permissions. This ensures all Roles given that managed policy will have access to the CCAPI read and list endpoints. If you do not attach the AmazonQFullAccess managed policy to the required roles, you will need to attach the ListResources and GetResource permission directly to the role.

Generating Step-by-step Resolution Instructions

At this point, all acquired information is synthesized by Amazon Q in order to generate useful and actionable resolution instructions. As an illustration, possible sample instructions for the running examples under consideration are listed below. As the models are updated and improved over time, the responses can change.

For Example 1, sample instructions could look like:

  1. Navigate to the S3 console, click “Buckets”, and select the my-bucket-123456 bucket
  2. Click on the “Empty” tab.
  3. If your bucket contains a large number of objects, creating a lifecycle rule to delete all objects in the bucket might be a more efficient way of emptying your bucket
  4. Type “permanently delete” in text input field and confirm that all objects are to be removed.
  5. Retry deleting the my-bucket-123456 S3 bucket.

For Example 2, you may obtain:

  1. Go to the IAM console. Edit the IAM policy attached to the role ReadOnly
  2. Allow for the s3:ListBucket action for resource being the S3 bucket ARN arn:aws:s3:::my-bucket-123456.
  3. Save the updated IAM policy
  4. Refresh the S3 console page to list the objects in the bucket my-bucket-123456

Note that the instructions contain information inferred from the context, such as bucket name my-bucket-123456, instead of placeholders. Instructions returned by Diagnose with Amazon Q are complete and fine-grained enough in order to be followed without any extra effort. In fact, while the service makes use of an LLM to synthesize resolution instructions, Amazon Q uses post-processing to correct frequently occurring mistakes. For example, in Example 2 above, the LLM may have returned the ARN as arn:aws:s3:<region>::<bucket_name>, which would be corrected to what is shown above.

The instructions returned for Example 2 above assume that the reason for the user not being able to list objects is a missing Allow statement in the policies attached to the ReadOnly role. Other root causes could be a Deny statement in a policy attached to the S3 bucket, or to the ReadOnly role. Diagnose with Amazon Q can use account interrogation in order to identify the correct root cause and propose the right resolution. In the example above, it can fetch the policies attached to the ReadOnly role and check whether s3:ListBucket is missing indeed, or fetch policies attached to the bucket bucket-123456.

Validation

One goal for Diagnose with Amazon Q is to attain wide coverage of AWS rapidly, while keeping the quality bar high, so that you obtain useful, actionable advice where ever you obtain an error. An important prerequisite to attain this goal is a robust and flexible evaluation system. Evaluating systems based on Generative AI is challenging due to the large output space (natural language) and non-deterministic behavior.

In a nutshell, our validation system is based on building a large dataset of errors, where each record has a certain number of annotations. Each record contains the context (templatized error message and console URL; meaning that bucket-123456 is replaced by {{s3_bucket_name}}, us-west-2 by {{aws_region}}). Annotations include Infrastructure as Code (CloudFormation) descriptions of the erroneous account state and the triggering action, as well as ground truth responses obtained from expert annotators. These records allow us to simulate the behaviour of variants of our system without human interactions and many times faster than real time (by way of parallelization). We are also developing automated validation metrics for comparing ground truth annotations and system responses, based on which offline evaluations can be run fully automatically.

This validation system allows us to rapidly validate new ideas by comparing them against the current state, while also guarding against regressions. While human experts are still needed to provide annotations of error records, we actively innovate to speed up and simplify these tasks, by building annotation tools which avoid natural language input, have validations built in, and are rather asking to correct system output than providing ground truth annotations from scratch.

Conclusion

The Diagnose with Amazon Q feature of Amazon Q Developer allows you to determine the cause of an error in the AWS Console without needing to navigate to multiple service consoles. By providing tailored, step-by-step instructions specific to your AWS account and error context, Amazon Q Developer empowers you to troubleshoot and resolve issues efficiently. This helps your organization achieve greater operational efficiency, reduce downtime, improve service quality, and free up valuable human resources enabling them to focus on higher-value activities. We also provide you details on how AI and machine learning capabilities work behind the scenes to enable this functionality.

About the authors

Matthias Seeger, Principal Applied Scientist, AWS NGDE Science

Matthias Seeger is a Principal Applied Scientist at AWS.

Marco Frattallone, Sr. TAM, AWS Enterprise Support

Marco Frattallone is a Senior Technical Account Manager at AWS focused on supporting Partners. He works closely with Partners to help them build, deploy, and optimize their solutions on AWS, providing guidance and leveraging best practices. Marco is passionate about technology and helps Partners stay at the forefront of innovation. Outside work, he enjoys outdoor cycling, sailing, and exploring new cultures.

Surabhi Tandon, Sr EAE, AWS Support

Surabhi Tandon is a Senior Technical Account Manager at Amazon Web Services (AWS). She supports enterprise customers achieve operational excellence and help them with their cloud journey on AWS by providing strategic technical guidance. Surabhi is a builder with interest in Generative AI, automation, and DevOps. Outside of work, she enjoys hiking, reading and spending time with family and friends.

Announcing a visual update to the AWS Management Console (preview)

Post Syndicated from Prasad Rao original https://aws.amazon.com/blogs/aws/announcing-a-visual-update-to-the-aws-management-console-preview/

Today, we are announcing a visual update to the AWS Management Console in preview. We are rolling out this update by using the latest version of Cloudscape, the Amazon Web Services (AWS) design system used to build intuitive, inclusive, and meaningful AWS experiences at scale.

In this post, I describe how the visual update makes it easier for you to scan content, focus on the key information, and find what you are looking for more effectively while preserving the familiar and consistent experience of the AWS Management Console.

AWS Management console home page - previous

AWS Management console home page - Visual Update

Improved readability
A revised typography scale and improved treatment of headings result in a stronger visual hierarchy, which helps you to better locate and understand your data. A refined use of color and weight across text elements help you differentiate key pieces of information faster. For example, you’ll see that labels in form fields are now more prominent, which eases scanning. The same applies to keys in key-value pairs and sections across components, such as service navigation, expandable elements, and tabs.

Cloudfront distribution console screenshot - Previous vs Visual Update

We improved the color palette, made it more vibrant, and simplified the color treatment of interactive elements. For example, secondary buttons, links, tokens, and interactive states for numerous interface elements are now blue, making it easier for you to interact with the content on the screen and contributing to improving task efficiency.

Screenshot showing improved color - Previous vs Visual Update

Improved focus in light and dark mode
Reduced visual complexity supports user focus. We replaced drop shadows with a new thinner stroke on main content wrappers, such as cards, panels, and containers, and unified the use of border styles across components. This reduces visual noise and optimizes the space inside the layout. Shadows are now reserved to add emphasis on specific interactive and transient elements, which helps simplify visual depth and improves the overall content hierarchy.

Screenshot showing improved focus - Previous vs Visual Update

We also released updates to dark mode to address the need for clearer differentiation between elements on the page. These changes include an update to the color ramp and improved contrast between interactive states across components.

Screenshot comparing dark mode of AWS Management Console home page - Previous vs Visual Update

Modernized interface
We modernized the interface while retaining familiarity to continue to offer predictable and recognizable experiences across AWS. The user experience is now easier on the eyes, thanks to the use of rounder shapes, brighter colors, and improved layout treatment. These updates create a smoother, more natural appearance, making the interface more visually pleasing.

To deliver a more delightful experience and support visual storytelling, we also introduced a whole new family of illustrations and motion while still offering the highest accessibility standards.

Example of an illustration introduced

Improved information density
We optimized information density by reducing unused space, leading to more content visible on the screen. Related data is now displayed closer together, reinforcing visual grouping. Space within content wrappers such as cards and containers has been minimized, so you can consume more information at once. The new layout is centered and wider, optimizing the experience to serve larger screen sizes than before. The visual update makes it easier to consume information, which creates a better and friendlier experience within the AWS Management Console.

Showing Improved information density on AWS Lambda Create Function Screen - Previous vs Visual Update

Showing Improved information density in tabular format - Previous vs Visual Update

Additionally, we introduced Toolbar, a new way to navigate and access contextual tools and features. This helps you perform your tasks while maximizing the amount of content available on screen.

Screenshot of toolbar introduced

Improved consistency
The interface is now more distinctive and consistent. Refreshed colors, iconography, and shapes help deliver a more dynamic and expressive experience while reinforcing a unified and cohesive journey across all AWS experiences.

Available now
You can start experiencing the visual update now in selected consoles across all AWS Regions by visiting the AWS Management Console. We’ll be extending the update across all services. Thanks to the new visual treatment, you can now benefit from an experience that’s more readable and intuitive and that contributes to improved overall task efficiency.

AWS Weekly Roundup: Amazon EC2 G6 instances, Mistral Large on Amazon Bedrock, AWS Deadline Cloud, and more (April 8, 2024)

Post Syndicated from Donnie Prakoso original https://aws.amazon.com/blogs/aws/aws-weekly-roundup-mistral-large-aws-clean-rooms-ml-aws-deadline-cloud-and-more-april-8-2024/

We’re just two days away from AWS Summit Sydney (April 10–11) and a month away from the AWS Summit season in Southeast Asia, starting with the AWS Summit Singapore (May 7) and the AWS Summit Bangkok (May 30). If you happen to be in Sydney, Singapore, or Bangkok around those dates, please join us.

Last Week’s Launches
If you haven’t read last week’s Weekly Roundup yet, Channy wrote about the AWS Chips Taste Test, a new initiative from Jeff Barr as part of April’ Fools Day.

Here are some launches that caught my attention last week:

New Amazon EC2 G6 instances — We announced the general availability of Amazon EC2 G6 instances powered by NVIDIA L4 Tensor Core GPUs. G6 instances can be used for a wide range of graphics-intensive and machine learning use cases. G6 instances deliver up to 2x higher performance for deep learning inference and graphics workloads compared to Amazon EC2 G4dn instances. To learn more, visit the Amazon EC2 G6 instance page.

Mistral Large is now available in Amazon Bedrock — Veliswa wrote about the availability of the Mistral Large foundation model, as part of the Amazon Bedrock service. You can use Mistral Large to handle complex tasks that require substantial reasoning capabilities. In addition, Amazon Bedrock is now available in the Paris AWS Region.

Amazon Aurora zero-ETL integration with Amazon Redshift now in additional Regions — Zero-ETL integration announcements were my favourite launches last year. This Zero-ETL integration simplifies the process of transferring data between the two services, allowing customers to move data between Amazon Aurora and Amazon Redshift without the need for manual Extract, Transform, and Load (ETL) processes. With this announcement, Zero-ETL integrations between Amazon Aurora and Amazon Redshift is now supported in 11 additional Regions.

Announcing AWS Deadline Cloud — If you’re working in films, TV shows, commercials, games, and industrial design and handling complex rendering management for teams creating 2D and 3D visual assets, then you’ll be excited about AWS Deadline Cloud. This new managed service simplifies the deployment and management of render farms for media and entertainment workloads.

AWS Clean Rooms ML is Now Generally Available — Last year, I wrote about the preview of AWS Clean Rooms ML. In that post, I elaborated a new capability of AWS Clean Rooms that helps you and your partners apply machine learning (ML) models on your collective data without copying or sharing raw data with each other. Now, AWS Clean Rooms ML is available for you to use.

Knowledge Bases for Amazon Bedrock now supports private network policies for OpenSearch Serverless — Here’s exciting news for you who are building with Amazon Bedrock. Now, you can implement Retrieval-Augmented Generation (RAG) with Knowledge Bases for Amazon Bedrock using Amazon OpenSearch Serverless (OSS) collections that have a private network policy.

Amazon EKS extended support for Kubernetes versions now generally available — If you’re running Kubernetes version 1.21 and higher, with this Extended Support for Kubernetes, you can stay up-to-date with the latest Kubernetes features and security improvements on Amazon EKS.

AWS Lambda Adds Support for Ruby 3.3 — Coding in Ruby? Now, AWS Lambda supports Ruby 3.3 as its runtime. This update allows you to take advantage of the latest features and improvements in the Ruby language.

Amazon EventBridge Console Enhancements — The Amazon EventBridge console has been updated with new features and improvements, making it easier for you to manage your event-driven applications with a better user experience.

Private Access to the AWS Management Console in Commercial Regions — If you need to restrict access to personal AWS accounts from the company network, you can use AWS Management Console Private Access. With this launch, you can use AWS Management Console Private Access in all commercial AWS Regions.

From community.aws 
The community.aws is a home for us, builders, to share our learnings with building on AWS. Here’s my Top 3 posts from last week:

Other AWS News 
Here are some additional news items, open-source projects, and Twitch shows that you might find interesting:

Build On Generative AI – Join Tiffany and Darko to learn more about generative AI, see their demos and discuss different aspects of generative AI with the guest speakers. Streaming every Monday on Twitch, 9:00 AM US PT.

AWS open source news and updates – If you’re looking for various open-source projects and tools from the AWS community, please read the AWS open-source newsletter maintained by my colleague, Ricardo.

Upcoming AWS events
Check your calendars and sign up for these AWS events:

AWS Summits – Join free online and in-person events that bring the cloud computing community together to connect, collaborate, and learn about AWS. Register in your nearest city: Amsterdam (April 9), Sydney (April 10–11), London (April 24), Singapore (May 7), Berlin (May 15–16), Seoul (May 16–17), Hong Kong (May 22), Milan (May 23), Dubai (May 29), Thailand (May 30), Stockholm (June 4), and Madrid (June 5).

AWS re:Inforce – Explore cloud security in the age of generative AI at AWS re:Inforce, June 10–12 in Pennsylvania for two-and-a-half days of immersive cloud security learning designed to help drive your business initiatives.

AWS Community Days – Join community-led conferences that feature technical discussions, workshops, and hands-on labs led by expert AWS users and industry leaders from around the world: Poland (April 11), Bay Area (April 12), Kenya (April 20), and Turkey (May 18).

You can browse all upcoming in-person and virtual events.

That’s all for this week. Check back next Monday for another Weekly Roundup!

— Donnie

This post is part of our Weekly Roundup series. Check back each week for a quick roundup of interesting news and announcements from AWS!

New myApplications in the AWS Management Console simplifies managing your application resources

Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/new-myapplications-in-the-aws-management-console-simplifies-managing-your-application-resources/

Today, we are announcing the general availability of myApplications supporting application operations, a new set of capabilities that help you get started with your applications on AWS, operate them with less effort, and move faster at scale. With myApplication in the AWS Management Console, you can more easily manage and monitor the cost, health, security posture, and performance of your applications on AWS.

The myApplications experience is available in the Console Home, where you can access an Applications widget that lists the applications in an account. Now, you can create your applications more easily using the Create application wizard, connecting resources in your AWS account from one view in the console. The created application will automatically display in myApplications, and you can take action on your applications.

When you choose your application in the Applications widget in the console, you can see an at-a-glance view of key application metrics widgets in the applications dashboard. Here you can find, debug operational issues, and optimize your applications.

With a single action on the applications dashboard, you can dive deeper to act on specific resources in the relevant services, such as Amazon CloudWatch for application performance, AWS Cost Explorer for cost and usage, and AWS Security Hub for security findings.

Getting started with myApplications
To get started, on the AWS Management Console Home, choose Create application in the Applications widget. In the first step, input your application name and description.

In the next step, you can add your resources. Before you can search and add resources, you should turn on and set up AWS Resource Explorer, a managed capability that simplifies the search and discovery of your AWS resources across AWS Regions.

Choose Add resources and select the resources to add to your applications. You can also search by keyword, tag, or AWS CloudFormation stack to integrate groups of resources to manage the full lifecycle of your application.

After confirming, your resources are added, new awsApplication tags applied, and the myApplications dashboard will be automatically generated.

Now, let’s see which widgets can be useful.

The Application summary widget displays the name, description, and tag so you know which application you are working on. The Cost and usage widget visualizes your AWS resource costs and usage from AWS Cost Explorer, including the application’s current and forecasted month-end costs, top five billed services, and a monthly application resource cost trend chart. You can monitor spend, look for anomalies, and click to take action where needed.

The Compute widget summarizes of application compute resources, information about which are in alarm, and trend charts from CloudWatch showing basic metrics such as Amazon EC2 instance CPU utilization and AWS Lambda invocations. You also can assess application operations, look for anomalies, and take action.

The Monitoring and Operations widget displays alarms and alerts for resources associated with your application, service level objectives (SLOs), and standardized application performance metrics from CloudWatch Application Signals. You can monitor ongoing issues, assess trends, and quickly identify and drill down on any issues that might impact your application.

The Security widget shows the highest priority security findings identified by AWS Security Hub. Findings are listed by severity and service, so you can monitor their security posture and click to take action where needed.

The DevOps widget summarizes operational insights from AWS System Manager Application Manager, such as fleet management, state management, patch management, and configuration management status so you can assess compliance and take action.

You can also use the Tagging widget to assist you in reviewing and applying tags to your application.

Now available
You can enjoy this new myApplications capability, a new application-centric experience to easily manage and monitor applications on AWS. myApplications capability is available in the following AWS Regions: US East (Ohio, N. Virginia), US West (N. California, Oregon), South America (São Paulo), Asia Pacific (Hyderabad, Jakarta, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Europe (Frankfurt, Ireland, London, Paris, Stockholm), Middle East (Bahrain) Regions.

AWS Premier Tier Services Partners— Escala24x7, IBM, Tech Mahindra, and Xebia will support application operations with complementary features and services.

Give it a try now in the AWS Management Console and send feedback to AWS re:Post for AWS Management Console, using the feedback link on the myApplications dashboard, or through your usual AWS Support contacts.

Channy

New – Multi-account search in AWS Resource Explorer

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/new-multi-account-search-in-aws-resource-explorer/

With AWS Resource Explorer, you can search for and discover your resources, such as Amazon Elastic Compute Cloud (Amazon EC2) instances, Amazon Kinesis data streams, and Amazon DynamoDB tables, across AWS Regions. Starting today, you can also search across accounts within your organization.

It takes just a few minutes to turn on and configure Resource Explorer for an entire organization or a specific organizational unit (OU) and use simple free-form text and filtered searches to find relevant AWS resources across accounts and Regions.

Multi-account search is available in the Resource Explorer console, anywhere in the AWS Management Console through the unified search bar (the search bar at the top of every AWS console page), using the AWS Command Line Interface (AWS CLI), AWS SDKs, or AWS Chatbot. In this way, you can locate a resource quickly, navigate to the appropriate account and service, and take action.

When operating in a well-architected manner, multiple AWS accounts are used to help isolate and manage business applications and data. You can now use Resource Explorer to simplify how you explore your resources across accounts and act on them at scale. For example, Resource Explorer can help you locate impacted resources across your entire organization when investigating increased operational costs, troubleshooting a performance issue, or remediating a security alert.

Let’s see how this works in practice.

Setting up multi-account search
You can set up multi-account search for your organization in four steps:

  1. Enable trusted access for AWS Account Management.
  2. Configure Resource Explorer in every account in the organization or in the OU you want to search through. You can do that in just a few clicks using AWS Systems Manager Quick Setup. Optionally, you can use AWS CloudFormation, or other management tools you are comfortable with.
  3. It is not mandatory, but we suggest creating a delegated admin account for AWS Account Management. Then, to centralize all the required permissions for multi-account creation, we recommend using the delegated admin account to create Resource Explorer multi-account views.
  4. Finally, you can create a multi-account view to start searching across the organization.

Create a multi-account view
I already implemented the first three steps in the previous list. Using the delegated admin account, I go to the Resource Explorer console. There, I choose Views in the Explore resources section and create a view.

I enter a name for the view and select Organization-wide resources visibility. In this way, I can allow visibility of resources located in accounts across my entire organization or in specific OUs. For this view, I select the whole organization.

Console screenshot.

For the Region, I select the one where I have the aggregator index. The aggregator index contains a replicated copy of the local index in every other Region where Resource Explorer has been turned on. Optionally, I can use a filter to limit which resources should be included in this view. I choose to include all resources and additional resource attributes such as tags.

Console screenshot.

Then, I complete the creation of the view. Now, by granting access to the view, I can control who can access what resource information in Resource Explorer.

Using multi-account search
To try the new multi-account view, I choose Resource search from the Explore resources section of the navigation pane. In my query, I want to see if there are Amazon ElastiCache resources for an old version of Redis. I type elasticache:* redis3.2 in the Query field.

Console screenshot.

In the results, I see the different AWS accounts and Regions where these resources are based. For resources in my account, there is a link in the first column that opens that resource in the console. For resources in other accounts, I can use the console with the appropriate account and service to get more information or take action.

Things to know
Multi-account search is available in the following AWS Regions: [[ Regions ]].

There is no additional charge for using AWS Resource Explorer, including for multi-account searches.

To share views with other accounts in an organization, we suggest you use the delegated admin account to create the view with the necessary visibility in terms of resources, Regions, and accounts within the organization and then use AWS Resource Access Manager to share access to the view. For example, you can create a view for a specific OU and then share the view with an account in that OU.

Search for and discover relevant resources across accounts in your organization and across Regions with AWS Resource Explorer.

Danilo

Access accounts with AWS Management Console Private Access

Post Syndicated from Suresh Samuel original https://aws.amazon.com/blogs/security/access-accounts-with-aws-management-console-private-access/

AWS Management Console Private Access is an advanced security feature to help you control access to the AWS Management Console. In this post, I will show you how this feature works, share current limitations, and provide AWS CloudFormation templates that you can use to automate the deployment. AWS Management Console Private Access is useful when you want to restrict users from signing in to unknown AWS accounts from within your network. With this feature, you can limit access to the console only to a specified set of known accounts when the traffic originates from within your network.

For enterprise customers, users typically access the console from devices that are connected to a corporate network, either directly or through a virtual private network (VPN). With network connectivity to the console, users can authenticate into an account with valid credentials, including third-party accounts and personal accounts. For enterprise customers with stringent network access controls, this feature provides a way to control which accounts can be accessed from on-premises networks.

How AWS Management Console Private Access works

AWS PrivateLink now supports the AWS Management Console, which means that you can create Virtual Private Cloud (VPC) endpoints in your VPC for the console. You can then use DNS forwarding to conditionally route users’ browser traffic to the VPC endpoints from on-premises and define endpoint policies that allow or deny access to specific accounts, organizations, or organizational units (OUs). To privately reach the endpoints, you must have a hybrid network connection between on-premises and AWS over AWS Direct Connect or AWS Site-to-Site VPN.

When you conditionally forward DNS queries for the zone aws.amazon.com from on-premises to an Amazon Route 53 Resolver inbound endpoint within the VPC, Route 53 will prefer the private hosted zone for aws.amazon.com to resolve the queries. The private hosted zone makes it simple to centrally manage records for the console in the AWS US East (N. Virginia) Region (us-east-1) as well as other Regions.

Configure a VPC endpoint for the console

To configure VPC endpoints for the console, you must complete the following steps:

  1. Create interface VPC endpoints in a VPC in the US East (N. Virginia) Region for the console and sign-in services. Repeat for other desired Regions. You must create VPC endpoints in the US East (N. Virginia) Region because the default DNS name for the console resolves to this Region. Specify the accounts, organizations, or OUs that should be allowed or denied in the endpoint policies. For instructions on how to create interface VPC endpoints, see Access an AWS service using an interface VPC endpoint.
  2. Create a Route 53 Resolver inbound endpoint in a VPC and note the IP addresses for the elastic network interfaces of the endpoint. Forward DNS queries for the console from on-premises to these IP addresses. For instructions on how to configure Route 53 Resolver, see Getting started with Route 53 Resolver.
  3. Create a Route 53 private hosted zone with records for the console and sign-in subdomains. For the full list of records needed, see DNS configuration for AWS Management Console and AWS Sign-In. Then associate the private hosted zone with the same VPC that has the Resolver inbound endpoint. For instructions on how to create a private hosted zone, see Creating a private hosted zone.
  4. Conditionally forward DNS queries for aws.amazon.com to the IP addresses of the Resolver inbound endpoint.

How to access Regions other than US East (N. Virginia)

To access the console for another supported Region using AWS Management Console Private Access, complete the following steps:

  1. Create the console and sign-in VPC endpoints in a VPC in that Region.
  2. Create resource records for <region>.console.aws.amazon.com and <region>.signin.aws.amazon.com in the private hosted zone, with values that target the respective VPC endpoints in that Region. Replace <region> with the region code (for example, us-west-2).

For increased resiliency, you can also configure a second Resolver inbound endpoint in a different Region other than the US East (N. Virginia) Region (us-east-1). On-premises DNS resolvers can use both endpoints for resilient DNS resolution to the private hosted zone.

Automate deployment of AWS Management Console Private Access

I created an AWS CloudFormation template that you can use to deploy the required resources in the US East (N. Virginia) Region (us-east-1). To get the template, go to console-endpoint-use1.yaml. The CloudFormation stack deploys the required VPC endpoints, Route 53 Resolver inbound endpoint, and private hosted zone with required records.

Note: The default endpoint policy allows all accounts. For sample policies with conditions to restrict access, see Allow AWS Management Console use for expected accounts and organizations only (trusted identities).

I also created a CloudFormation template that you can use to deploy the required resources in other Regions where private access to the console is required. To get the template, go to console-endpoint-non-use1.yaml.

Cost considerations

When you configure AWS Management Console Private Access, you will incur charges. You can use the following information to estimate these charges:

  • PrivateLink pricing is based on the number of hours that the VPC endpoints remain provisioned. In the US East (N. Virginia) Region, this is $0.01 per VPC endpoint per Availability Zone ($/hour).
  • Data processing charges per gigabyte (GB) of data processed through the VPC endpoints is $0.01 in the US East (N. Virginia) Region.
  • The Route 53 Resolver inbound endpoint is charged per IP (elastic network interface) per hour. In the US East (N. Virginia) Region, this is $0.125 per IP address per hour. See Route 53 pricing.
  • DNS queries to the inbound endpoint are charged at $0.40 per million queries.
  • The Route 53 hosted zone is charged at $0.50 per hosted zone per month. To allow testing, AWS won’t charge you for a hosted zone that you delete within 12 hours of creation.

Based on this pricing model, the cost of configuring AWS Management Console Private Access in the US East (N. Virginia) Region in two Availability Zones is approximately $212.20 per month for the deployed resources. DNS queries and data processing charges are additional based on actual usage. You can also apply this pricing model to help estimate the cost to configure in additional supported Regions. Route 53 is a global service, so you only have to create the private hosted zone once along with the resources in the US East (N. Virginia) Region.

Limitations and considerations

Before you get started with AWS Management Console Private Access, make sure to review the following limitations and considerations:

  • For a list of supported Regions and services, see Supported AWS Regions, service consoles, and features.
  • You can use this feature to restrict access to specific accounts from customer networks by forwarding DNS queries to the VPC endpoints. This feature doesn’t prevent users from accessing the console directly from the internet by using the console’s public endpoints from devices that aren’t on the corporate network.
  • The following subdomains aren’t currently supported by this feature and won’t be accessible through private access:
    • docs.aws.amazon.com
    • health.aws.amazon.com
    • status.aws.amazon.com
  • After a user completes authentication and accesses the console with private access, when they navigate to an individual service console, for example Amazon Elastic Compute Cloud (Amazon EC2), they must have network connectivity to the service’s API endpoint, such as ec2.amazonaws.com. This is needed for the console to make API calls such as ec2:DescribeInstances to display resource details in the service console.

Conclusion

In this blog post, I outlined how you can configure the console through AWS Management Console Private Access to restrict access to AWS accounts from on-premises, how the feature works, and how to configure it for multiple Regions. I also provided CloudFormation templates that you can use to automate the configuration of this feature. Finally, I shared information on costs and some limitations that you should consider before you configure private access to the console.

For more information about how to set up and test AWS Management Console Private Access and reference architectures, see Try AWS Management Console Private Access. For the latest CloudFormation templates, see the aws-management-console-private-access-automation GitHub repository.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread at re:Post.

Want more AWS Security news? Follow us on Twitter.

Suresh Samuel

Suresh Samuel

Suresh is a Senior Technical Account Manager at AWS. He helps customers in the financial services industry with their operations on AWS. When not working, he can be found photographing birds in Texas or hanging out with his kids.

Temporary elevated access management with IAM Identity Center

Post Syndicated from Taiwo Awoyinfa original https://aws.amazon.com/blogs/security/temporary-elevated-access-management-with-iam-identity-center/

AWS recommends using automation where possible to keep people away from systems—yet not every action can be automated in practice, and some operations might require access by human users. Depending on their scope and potential impact, some human operations might require special treatment.

One such treatment is temporary elevated access, also known as just-in-time access. This is a way to request access for a specified time period, validate whether there is a legitimate need, and grant time-bound access. It also allows you to monitor activities performed, and revoke access if conditions change. Temporary elevated access can help you to reduce risks associated with human access without hindering operational capabilities.

In this post, we introduce a temporary elevated access management solution (TEAM) that integrates with AWS IAM Identity Center (successor to AWS Single Sign-On) and allows you to manage temporary elevated access to your multi-account AWS environment. You can download the TEAM solution from AWS Samples, deploy it to your AWS environment, and customize it to meet your needs.

The TEAM solution provides the following features:

  • Workflow and approval — TEAM provides a workflow that allows authorized users to request, review, and approve or reject temporary access. If a request is approved, TEAM activates access for the requester with the scope and duration specified in the request.
  • Invoke access using IAM Identity Center — When temporary elevated access is active, a requester can use the IAM Identity Center AWS access portal to access the AWS Management Console or retrieve temporary credentials. A requester can also invoke access directly from the command line by configuring AWS Command Line Interface (AWS CLI) to integrate with IAM Identity Center.
  • View request details and session activity — Authorized users can view request details and session activity related to current and historical requests from within the application’s web interface.
  • Ability to use managed identities and group memberships — You can either sync your existing managed identities and group memberships from an external identity provider into IAM Identity Center, or manage them directly in IAM Identity Center, in order to control user authorization in TEAM. Similarly, users can authenticate directly in IAM Identity Center, or they can federate from an external identity provider into IAM Identity Center, to access TEAM.
  • A rich authorization model — TEAM uses group memberships to manage eligibility (authorization to request temporary elevated access with a given scope) and approval (authorization to approve temporary elevated access with a given scope). It also uses group memberships to determine whether users can view historical and current requests and session activity, and whether they can administer the solution. You can manage both eligibility and approval policies at different levels of granularity within your organization in AWS Organizations.

TEAM overview

You can download the TEAM solution and deploy it into the same organization where you enable IAM Identity Center. TEAM consists of a web interface that you access from the IAM Identity Center access portal, a workflow component that manages requests and approvals, an orchestration component that activates temporary elevated access, and additional components involved in security and monitoring.

Figure 1 shows an organization with TEAM deployed alongside IAM Identity Center.

Figure 1: An organization using TEAM alongside IAM Identity Center

Figure 1: An organization using TEAM alongside IAM Identity Center

Figure 1 shows three main components:

  • TEAM — a self-hosted solution that allows users to create, approve, monitor and manage temporary elevated access with a few clicks in a web interface.
  • IAM Identity Center — an AWS service which helps you to securely connect your workforce identities and manage their access centrally across accounts.
  • AWS target environment — the accounts where you run your workloads, and for which you want to securely manage both persistent access and temporary elevated access.

There are four personas who can use TEAM:

  • Requesters — users who request temporary elevated access to perform operational tasks within your AWS target environment.
  • Approvers — users who review and approve or reject requests for temporary elevated access.
  • Auditors — users with read-only access who can view request details and session activity relating to current and historical requests.
  • Admins — users who can manage global settings and define policies for eligibility and approval.

TEAM determines a user’s persona from their group memberships, which can either be managed directly in IAM Identity Center or synced from an external identity provider into IAM Identity Center. This allows you to use your existing access governance processes and tools to manage the groups and thereby control which actions users can perform within TEAM.

The following steps describe how you use TEAM during normal operations to request, approve, and invoke temporary elevated access. The steps correspond to the numbered items in Figure 1:

  1. Access the AWS access portal in IAM Identity Center (all personas)
  2. Access the TEAM application (all personas)
  3. Request elevated access (requester persona)
  4. Approve elevated access (approver persona)
  5. Activate elevated access (automatic)
  6. Invoke elevated access (requester persona)
  7. Log session activity (automatic)
  8. End elevated access (automatic; or requester or approver persona)
  9. View request details and session activity (requester, approver, or auditor persona)

In the TEAM walkthrough section later in this post, we provide details on each of these steps.

Deploy and set up TEAM

Before you can use TEAM, you need to deploy and set up the solution.

Prerequisites

To use TEAM, you first need to have an organization set up in AWS Organizations with IAM Identity Center enabled. If you haven’t done so already, create an organization, and then follow the Getting started steps in the IAM Identity Center User Guide.

Before you deploy TEAM, you need to nominate a member account for delegated administration in IAM Identity Center. This has the additional benefit of reducing the need to use your organization’s management account. We strongly recommend that you use this account only for IAM Identity Center delegated administration, TEAM, and associated services; that you do not deploy any other workloads into this account, and that you carefully manage access to this account using the principle of least privilege.

We recommend that you enforce multi-factor authentication (MFA) for users, either in IAM Identity Center or in your external identity provider. If you want to statically assign access to users or groups (persistent access), you can do that in IAM Identity Center, independently of TEAM, as described in Multi-account permissions.

Deploy TEAM

To deploy TEAM, follow the solution deployment steps in the TEAM documentation. You need to deploy TEAM in the same account that you nominate for IAM Identity Center delegated administration.

Access TEAM

After you deploy TEAM, you can access it through the IAM Identity Center web interface, known as the AWS access portal. You do this using the AWS access portal URL, which is configured when you enable IAM Identity Center. Depending on how you set up IAM Identity Center, you are either prompted to authenticate directly in IAM Identity Center, or you are redirected to an external identity provider to authenticate. After you authenticate, the AWS access portal appears, as shown in Figure 2.

Figure 2: TEAM application icon in the AWS access portal of IAM Identity Center

Figure 2: TEAM application icon in the AWS access portal of IAM Identity Center

You configure TEAM as an IAM Identity Center Custom SAML 2.0 application, which means it appears as an icon in the AWS access portal. To access TEAM, choose TEAM IDC APP.

When you first access TEAM, it automatically retrieves your identity and group membership information from IAM Identity Center. It uses this information to determine what actions you can perform and which navigation links are visible.

Set up TEAM

Before users can request temporary elevated access in TEAM, a user with the admin persona needs to set up the application. This includes defining policies for eligibility and approval. A user takes on the admin persona if they are a member of a named IAM Identity Center group that is specified during TEAM deployment.

Manage eligibility policies

Eligibility policies determine who can request temporary elevated access with a given scope. You can define eligibility policies to ensure that people in specific teams can only request the access that you anticipate they’ll need as part of their job function.

  • To manage eligibility policies, in the left navigation pane, under Administration, select Eligibility policy. Figure 3 shows this view with three eligibility policies already defined.
     
Figure 3: Manage eligibility policies

Figure 3: Manage eligibility policies

An eligibility policy has four main parts:

  • Name and Type — An IAM Identity Center user or group
  • Accounts or OUs — One or more accounts, organizational units (OUs), or both, which belong to your organization
  • Permissions — One or more IAM Identity Center permission sets (representing IAM roles)
  • Approval required — whether requests for temporary elevated access require approval.

Each eligibility policy allows the specified IAM Identity Center user, or a member of the specified group, to log in to TEAM and request temporary elevated access using the specified permission sets in the specified accounts. When you choose a permission set, you can either use a predefined permission set provided by IAM Identity Center, or you can create your own permission set using custom permissions to provide least-privilege access for particular tasks.

Note: If you specify an OU in an eligibility or approval policy, TEAM includes the accounts directly under that OU, but not those under its child OUs.

Manage approval policies

Approval policies work in a similar way as eligibility policies, except that they authorize users to approve temporary elevated access requests, rather than create them. If a specific account is referenced in an eligibility policy that is configured to require approval, then you need to create a corresponding approval policy for the same account. If there is no corresponding approval policy—or if one exists but its groups have no members — then TEAM won’t allow users to create temporary elevated access requests for that account, because no one would be able to approve them.

  • To manage approval policies, in the left navigation pane, under Administration, select Approval policy. Figure 4 shows this view with three approval policies already defined.
     
Figure 4: Manage approval policies

Figure 4: Manage approval policies

An approval policy has two main parts:

  • Id, Name, and Type — Identifiers for an account or organizational unit (OU)
  • Approver groups — One or more IAM Identity Center groups

Each approval policy allows a member of a specified group to log in to TEAM and approve temporary elevated access requests for the specified account, or all accounts under the specified OU, regardless of permission set.

Note: If you specify the same group for both eligibility and approval in the same account, this means approvers can be in the same team as requesters for that account. This is a valid approach, sometimes known as peer approval. Nevertheless, TEAM does not allow an individual to approve their own request. If you prefer requesters and approvers to be in different teams, specify different groups for eligibility and approval.

TEAM walkthrough

Now that the admin persona has defined eligibility and approval policies, you are ready to use TEAM.

To begin this walkthrough, imagine that you are a requester, and you need to perform an operational task that requires temporary elevated access to your AWS target environment. For example, you might need to fix a broken deployment pipeline or make some changes as part of a deployment. As a requester, you must belong to a group specified in at least one eligibility policy that was defined by the admin persona.

Step 1: Access the AWS access portal in IAM Identity Center

To access the AWS access portal in IAM Identity Center, use the AWS access portal URL, as described in the Access TEAM section earlier in this post.

Step 2: Access the TEAM application

To access the TEAM application, select the TEAM IDC APP icon, as described in the Access TEAM section earlier.

Step 3: Request elevated access

The next step is to create a new elevated access request as follows:

  1. Under Requests, in the left navigation pane, choose Create request.
  2. In the Elevated access request section, do the following, as shown in Figure 5:
    1. Select the account where you need to perform your task.
    2. For Role, select a permission set that will give you sufficient permissions to perform the task.
    3. Enter a start date and time, duration, ticket ID (typically representing a change ticket or incident ticket related to your task), and business justification.
    4. Choose Submit.
Figure 5: Create a new request

Figure 5: Create a new request

When creating a request, consider the following:

  • In each request, you can specify exactly one account and one permission set.
  • You can only select an account and permission set combination for which you are eligible based on the eligibility policies defined by the admin persona.
  • As a requester, you should apply the principle of least privilege by selecting a permission set with the least privilege, and a time window with the least duration, that will allow you to complete your task safely.
  • TEAM captures a ticket identifier for audit purposes only; it does not try to validate it.
  • The duration specified in a request determines the time window for which elevated access is active, if your request is approved. During this time window, you can invoke sessions to access the AWS target environment. It doesn’t affect the duration of each session.
  • Session duration is configured independently for each permission set by an IAM Identity Center administrator, and determines the time period for which IAM temporary credentials are valid for sessions using that permission set.
  • Sessions invoked just before elevated access ends might remain valid beyond the end of the approved elevated access period. If this is a concern, consider minimizing the session duration configured in your permission sets, for example by setting them to 1 hour.

Step 4: Approve elevated access

After you submit your request, approvers are notified by email. Approvers are notified when there are new requests that fall within the scope of what they are authorized to approve, based on the approval policies defined earlier.

For this walkthrough, imagine that you are now the approver. You will perform the following steps to approve the request. As an approver, you must belong to a group specified in an approval policy that the admin persona configured.

  1. Access the TEAM application in exactly the same way as for the other personas.
  2. In the left navigation pane, under Approvals, choose Approve requests. TEAM displays requests awaiting your review, as shown in Figure 6.
    • To view the information provided by the requester, select a request and then choose View details.
    Figure 6: Requests awaiting review

    Figure 6: Requests awaiting review

  3. Select a pending request, and then do one of the following:
    • To approve the request, select Actions and then choose Approve.
    • To reject the request, select Actions and then choose Reject.

    Figure 7 shows what TEAM displays when you approve a request.

    Figure 7: Approve a request

    Figure 7: Approve a request

  4. After you approve or reject a request, the original requester is notified by email.

A requester can view the status of their requests in the TEAM application.

  • To see the status of your open requests in the TEAM application, in the left navigation pane, under Requests, select My requests. Figure 8 shows this view with one approved request.
     
Figure 8: Approved request

Figure 8: Approved request

Step 5: Automatic activation of elevated access

After a request is approved, the TEAM application waits until the start date and time specified in the request and then automatically activates elevated access. To activate access, a TEAM orchestration workflow creates a temporary account assignment, which links the requester’s user identity in IAM Identity Center with the permission set and account in their request. Then TEAM notifies the requester by email that their request is active.

A requester can now view their active request in the TEAM application.

  1. To see active requests, in the left navigation pane under Elevated access, choose Active access. Figure 9 shows this view with one active request.
     
    Figure 9: Active request

    Figure 9: Active request

  2. To see further details for an active request, select a request and then choose View details. Figure 10 shows an example of these details.
    Figure 10: Details of an active request

    Figure 10: Details of an active request

Step 6: Invoke elevated access

During the time period in which elevated access is active, the requester can invoke sessions to access the AWS target environment to complete their task. Each session has the scope (permission set and account) approved in their request. There are three ways to invoke access.

The first two methods involve accessing IAM Identity Center using the AWS access portal URL. Figure 11 shows the AWS access portal while a request is active.

Figure 11: Invoke access from the AWS access portal

Figure 11: Invoke access from the AWS access portal

From the AWS access portal, you can select an account and permission set that is currently active. You’ll also see the accounts and permission sets that have been statically assigned to you using IAM Identity Center, independently of TEAM. From here, you can do one of the following:

  • Choose Management console to federate to the AWS Management Console.
  • Choose Command line or programmatic access to copy and paste temporary credentials.

The third method is to initiate access directly from the command line using AWS CLI. To use this method, you first need to configure AWS CLI to integrate with IAM Identity Center. This method provides a smooth user experience for AWS CLI users, since you don’t need to copy and paste temporary credentials to your command line.

Regardless of how you invoke access, IAM Identity Center provides temporary credentials for the IAM role and account specified in your request, which allow you to assume that role in that account. The temporary credentials are valid for the duration specified in the role’s permission set, defined by an IAM Identity Center administrator.

When you invoke access, you can now complete the operational tasks that you need to perform in the AWS target environment. During the period in which your elevated access is active, you can invoke multiple sessions if necessary.

Step 7: Log session activity

When you access the AWS target environment, your activity is logged to AWS CloudTrail. Actions you perform in the AWS control plane are recorded as CloudTrail events.

Note: Each CloudTrail event contains the unique identifier of the user who performed the action, which gives you traceability back to the human individual who requested and invoked temporary elevated access.

Step 8: End elevated access

Elevated access ends when either the requested duration elapses or it is explicitly revoked in the TEAM application. The requester or an approver can revoke elevated access whenever they choose.

When elevated access ends, or is revoked, the TEAM orchestration workflow automatically deletes the temporary account assignment for this request. This unlinks the permission set, the account, and the user in IAM Identity Center. The requester is then notified by email that their elevated access has ended.

Step 9: View request details and session activity

You can view request details and session activity for current and historical requests from within the TEAM application. Each persona can see the following information:

  • Requesters can inspect elevated access requested by them.
  • Approvers can inspect elevated access that falls within the scope of what they are authorized to approve.
  • Auditors can inspect elevated access for all TEAM requests.

Session activity is recorded based on the log delivery times provided by AWS CloudTrail, and you can view session activity while elevated access is in progress or after it has ended. Figure 12 shows activity logs for a session displayed in the TEAM application.

Figure 12: Session activity logs

Figure 12: Session activity logs

Security and resiliency considerations

The TEAM application controls access to your AWS environment, and you must manage it with great care to prevent unauthorized access. This solution is built using AWS Amplify to ease the reference deployment. Before operationalizing this solution, consider how to align it with your existing development and security practices.

Further security and resiliency considerations including setting up emergency break-glass access are available in the TEAM documentation.

Additional resources

AWS Security Partners provide temporary elevated access solutions that integrate with IAM Identity Center, and AWS has validated the integration of these partner offerings and assessed their capabilities against a common set of customer requirements. For further information, see temporary elevated access in the IAM Identity Center User Guide.

The blog post Managing temporary elevated access to your AWS environment describes an alternative self-hosted solution for temporary elevated access which integrates directly with an external identity provider using OpenID Connect, and federates users directly into AWS Identity and Access Management (IAM) roles in your accounts. The TEAM solution described in this blog post, on the other hand, integrates with IAM Identity Center, which provides a way to centrally manage user access to accounts across your organization and optionally integrates with an external identity provider.

Conclusion

In this blog post, you learned that your first priority should be to use automation to avoid the need to give human users persistent access to your accounts. You also learned that in the rare cases in which people need access to your accounts, not all access is equal; there are times when you need a process to verify that access is needed, and to provide temporary elevated access.

We introduced you to a temporary elevated access management solution (TEAM) that you can download from AWS Samples and use alongside IAM Identity Center to give your users temporary elevated access. We showed you the TEAM workflow, described the TEAM architecture, and provided links where you can get started by downloading and deploying TEAM.

 
If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on AWS IAM Identity Center re:Post or contact AWS Support.

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Taiwo Awoyinfa

Taiwo Awoyinfa

Taiwo is a senior cloud architect with AWS Professional Services. At AWS, he helps global customers with cloud transformation, migration and security initiatives. Taiwo has expertise in cloud architecture, networking, security and application development. He is passionate about identifying and solving problems that delivers value.

Author

James Greenwood

James is a principal security solutions architect who helps AWS Financial Services customers meet their security and compliance objectives in the AWS cloud. James has a background in identity and access management, authentication, credential management, and data protection with more than 20 years experience in the financial services industry.

Varvara Semenova

Varvara Semenova

Varvara is a cloud infrastructure architect with AWS Professional Services. She specialises in building microservices-based serverless applications to address the needs of AWS enterprise customers. Varvara uses her background in DevOps to help the customer innovate faster when developing cost-effective, secure, and reliable solutions.

New – Visualize Your VPC Resources from Amazon VPC Creation Experience

Post Syndicated from Channy Yun original https://aws.amazon.com/blogs/aws/new-visualize-your-vpc-resources-from-amazon-vpc-creation-experience/

Today we are announcing Amazon Virtual Private Cloud (Amazon VPC) resource map, a new feature that simplifies the VPC creation experience in the AWS Management Console. This feature displays your existing VPC resources and their routing visually on a single page, allowing you to quickly understand the architectural layout of the VPC.

A year ago, in March 2022, we launched a new VPC creation experience that streamlines the process of creating and connecting VPC resources. With just one click, even across multiple Availability Zones (AZs), you can create and connect VPC resources, eliminating more than 90 percent of the manual steps required in the past. The new creation experience is centered around an interactive diagram that displays a preview of the VPC architecture and updates as options are selected, providing a visual representation of the resources and their relationships within the VPC that you are about to create.

However, after the creation of the VPC, the diagram that was available during the creation experience that many of our customers loved was no longer available. Today we are changing that! With VPC resource map, you can quickly understand the architectural layout of the VPC, including the number of subnets, which subnets are associated with the public route table, and which route tables have routes to the NAT Gateway.

You can also get to the specific resource details by clicking on the resource. This eliminates the need for you to map out resource relationships mentally and hold the information in your head while working with your VPC, making the process much more efficient and less prone to mistakes.

Getting Started with VPC Resource Map
To get started, choose an existing VPC in the VPC console. In the details section, select the Resource map tab. Here, you can see the resources in your VPC and the relationships between those resources.

As you hover over a resource, you can see the related resources and the connected lines highlighted. If you click to select the resource, you can see a few lines of details and a link to see the details of the selected resource.

Getting Started with VPC Creation Experience
I want to explain how to use the VPC creation experience to improve your workflow to create a new VPC to make a high-availability three-tier VPC easily.

Choose Create VPC and select VPC and more in the VPC console. You can preview the VPC resources that you are about to create all on the same page.

In Name tag auto-generation, you can specify a prefix value for Name tags. This value is used to generate Name tags for all VPC resources in the preview. If I change the default value, which is project to channy, the Name tag in the preview changes to channy- something, such as channy-vpc. You can customize a Name tag per resource in the preview by clicking each resource and making changes.

You can easily change the default CIDR value (10.0.0.0/16) when you click the IPv4 CIDR block field to reveal the CIDR joystick. Use the left or right arrow to move to the previous (9.255.0.0/16) or next (10.0.1.0/16) CIDR block within the /16 network mask. You can also change the subnet mask to /17 by using the down arrow, or go back to /16 using the up arrow.

Choose the number of Availability Zones (AZs) up to 3. The number of public and private subnet types changes based on the number of AZs and shows the total number of each subnet type it will create.

I want a high-availability VPC in three AZs and select 6 for the number of private subnets. In the preview panel, you can see that there are 9 subnets. When I hover over channy-rtb-public, I can visually confirm that this route table is connected to three public subnets and also routed to the internet gateway (channy-igw). The dotted lines indicate routes to network node, and the solid lines indicate relationships such as implicit or explicit associations.

Adding NAT gateways and VPC endpoints is easy. You can simply change the number of NAT gateways in or per Availability Zone (AZ). Note that there is a charge for each NAT gateway. We always recommend having one NAT gateway per AZ and route traffic from subnets in an AZ to the NAT gateway in the same AZ for high availability and to avoid inter-AZ data charges.

To route traffic to Amazon Simple Storage Service (Amazon S3) buckets more securely, you can choose the S3 Gateway endpoint by default. The S3 Gateway endpoint is free of charge and does not use NAT gateways when moving data from private subnets.

You can create additional tags and assign them to all resources in the VPC in no time. I select Add new tag and enter environment for the Key and test for the Value. This key-value pair will be added to every resource here.

Choose Create VPC at the bottom of the page and see the resources and the IDs of those resources that are being created. Before creating, please validate resources from the preview.

Once all the resources are created, choose View VPC at the bottom. The button takes you directly to the VPC resource map, where you can see a visual representation of what you created.

Now Available
Amazon VPC resource map is now available in all AWS Regions where Amazon VPC is available, and you can start using it today.

The VPC resource map and creation experience now only displays VPC, subnets, route tables, internet gateway, NAT gateways, and Amazon S3 gateway. The Amazon VPC console teams and user experience teams will continue to improve the console experience using customer feedback.

To learn more, see the Amazon VPC User Guide, and please send feedback to AWS re:Post for Amazon VPC or through your usual AWS support contacts.

Channy

Architecting your security model in AWS for legacy application migrations

Post Syndicated from Irfan Saleem original https://aws.amazon.com/blogs/architecture/architecting-your-security-model-in-aws-for-legacy-application-migrations/

Application migrations, especially from legacy/mainframe to the cloud, are done in phases that sometimes span multiple years. Each phase migrates a set of applications, data, and other resources to the cloud. During the transition phases, applications might require access to both on-premises and cloud-based resources to perform their function. While working with our customers, we observed that the most common resources that applications require access to are databases, file storage, and shared services.

This blog post includes architecture guidelines for setting up access to commonly used resources by building a security model in Amazon Web Services (AWS). As you move your legacy applications to the cloud, you can apply Zero Trust concepts and security best practices according to your security needs. With AWS, you can build strong identity and access management with centralized control and set up and manage guardrails and fine-grained access controls for your workforce and applications.

In large organizations, on-premises applications rely on mainframe-based security services, an Identity Provider (IdP) platform, or a combination of both.

  • A mainframe-based control facility enables on-premises applications to:
    • Identify and verify users.
    • Establish an authority (authorize users and backend programs to access protected resources) through privileges defined in the control facility.
    • The backend programs use a unique identifier (or surrogate key) and run under the authority defined by the privileges assigned to the unique identifier.This security mechanism needs to be transformed into a role-based security model in AWS as applications are moved to the cloud. You assign permissions to a role, which is assumed by an application to get access to resources in AWS, similar to an authority defined in the legacy environment.
  • An IdP platform (such as Octa or Ping Identify) provides capabilities such as centralized access management and identity federation using SAML 2.0 or OpenID Connect (OIDC), that builds a system of trust between on-premises IdP and AWS. Once the federation is set up, on-premises applications can access AWS resources using AWS Identity and Access Management (IAM) roles, as explained in the next section.

Setting up a scalable security model in AWS

Figure 1 shows an on-premises environment where enterprise identity management is integrated with the mainframe and provides authentication and authorization to applications running off the mainframe. Generally, mainframe-based security controls (users, resources, and profiles) are replicated to the enterprise identity platform and are kept in sync through a change data capture process.

Access to AWS resources from on-premises

Figure 1. Access to AWS resources from on-premises

To enable your on-premises applications to access AWS resources, the applications need valid AWS credentials for making AWS API requests. Avoid using long-term access keys (such as those associated with IAM users) because they remain valid until you remove them. The following two methods can be used to assume an IAM role and get temporary security credentials to gain access to the AWS resources:

  • SAML based Identity federation – AWS supports identity federation with SAML. It allows federated access to users and applications in your organization by assuming an IAM role created for SAML federation to get temporary credentials. This method is helpful:
    • If your application needs to restrict access to AWS resources based on logged in users. You can define attribute mapping and additional attributes as required.
    • If your application uses a service account to manage AWS resource access, regardless of who is logged in.
  • IAM Roles Anywhere – Your on-premises applications will exchange X.509 certificates so that they can assume a role and get temporary credentials. This method is helpful if your application needs access to an AWS resource based on a service account.

In both of these cases, authenticated requests assume an IAM role, get temporary security credentials, and perform certain actions using AWS command line interface (CLI) and AWS SDKs. The IAM role has attached permissions for AWS resources such as Amazon Simple Storage Service (Amazon S3), Amazon DynamoDB, and Amazon Relational Database Service (Amazon RDS).

The temporary credentials expire when the session expires. By default, the session duration is one hour; you can request longer duration and session refresh.

To understand better, let’s consider the use case in Figure 2, where on-premises applications need access to AWS resources.

Access to resources that are created or already migrated to AWS from on-premises

Figure 2. Access to resources that are created or already migrated to AWS from on-premises

Applications can get temporary security credentials through SAML or IAM Roles Anywhere as explained earlier. The next sections explain setting up access to the resources in Figure 2 using temporary credentials.

1. Amazon S3

On-premises applications can access Amazon S3 using the REST API or the AWS SDK to perform certain actions (such as GetObjects or ListObjects):

2. Amazon RDS and Amazon Aurora

AWS Secrets Manager helps you store credentials for Amazon RDS and Amazon Aurora. You can also set up automatic rotation of your database secrets to meet your security and compliance needs. Applications can retrieve secrets using AWS SDKs and AWS CLI.

Additional configuration values can be stored in AWS Systems Manager Parameter Store, which provides secure, hierarchical storage for configuration data management such as passwords, database strings and license codes as parameter values rather than hard coding them in the code.

To access Amazon RDS and Amazon Aurora:

    • You can launch Amazon RDS DB instances into a virtual private cloud (VPC). A client application can access DB instance through the internet or through the private network only using an established connection from on-premises to the AWS environment.
    • On-premises applications can connect to a relational database using a database driver such as Java Database Connectivity (JDBC). The application can retrieve database connection details (such as database URL, port, or credentials) from AWS Secrets Manager and AWS Systems Manager Parameter Store  through API calls and can use them for the database connection.
    • Database admins can access AWS Management Console through an assumed role and can have access to database credentials from AWS Secrets Manager in order to connect directly with the database. For certain administration tasks (such as cluster setup, backup, recovery, maintenance, and management), they will need access to the Amazon RDS management console.
    • Amazon RDS also provides IAM database authentication option for MariaDB, MySQL, and PostgreSQL. You can authenticate without a password when you connect to a DB instance. Instead, you use an authentication token. For more information, go to IAM database authentication.

3. Amazon DynamoDB

Applications can use temporary credentials to invoke certain actions using AWS SDKs for DynamoDB. You can create a VPC endpoint for DynamoDB to access DynamoDB with no exposure to the public internet, then restrict access further by using VPC endpoint and IAM policies.

Conclusion

This blog helps you architect an application security model in AWS to provide on-premises access to commonly used resources in AWS.

You can apply security best practices and Zero Trust concepts as you move your legacy applications to the cloud. With AWS, you can build identity and access management with centralized and fine-grained access controls for your workforce and applications.

Start building your security model on AWS:

Simplify data loading on the Amazon Redshift console with Informatica Data Loader

Post Syndicated from Deepak Rameswarapu original https://aws.amazon.com/blogs/big-data/simplify-data-loading-on-the-amazon-redshift-console-with-informatica-data-loader/

Amazon Redshift is the fastest, most widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Data engineers, data analysts, and data scientists want to use this data to power analytics workloads such as business intelligence (BI), predictive analytics, machine learning (ML), and real-time streaming analytics.

Informatica Intelligent Data Management Cloud™ (IDMC) is an AI-powered, metadata-driven, persona-based, cloud-native platform to empower data professionals with a comprehensive and cohesive cloud data management capabilities to discover, catalog, ingest, cleanse, integrate, govern, secure, prepare, and master data. Informatica Data Loader for Amazon Redshift, available on the AWS Management Console, is a zero-cost, serverless IDMC service that enables frictionless data loading to Amazon Redshift.

Customers need to bring data quickly and at scale from various data stores, including on-premises and legacy systems, third-party applications, and AWS services such as Amazon Relational Database Service (Amazon RDS), Amazon DynamoDB, and more. You also need a simple, easy, and cloud-native solution to quickly onboard new data sources or to analyze recent data for actionable insights. Now, with Informatica Data Loader for Amazon Redshift, you can securely connect and load data to Amazon Redshift at scale via a simple and guided interface. You can access Informatica Data Loader directly from the Amazon Redshift console.

This post provides step-by-step instructions to load data into Amazon Redshift using Informatica Data Loader.

Solution overview

You can access Informatica Data Loader directly from the navigation pane on the Amazon Redshift console. The process follows a similar workflow that Amazon Redshift users already use to access the Amazon Redshift query editor to author and organize SQL queries, or create datashares to share live data in read-only mode across clusters.

For this post, we use a Salesforce developer account as the data source. For instructions in importing a sample dataset, see Import Sample Account Data. You can use over 30 pre-built connectors supported by Informatica services to connect to the data source of your choice.

We use Informatica Data Loader to select and load a subset of Salesforce objects to Amazon Redshift in three simple steps:

  1. Connect to the data source.
  2. Connect to the target data source.
  3. Schedule or run the data load.

In addition to object-level filtering, the service also supports full and incremental loads, change data capture (CDC), column-based and row-based filtering, and schema drifts. After the data is loaded, you can run query and generate visualizations using Amazon Redshift Query Editor v2.0.

Prerequisites

Complete the following prerequisites:

  1. Create an Amazon Redshift cluster or workgroup. For more information, refer to Creating a cluster in a VPC or Amazon Redshift Serverless.
  2. Ensure that the cluster can be accessed from Informatica Data Loader. For a private cluster, add an ingress rule to the security group attached to your cluster to allow traffic from Informatica Data Loader. Allow-list the IP address for the cluster to be accessed from Informatica Data Loader. For more information about adding rules to an Amazon Elastic Compute Cloud (Amazon EC2) security group, see Authorize inbound traffic for your Linux instances.
  3. Create an Amazon Simple Storage Service (Amazon S3) bucket in the same Region as the Amazon Redshift cluster. The Informatica Data Loader will stage the data into this bucket before uploading the data to the cluster. Refer to Creating a bucket for more details. Make a note of the access key ID and secret access key for the user with permission to write to the staging S3 bucket.
  4. If you don’t have a Salesforce account, you can sign up for a free developer account.

Now that you have completed the prerequisites, let’s get started.

Launch Informatica Data Loader from the Amazon Redshift console

To launch Informatica Data Loader, complete the following steps:

  1. On the Amazon Redshift console, under AWS Partner Integration in navigation pane, choose Informatica Data Loader.
  2. In the pop-up window Create Informatica integration, choose Complete Informatica integration.
    If you’re accessing the free Informatica Data Loader for first time, you’re directed to the Informatica Data Loader for Amazon Redshift to sign up at no cost. You only need your email address to sign up.
  3. After you sign up, you can sign in to your Informatica account.

Connect to a data source

To connect to a data source, complete the following steps:

  1. On the Informatica Data Loader console, choose New in the navigation pane.
  2. Choose New Connection.
  3. Choose Salesforce as your source connection.
  4. Choose Continue.
  5. Under General Properties, enter a name for your connection and an optional description.
  6. Under Salesforce Connection Properties¸ enter the credentials for your Salesforce account and security token.These options may vary depending on the source type, connection type, and authentication method. For guidance, you can use the embedded connection configuration help video.
  7. Make a note of the connection name Salesforce_Source_Connection.
  8. Choose Test to verify the connection.
  9. Choose Add to save your connection details, and continue setting up the data loader.Now that you have connected to the Salesforce data source, you load the sample account information to Amazon Redshift. For this post, we load the Account object containing information on customer type and billing state or province, among other fields.
  10. Ensure that Salesforce_Source_Connection you just created is selected as Connection.
  11. To filter the Account object in Salesforce, select Include some under Define Object.
  12. Choose the plus sign to select the source object Account.
  13. In the pop-up window Select Source Object, search for account and choose Search.
  14. Select Account and choose OK.
  15. For this post, the rest of the following settings are left to their default value:
    1. Exclude fields – Exclude source fields from the source data.
    2. Define Filter – Filter rows from source data based on one or more specified filters.
    3. Define Primary Keys – Configuration to specify or detect the primary key column in the data source.
    4. Define Watermark Fields – Configuration to specify or detect the watermark column in the data source.

Connect to the target data source

To connect to the target data source (Amazon Redshift), complete the following steps:

  1. On the Informatica Data Loader, choose Connect Target.
  2. Choose New Connection.
  3. For Connection, choose Redshift (Amazon Redshift v2).
  4. Provide a connection name and optional description.
  5. Under Amazon Redshift Connection Section, enter your access key ID, secret access key, and the JDBC URL or your provisioned cluster or serverless workgroup.
  6. Choose Test to verify connectivity.
  7. After the connection is successful, choose Add.
  8. Optionally, for Target Name Prefix, enter the prefix to which the object name should be appended.
  9. For Path, enter the schema name public in Amazon Redshift where you want to load the data.
  10. For Load to existing tables, select No, create new tables every time.
  11. Choose Advanced Options to enter the name of the staging S3 bucket.
  12. Choose OK.

You have now successfully connected to a target Amazon Redshift cluster.

Schedule or run a data load

You can run your data load by choosing Run or expand the Schedule section to schedule it.

You can also monitor job status on the My Jobs page.

When your job status changes to Success, you can return to the Amazon Redshift console and open Query Editor V2.

In Amazon Redshift Query Editor v2.0, you can verify the loaded data by running the following query:

select * from public.”Account”;

Now we can do some more analysis. Let’s look at customer account by industry:

select 
    case when industry is NULL then 'Other'
    else industry end as Industry,
    case
        when type is NULL then 'Customer-Other'
        when type = '1' then 'Customer-Other'
        when type = '2' then 'Customer-Other'
        else type 
    end as CustomerType,
    count(*) as AggCount
from "dev"."public"."Account"
group by industry, type
order by aggcount desc

Also, we can use the charting capability of Query Editor V2 for visualization.

Simply choose the chart type and the value and label you want to chart.

Conclusion

The post demonstrates the integrated Amazon Redshift console experience of loading data with Informatica Data Loader and querying the data with Amazon Redshift Query Editor. With Informatica Data Loader, Amazon Redshift customers can quickly onboard new data sources in three simple steps and just-in-time bring data at scale to drive data-driven decisions.

You can sign up for Informatica Data Loader for Amazon Redshift and start loading data to Amazon Redshift.


About the authors

Deepak Rameswarapu is a Director of Product Management at Informatica. He is product leader with a strategic focus on new features and product launches, strategic product road map, AI/ML, cloud data integration, and data engineering and integration leadership. He brings 20 years of experience building best-of-breed products and solutions to address end-to-end data management challenges.

Rajeev Srinivasan is a Director of Technical Alliance, Ecosystem at Informatica. He leads the strategic technical partnership with AWS to bring needed and innovative solutions and capabilities into the hands of the customers. Along with customer obsession, he has a passion for data and cloud technologies, and riding his Harley.

Michael Yitayew is a Product Manager for Amazon Redshift based out of New York. He works with customers and engineering teams to build new features that enable data engineers and data analysts to more easily load data, manage data warehouse resources, and query their data. He has supported AWS customers for over 3 years in both product marketing and product management roles.

Phil Bates is a Senior Analytics Specialist Solutions Architect at AWS. He has more than 25 years of experience implementing large-scale data warehouse solutions. He is passionate about helping customers through their cloud journey and using the power of ML within their data warehouse.

Weifan Liang is a Senior Partner Solutions Architect at AWS. He works closely with AWS top strategic data analytics software partners to drive product integration, build optimized architecture, develop long-term strategy, and provide thought leadership. Innovating together with partners, Weifan strives to help customers accelerate business outcomes with cloud-powered digital transformation.

AWS Week in Review – November 21, 2022

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/aws-week-in-review-november-21-2022/

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS!

A new week starts, and the News Blog team is getting ready for AWS re:Invent! Many of us will be there next week and it would be great to meet in person. If you’re coming, do you know about PeerTalk? It’s an onsite networking program for re:Invent attendees available through the AWS Events mobile app (which you can get on Google Play or Apple App Store) to help facilitate connections among the re:Invent community.

If you’re not coming to re:Invent, no worries, you can get a free online pass to watch keynotes and leadership sessions.

Last Week’s Launches
It was a busy week for our service teams! Here are the launches that got my attention:

AWS Region in Spain – The AWS Region in Aragón, Spain, is now open. The official name is Europe (Spain), and the API name is eu-south-2.

Amazon Athena – You can now apply AWS Lake Formation fine-grained access control policies with all table and file format supported by Amazon Athena to centrally manage permissions and access data catalog resources in your Amazon Simple Storage Service (Amazon S3) data lake. With fine-grained access control, you can restrict access to data in query results using data filters to achieve column-level, row-level, and cell-level security.

Amazon EventBridge – With these additional filtering capabilities, you can now filter events by suffix, ignore case, and match if at least one condition is true. This makes it easier to write complex rules when building event-driven applications.

AWS Controllers for Kubernetes (ACK) – The ACK for Amazon Elastic Compute Cloud (Amazon EC2) is now generally available and lets you provision and manage EC2 networking resources, such as VPCs, security groups and internet gateways using the Kubernetes API. Also, the ACK for Amazon EMR on EKS is now generally available to allow you to declaratively define and manage EMR on EKS resources such as virtual clusters and job runs as Kubernetes custom resources. Learn more about ACK for Amazon EMR on EKS in this blog post.

Amazon HealthLake – New analytics capabilities make it easier to query, visualize, and build machine learning (ML) models. Now HealthLake transforms customer data into an analytics-ready format in near real-time so that you can query, and use the resulting data to build visualizations or ML models. Also new is Amazon HealthLake Imaging (preview), a new HIPAA-eligible capability that enables you to easily store, access, and analyze medical images at any scale. More on HealthLake Imaging can be found in this blog post.

Amazon RDS – You can now transfer files between Amazon Relational Database Service (RDS) for Oracle and an Amazon Elastic File System (Amazon EFS) file system. You can use this integration to stage files like Oracle Data Pump export files when you import them. You can also use EFS to share a file system between an application and one or more RDS Oracle DB instances to address specific application needs.

Amazon ECS and Amazon EKS – We added centralized logging support for Windows containers to help you easily process and forward container logs to various AWS and third-party destinations such as Amazon CloudWatch, S3, Amazon Kinesis Data Firehose, Datadog, and Splunk. See these blog posts for how to use this new capability with ECS and with EKS.

AWS SAM CLI – You can now use the Serverless Application Model CLI to locally test and debug an AWS Lambda function defined in a Terraform application. You can see a walkthrough in this blog post.

AWS Lambda – Now supports Node.js 18 as both a managed runtime and a container base image, which you can learn more about in this blog post. Also check out this interesting article on why and how you should use AWS SDK for JavaScript V3 with Node.js 18. And last but not least, there is new tooling support to build and deploy native AOT compiled .NET 7 applications to AWS Lambda. With this tooling, you can enable faster application starts and benefit from reduced costs through the faster initialization times and lower memory consumption of native AOT applications. Learn more in this blog post.

AWS Step Functions – Now supports cross-account access for more than 220 AWS services to process data, automate IT and business processes, and build applications across multiple accounts. Learn more in this blog post.

AWS Fargate – Adds the ability to monitor the utilization of the ephemeral storage attached to an Amazon ECS task. You can track the storage utilization with Amazon CloudWatch Container Insights and ECS Task Metadata endpoint.

AWS Proton – Now has a centralized dashboard for all resources deployed and managed by AWS Proton, which you can learn more about in this blog post. You can now also specify custom commands to provision infrastructure from templates. In this way, you can manage templates defined using the AWS Cloud Development Kit (AWS CDK) and other templating and provisioning tools. More on CDK support and AWS CodeBuild provisioning can be found in this blog post.

AWS IAM – You can now use more than one multi-factor authentication (MFA) device for root account users and IAM users in your AWS accounts. More information is available in this post.

Amazon ElastiCache – You can now use IAM authentication to access Redis clusters. With this new capability, IAM users and roles can be associated with ElastiCache for Redis users to manage their cluster access.

Amazon WorkSpaces – You can now use version 2.0 of the WorkSpaces Streaming Protocol (WSP) host agent that offers significant streaming quality and performance improvements, and you can learn more in this blog post. Also, with Amazon WorkSpaces Multi-Region Resilience, you can implement business continuity solutions that keep users online and productive with less than 30-minute recovery time objective (RTO) in another AWS Region during disruptive events. More on multi-region resilience is available in this post.

Amazon CloudWatch RUM – You can now send custom events (in addition to predefined events) for better troubleshooting and application specific monitoring. In this way, you can monitor specific functions of your application and troubleshoot end user impacting issues unique to the application components.

AWS AppSync – You can now define GraphQL API resolvers using JavaScript. You can also mix functions written in JavaScript and Velocity Template Language (VTL) inside a single pipeline resolver. To simplify local development of resolvers, AppSync released two new NPM libraries and a new API command. More info can be found in this blog post.

AWS SDK for SAP ABAP – This new SDK makes it easier for ABAP developers to modernize and transform SAP-based business processes and connect to AWS services natively using the SAP ABAP language. Learn more in this blog post.

AWS CloudFormation – CloudFormation can now send event notifications via Amazon EventBridge when you create, update, or delete a stack set.

AWS Console – With the new Applications widget on the Console home, you have one-click access to applications in AWS Systems Manager Application Manager and their resources, code, and related data. From Application Manager, you can view the resources that power your application and your costs using AWS Cost Explorer.

AWS Amplify – Expands Flutter support (developer preview) to Web and Desktop for the API, Analytics, and Storage use cases. You can now build cross-platform Flutter apps with Amplify that target iOS, Android, Web, and Desktop (macOS, Windows, Linux) using a single codebase. Learn more on Flutter Web and Desktop support for AWS Amplify in this post. Amplify Hosting now supports fully managed CI/CD deployments and hosting for server-side rendered (SSR) apps built using Next.js 12 and 13. Learn more in this blog post and see how to deploy a NextJS 13 app with the AWS CDK here.

Amazon SQS – With attribute-based access control (ABAC), you can define permissions based on tags attached to users and AWS resources. With this release, you can now use tags to configure access permissions and policies for SQS queues. More details can be found in this blog.

AWS Well-Architected Framework – The latest version of the Data Analytics Lens is now available. The Data Analytics Lens is a collection of design principles, best practices, and prescriptive guidance to help you running analytics on AWS.

AWS Organizations – You can now manage accounts, organizational units (OUs), and policies within your organization using CloudFormation templates.

For a full list of AWS announcements, be sure to keep an eye on the What’s New at AWS page.

Other AWS News
A few more stuff you might have missed:

Introducing our final AWS Heroes of the year – As the end of 2022 approaches, we are recognizing individuals whose enthusiasm for knowledge-sharing has a real impact with the AWS community. Please meet them here!

The Distributed Computing ManifestoWerner Vogles, VP & CTO at Amazon.com, shared the Distributed Computing Manifesto, a canonical document from the early days of Amazon that transformed the way we built architectures and highlights the challenges faced at the end of the 20th century.

AWS re:Post – To make this community more accessible globally, we expanded the user experience to support five additional languages. You can now interact with AWS re:Post also using Traditional Chinese, Simplified Chinese, French, Japanese, and Korean.

For AWS open-source news and updates, here’s the latest newsletter curated by Ricardo to bring you the most recent updates on open-source projects, posts, events, and more.

Upcoming AWS Events
As usual, there are many opportunities to meet:

AWS re:Invent – Our yearly event is next week from November 28 to December 2. If you can’t be there in person, get your free online pass to watch live the keynotes and the leadership sessions.

AWS Community DaysAWS Community Day events are community-led conferences to share and learn together. Join us in Sri Lanka (on December 6-7), Dubai, UAE (December 10), Pune, India (December 10), and Ahmedabad, India (December 17).

That’s all from me for this week. Next week we’ll focus on re:Invent, and then we’ll take a short break. We’ll be back with the next Week in Review on December 12!

Danilo

Introducing AWS Resource Explorer – Quickly Find Resources in Your AWS Account

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/introducing-aws-resource-explorer-quickly-find-resources-in-your-aws-account/

Looking for a specific Amazon Elastic Compute Cloud (Amazon EC2) instance, Amazon Elastic Container Service (Amazon ECS) task, or Amazon CloudWatch log group can take some time, especially if you have many resources and use multiple AWS Regions.

Today, we’re making that easier. Using the new AWS Resource Explorer, you can search through the AWS resources in your account across Regions using metadata such as names, tags, and IDs. When you find a resource in the AWS Management Console, you can quickly go from the search results to the corresponding service console and Region to start working on that resource. In a similar way, you can use the AWS Command Line Interface (CLI) or any of the AWS SDKs to find resources in your automation tools.

Let’s see how this works in practice.

Using AWS Resource Explorer
To start using Resource Explorer, I need to turn it on so that it creates and maintains the indexes that will provide fast responses to my search queries. Usually, the administrator of the account is the one taking these steps so that authorized users in that account can start searching.

To run a query, I need a view that gives access to an index. If the view is using an aggregator index, then the query can search across all indexed Regions.

Aggregator index diagram.

If the view is using a local index, then the query has access only to the resources in that Region.

Local index diagram.

I can control the visibility of resources in my account by creating views that define what resource information is available for search and discovery. These controls are not based only on resources but also on the information that resources bring. For example, I can give access to the Amazon Resource Names (ARNs) of all resources but not to their tags which might contain information that I want to keep confidential.

In the Resource Explorer console, I choose Enable Resource Explorer. Then, I select the Quick setup option to have visibility for all supported resources within my account. This option creates local indexes in all Regions and an aggregator index in the selected Region. A default view with a filter that includes all supported resources in the account is also created in the same Region as the aggregator index.

Console screenshot.

With the Advanced setup option, I have access to more granular controls that are useful when there are specific governance requirements. For example, I can select in which Regions to create indexes. I can choose not to replicate resource information to any other Region so that resources from each AWS Region are searchable only from within the same Region. I can also control what information is available in the default view or avoid the creation of the default view.

With the Quick setup option selected, I choose Go to Resource Explorer. A quick overview shows the progress of enabling Resource Explorer across Regions. After the indexes have been created, it can take up to 36 hours to index all supported resources, and search results might be incomplete until then. When resources are created or deleted, your indexes are automatically updated. These updates are asynchronous, so it can take some time (usually a few minutes) to see the changes.

Searching With AWS Resource Explorer
After resources have been indexed, I choose Proceed to resource search. In the Search criteria, I choose which View to use. Currently, I have the default view selected. Then, I start typing in the Query field to search through the resources in my AWS account across all Regions. For example, I have an application where I used the convention to start resource names with my-app. For the resources I created manually, I also added the Project tag with value MyApp.

To find the resource of this application, I start by searching for my-app.

Console screenshot.

The results include resources from multiple services and Regions and global resources from AWS Identity and Access Management (IAM). I have a service, tasks, and a task definition from Amazon ECS, roles and policies from AWS IAM, log groups from CloudWatch. Optionally, I can filter results by Region or resource type. If I choose any of the listed resources, the link will bring me to the corresponding service console and Region with the resource selected.

Console screenshot.

To look for something in a specific Region, such as Europe (Ireland), I can restrict the results by adding region:eu-west-1 to the query.

Console screenshot.

I can further restrict results to Amazon ECS resources by adding service:ecs to the query. Now I only see the ECS cluster, service, tasks, and task definition in Europe (Ireland). That’s the task definition I was looking for!

Console screenshot.

I can also search using tags. For example, I can see the resources where I added the MyApp tag by including tag.value:MyApp in a query. To specify the actual key-value pair of the tag, I can use tag:Project=MyApp.

Console screenshot.

Creating a Custom View
Sometimes you need to control the visibility of the resources in your account. For example, all the EC2 instances used for development in my account are in US West (Oregon). I create a view for the development team by choosing a specific Region (us-west-2) and filtering the results with service:ec2 in the query. Optionally, I could further filter results based on resource names or tags. For example, I could add tag:Environment=Dev to only see resources that have been tagged to be in a development environment.

Console screenshot.

Now I allow access to this view to users and roles used by the development team. To do so, I can attach an identity-based policy to the users and roles of the development team. In this way, they can only explore and search resources using this view.

Console screenshot.

Unified Search in the AWS Management Console
After I turn Resource Explorer on, I can also search through my AWS resources in the search bar at the top of the Management Console. We call this capability unified search as it gives results that include AWS services, features, blogs, documentation, tutorial, events, and more.

To focus my search on AWS resources, I add /Resources at the beginning of my search.

Console screenshot.

Note that unified search automatically inserts a wildcard character (*) at the end of the first keyword in the string. This means that unified search results include resources that match any string that starts with the specified keyword.

Console screenshot.

The search performed by the Query text box on the Resource search page in the Resource Explorer console does not automatically append a wildcard character but I can do it manually after any term in the search string to have similar results.

Unified search works when I have the default view in the same Region that contains the aggregator index. To check if unified search works for me, I look at the top of the Settings page.

Console screenshot.

Availability and Pricing
You can start using AWS Resource Explorer today with a global console and via the AWS Command Line Interface (CLI) and the AWS SDKs. AWS Resource Explorer is available at no additional charge. Using Resource Explorer makes it much faster to find the resources you need and use them in your automation processes and in their service console.

Discover and access your AWS resources across all the Regions you use with AWS Resource Explorer.

Danilo

AWS Week In Review – September 12, 2022

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/aws-week-in-review-september-12-2022/

I am working from London, UK, this week to record sessions for the upcoming Innovate EMEA online conference—more about this in a future Week In Review. While I was crossing the channel, I took the time to review what happened on AWS last week.

Last Week’s Launches
Here are some launches that got my attention:

Seekable OCI for lazy loading container images. Seekable OCI (SOCI) is a technology open sourced by AWS that enables containers to launch faster by lazily loading the container image. SOCI works by creating an index of the files within an existing container image. This index is a key enabler to launching containers faster, providing the capability to extract an individual file from a container image before downloading the entire archive. Check out the source code on GitHub.

Amazon Lookout for Metrics now lets you filter data by dimensions and increased the limits on the number of measures and dimensions. Lookout for Metrics uses machine learning (ML) to automatically detect and diagnose anomalies (i.e., outliers from the norm) in business and operational data, such as a sudden dip in sales revenue or customer acquisition rates.

Amazon SageMaker has three new capabilities. First, SageMaker Canvas added additional capabilities to explore and analyze data with advanced visualizations. Second, SageMaker Studio now sends API user identity data to AWS CloudTrail. And third, SageMaker added TensorFlow image classification to its list of builtin algorithms.

The AWS console launches a widget to display the most recent AWS blog posts on the console landing page. Being part of the AWS News Blog team, I couldn’t be more excited about a launch this week. 😀

AW Console Blog widget

Other AWS News
Some other updates and news that you may have missed:

The Amazon Science blog published an article on the design of a pinch grasping robot. It is one of the many areas where we try to improve the efficiency of our fulfillment centers. A must-read if you’re into robotics or logistics.

The Public Sector blog has an article on how Satellogic and AWS are harnessing the power of space and cloud. Satellogic is creating a live catalog of Earth and delivering daily updates to create a complete picture of changes to our planet for decision-makers. Satellogic is generating massive volumes of data, with each of its satellites collecting an average of 50GB of data daily. They are using compute, storage, analytics, and ground station infrastructure in support of their growth.

Event Ruler is now open-source. Talking about open-source, the source code of the core rule engine built first for Amazon CloudWatch Events, and now the core of Amazon Event Bridge, is newly available on GitHub. This is a Java library that allows applications to identify events that match a set of rules. Events and rules are expressed as JSON documents. Rules are compiled for fast evaluation by a finite state engine. Read the announcement blog post to understand how Event Bridge works under the hood.

HP Anyware (formerly Teradici CAS) is now available for Amazon EC2 Mac instances, from the AWS Marketplace. HP Anyware is a remote access solution that provides pixel-perfect rendering for your remote Mac Mini running in the AWS cloud. It uses PCoIP™ to securely and efficiently access the remote macOS machines. You can connect from anywhere, using a PCoIP client application or from thin terminals such as Thin Clients or Zero Clients workstations.

Upcoming AWS Events
Check your calendars and sign up for these AWS events that are happening all over the world:

AWS Summits – Come together to connect, collaborate, and learn about AWS. Registration is open for the following in-person AWS Summits: Mexico City (September 21–22), Bogotá (October 4), and Singapore (October 6).

AWS Community DaysAWS Community Day events are community-led conferences to share and learn with one another. In September, the AWS community in the US will run events in Arlington, Virginia (September 30). In Europe, Community Day events will be held in October. Join us in Amersfoort, Netherlands (October 3), Warsaw, Poland (October 14), and Dresden, Germany (October 19).

That’s all from me for this week. Come back next Monday for another Week in Review!

— seb

 

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS!

Automate the Creation of On-Demand Capacity Reservations for running EC2 instances

Post Syndicated from sbbusser original https://aws.amazon.com/blogs/compute/automate-the-creation-of-on-demand-capacity-reservations-for-running-ec2-instances/

This post is written by Ballu Singh a Principal Solutions Architect at AWS, Neha Joshi a Senior Solutions Architect at AWS, and Naveen Jagathesan a Technical Account Manager at AWS.

Customers have asked how they can “create On-Demand Capacity Reservations (ODCRs) for their existing instances during events, such as the holiday season, Black Friday, marketing campaigns, or others?”

ODCRs let you reserve compute capacity for your your Amazon Elastic Compute Cloud (Amazon EC2) instances. ODCRs further make sure that you always have EC2 capacity access when required, and for as long as you need it. Customers who want to make sure that any instances that are stopped/started during the critical event and are available when needed should be covered by ODCRs.

ODCRs let you reserve compute capacity for your Amazon EC2 instances in a specific availability zone for any duration. This means that you can create and manage capacity reservations independently from the billing discounts offered by Savings Plans or Regional Reserved Instances. You can create ODCR at any time, without entering into a one-year or three-year term commitment, and the capacity is available immediately. Billing starts as soon as the ODCR enters the active state. When you no longer need it, cancel the ODCR to stop incurring charges.

At the time of this blog publication, if you need to create ODCR for existing running instances, you must manually identify your running instances configuration with matching attributes, such as instance type, platform, and Availability Zone. This is a time and resource consuming process.

In this post, we provide an automated way to manage ODCR operations. This includes creating, modifying, and cancelling ODCRs for the running instances across regions in an account, all without requiring any manual intervention of specifying instance configuration attributes. Additionally, it creates an Amazon CloudWatch Alarm for InstanceUtilization and an Amazon Simple Notification Service (Amazon SNS) topic with topic name ODCRAlarmNotificationTopic to notify when the threshold breaches.

Note: This will not create cluster placement group ODCRs. For details on capacity reservations in cluster placement groups, refer here.

Getting started

Before you create Capacity Reservations, note the limitations and restrictions here.

To get started, download the scripts for registering, modifying, and canceling ODCRs and associated requirements.txt, as well as AWS Identity and Access Management (IAM) policy from the GitHub link here.

Pre-requisites

To implement these scripts, you need the following prerequisites:

  1. Access to AWS Management Console, AWS Command Line Interface (CLI),or AWS SDK for ODCR.
  2. The following IAM role permissions for IAM users using the solution as provided in ODCR_IAM.json.
  3. Amazon EC2 instance having supported platform for capacity reservation. Capacity Reservations support the following platforms listed here for Linux and Windows.
  4. Refer to the above GitHub link for the code, and save the requirements.txt file in the same directory with other python scripts. You may want to run the requirements.txt file if you don’t have appropriate dependency to run the rest of the python scripts. You can run this using the following command:
pip3 install -r requirements.txt

Implementation Details

To create ODCR capacity reservation

The following instructions will guide you through creating a capacity reservation of running instances across all of the Regions within an AWS account.
Input variables needed from users:

  • EndDateType (String) – Indicates how the Capacity Reservation ends. A Capacity Reservation can have one of the following end types:
      • unlimited – The Capacity Reservation remains active until you explicitly cancel it. Don’t provide an EndDate if the EndDateType is unlimited.
      • limited – The Capacity Reservation expires automatically at a specified date and time. You must provide an EndDate value if the EndDateType value is limited.
  • EndDate (datetime) – The date and time when the Capacity Reservation expires. When a Capacity Reservation expires, the reserved capacity is released and you can no longer launch instances into it. The Capacity Reservation’s state changes to expired when it reaches its end date and time.

You must provide EndDateType as ‘limited’ and the EndDate in standard UTC format to secure instances for a limited period. Command to execute register ODCR script with limited period:

You must provide EndDateType as ‘unlimited’ to secure instances for unlimited period. Command to execute register ODCR script with unlimited period:

registerODCR.py '<EndDateType>' '<EndDate>'
    Example- registerODCR.py 'limited' '2022-01-31 14:30:00'
  • You must provide EndDateType as ‘unlimited’ to secure instances for unlimited period. Command to execute register ODCR script with unlimited period:
registerODCR.py 'EndDateType'
    Example- registerODCR.py 'unlimited'

This registerODCR.py script does following four things:

1. Describe instances cross-region in an account. It checks for the instance that has:

    • No Capacity reservation
    • State of the instance is running
    • Tenancy is default
    • InstanceLifecycle is None indicates whether this is a Spot Instance or a Scheduled Instance

Note: Describe instances API call is counted toward your account API limit. Therefore, it is advisable to run the script during non-peak hours or before the short-term scaling event begins. Work with AWS Support team if you run into API throttling.

2. Aggregates instances with similar attributes, such as InstanceType, AvailabilityZone, Tenancy, and Platform.

3. Describe reserved instances cross-region in an account. It checks for instance(s) that have Zonal Reservation Instances (ZRIs) and compares them with aggregated instances with similar attributes.

4. Finally,

    • Reserves ODCR(s) for existing running instances with matching attributes for which ZRIs do not exist.

Note: If you have one or more ZRIs in an account, then the script compares them with the existing instances with matching characteristics – Instance Type, AZ, and Platform – and does NOT create ODCR for the ZRIs to avoid incurring redundant charges. If there are more running instances than ZRIs, then the script creates an ODCR for just the delta.

    • Creates an SNS topic with the topic name – ODCRAlarmNotificationTopic in the region where you’re registering ODCR, if it doesn’t already exist.
    • Creates CloudWatch alarm for InstanceUtilization using the best practices, which can be found here.

Note: You must subscribe and confirm to the SNS topic, if you haven’t already, to receive notifications.

The CloudWatch alarm is also created on your behalf in the region for each ODCR. This alarm monitors your ODCR metric- InstanceUtilization. Whenever it breaches threshold (50% in this case), it enters the alarm state and sends an SNS notification using the topic that was created for you if you subscribed to it.

Note: You can change the alarm threshold based on your specific needs.

  • You will receive an email notification when CloudWatch Alarm State changes to Alarm with:
    • SNS Subject (Assuming CW alarms triggers in US East region).
ALARM: "ODCRAlarm-cr-009969c7abf4daxxx" in US East (N. Virginia)
    • SNS Body will have the details
      • CW alarm, region, link to view the alarm, alarm details, and state change actions.

With this, if your ODCR InstanceUtilization drops, then you will be notified in near-real time to help you optimize the capacity and stop unnecessary payments for unused capacity.

To modify ODCR capacity reservation

To modify the attributes of an active capacity reservation after you have created it, adhere to the following instructions.

Note: When modifying a Capacity Reservation, you can only increase or decrease the quantity and change how it is released. You can’t change the instance type, EBS optimization, instance store settings, platform, Availability Zone, or instance eligibility of a Capacity Reservation. If you must modify any of these attributes, then we recommend that you cancel the reservation, and then create a new one with the required attributes. You can’t modify a Capacity Reservation after it has expired or after you have explicitly canceled it.

  • Input variables needed from users:
    • CapacityReservationID – The ID of the Capacity Reservation that you want to modify.
    • InstanceCount (integer) – The number of instances for which to reserve capacity. The number of instances can’t be increased or decreased by more than 1000 in a single request.
    • EndDateType (String) – Indicates how the Capacity Reservation ends. A Capacity Reservation can have one of the following end types:
      • unlimited – The Capacity Reservation remains active until you explicitly cancel it. Don’t provide an EndDate if the EndDateType is unlimited.
      • limited – The Capacity Reservation expires automatically at a specified date and time. You must provide an EndDate value if the EndDateType value is limited.
    • EndDate (datetime) – The date and time of when the Capacity Reservation expires. When a Capacity Reservation expires, the reserved capacity is released, and you can no longer launch
    • instances into it. The Capacity Reservation’s state changes to expired when it reaches its end date and time.
      Example to run the modify ODCR script for ‘limited’ period:
    • You must provide EndDateType as ‘unlimited’ to modify instances for an unlimited period. Command to the run modify ODCR script with unlimited period:
  • Command to execute modify ODCR script:
    modifyODCR.py <CapacityReservationId> <InstanceCount> <EndDateType> <EndDate> 
  • Example to execute the modify ODCR script for limited period:
modifyODCR.py 'cr-05e6a94b99915xxxx' '1' 'limited' '2022-01-31 14:30:00'

Note: EndDate is in the standard UTC time.

  • You must provide EndDateType as ‘unlimited’ to modify instances for unlimited period. Command to execute modify ODCR script with unlimited period:
modifyODCR.py <CapacityReservationId> <InstanceCount> <EndDateType>
  • Example to execute the modify ODCR script for unlimited period:
modifyODCR.py 'cr-05e6a94b99915xxxx' '1' 'unlimited'

To cancel ODCR capacity reservation

To cancel the ODCR that are in the “Active” state, follow these instructions:

Note: Once the cancellation request succeeds, the reservation status will be marked as “cancelled”.

  • Input variables needed from users:
    • CapacityReservationID – The ID of the Capacity Reservation to cancel.
  • You must provide one parameter while executing the cancellation script.
  • Command to execute cancel ODCR script:
cancelODCR.py <CapacityReservationId> 
  • Example to execute the cancel ODCR script:
Example - cancelODCR.py 'cr-05e6a94b99915xxxx'

Monitoring

CloudWatch metrics let you monitor the unused capacity in your Capacity Reservations to optimize the ODCR. ODCRs send metric data to CloudWatch every five minutes. Although Capacity Reservation usage metrics are UsedInstanceCount, AvailableInstanceCount, TotalInstanceCount, and InstanceUtilization, for this solution we will be using the InstanceUtilization metric. This shows the percentage of reserved capacity instances that are currently in use. This will be useful for monitoring and optimizing ODCR consumption.

For example, if your On-Demand Capacity Reservation is for four instances and with matching criteria only one EC2 instance is currently running, then the InstanceUtilization metric will be 25% for your respective capacity reservation.

Let’s look at the steps to create the CloudWatch monitoring dashboard for your On-Demand Capacity Reservation solution:

  1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
  2. If necessary, change the Region. From the navigation bar, select the Region where your Capacity Reservation resides. For more information, see Regions and Endpoints.
  3. In the navigation pane, choose Metrics.

Amazon CloudWatch Dashboard

For All metrics, choose EC2 Capacity Reservations.

Amazon CloudWatch Dashboard: Metrics

4. Choose the metric dimension By Capacity Reservation. Metrics will be grouped by

Amazon CloudWatch Metrics: Capacity Reservation Ids

5. Select the dropdown arrow for InstanceUtilization, and select Search for this only.

Amazon CloudWatch Metrics Filter

Once we see the InstanceUtilization metric in the filter list, select Graph Search.

Amazon CloudWatch Metrics: Graph Search

This displays the InstanceUtilization metrics for the selected period.

Amazon CloudWatch Metrics Duration

OPTIONAL: To display the Capacity Reservation IDs for active metrics only:

    • Navigate to Graphed metrics.

Amazon CloudWatch: Graphed Metrics

    • Under Details column, select Edit math expression.

Amazon CloudWatch Metrics: Math Expression

    • Edit the math expression with the following, and select Apply:
REMOVE_EMPTY(SEARCH('{AWS/EC2CapacityReservations,CapacityReservationId} MetricName="InstanceUtilization"', 'Average', 300))

Amazon CloudWatch Graphed Metrics: Math Expression Apply

This displays the Capacity Reservation IDs for active metrics only.

Amazon CloudWatch Metrics: Active Capacity Reservation Ids

With this configuration, whenever new Capacity Reservations are created, the InstanceUtilization metric for respective Capacity Reservation IDs will be populated.

6. From the Actions drop-down menu, select Add to dashboard.

Amazon CloudWatch Metrics: Add to Dashboard

Select Create new to create a new dashboard for monitoring your ODCR metrics.

Amazon CloudWatch: Creat New Dashboard

Specify the new dashboard name, and select Add to dashboard.

Amazon CloudWatch: Create New Dashboard

7. These configuration steps will navigate you to your newly created CloudWatch dashboard under Dashboards.

Amazon CloudWatch Dashboard: ODCR Metrics

Once this is created, if you create new Capacity Reservations, or new instances get added to existing reservations, then those metrics will be automatically be added to your CloudWatch Dashboard.

Note: You may see a delay of approximately 5-10 minutes from the point when changes are made to your environment (ODCR operations or instances launch/termination activities) to those changes getting reflected on your CloudWatch Dashboard metrics.

Conclusion

In this post, we discussed a solution for automating ODCR operations for existing EC2 instances. This included creating capacity reservation, modifying capacity reservation, and cancelling capacity reservation operations that inherit your existing EC2 instances for attribute details. We also discussed monitoring aspects of ODCR metrics using CloudWatch. This solution allows you to automate some of the ODCR operations for existing instances, thereby optimizing and speeding up the entire process.

For more information, see Target a group of Amazon EC2 On-Demand Capacity Reservations blog and Capacity Reservations documentation.

If you have feedback or questions about this post, please submit your comments in the comments section or contact AWS Support.

A New AWS Console Home Experience

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/a-new-aws-console-home-experience/

If you are reading this blog, there is a high chance you frequently use the AWS Management Console. I taught AWS classes for years. During classes, students’ first hands-on experience with the AWS Cloud happened on the console, and I bet yours did too.

Until today, the home page of the console showed your most recently used services and a set of static links organized in sections, such as Getting Started with AWS, Build a Solution, or Explore AWS with links to training courses. However, we learned from our data that their usage is very different depending on your profile. You also told us it is cumbersome and time-consuming to navigate to different parts of the console to get an overview of important information for you.

We listened to your feedback, and I’m happy to announce a redesigned home page for the AWS Management Console. This new home page experience includes dynamic content, can be customized, and includes data from multiple AWS Regions.

The screenshot below shows the default view of this new console home page:

New console default layout

New console homepage action

The new Console Home is made of widgets. I may choose which widget to display on the page and where to include it. I may use the actions in the Actions drop down to customize my home page.

I may move and arrange widgets on the home page to organize the content as I want. When I click on the three little dots on the widget title bar, I may choose to remove the widget or resize it. I have the choice between Regular view and Extended view.

New console resize widget

At launch, the console provides eight widgets, and we will add more over time. Three widgets provide me with static links to learn how to build a solution or to explore AWS (Welcome to AWS, Build a Solution and Explore AWS). The other five are dynamic; their content depends on the usage of AWS by my applications and infrastructure:

  • AWS Health: this widget provides information on important events and changes
  • Cost and usage: this widget provides an overview of service costs, with a break down per AWS service.
  • Favorites: this widget shows a list of services that I have bookmarked
  • Recently visited: this widget provides the list of top recently visited services
  • Trusted Advisor: this widget provides recommendations to follow AWS best practices

AWS News Console List of widgets

As usual, we pay attention to the importance of not disturbing existing workflows and habits. You can use the new Console Home after opt-in. You can revert back to the old console home with a simple click.

This new Console Home is the first step to bring you more relevant content on this very first page you see every day. Stay tuned for more.

The new Console Home is available today in all AWS Regions at no additional cost. Go and customize your console homepage today.

— seb

Managing temporary elevated access to your AWS environment

Post Syndicated from James Greenwood original https://aws.amazon.com/blogs/security/managing-temporary-elevated-access-to-your-aws-environment/

In this post you’ll learn about temporary elevated access and how it can mitigate risks relating to human access to your AWS environment. You’ll also be able to download a minimal reference implementation and use it as a starting point to build a temporary elevated access solution tailored for your organization.

Introduction

While many modern cloud architectures aim to eliminate the need for human access, there often remain at least some cases where it is required. For example, unexpected issues might require human intervention to diagnose or fix, or you might deploy legacy technologies into your AWS environment that someone needs to configure manually.

AWS provides a rich set of tools and capabilities for managing access. Users can authenticate with multi-factor authentication (MFA), federate using an external identity provider, and obtain temporary credentials with limited permissions. AWS Identity and Access Management (IAM) provides fine-grained access control, and AWS Single Sign-On (AWS SSO) makes it easy to manage access across your entire organization using AWS Organizations.

For higher-risk human access scenarios, your organization can supplement your baseline access controls by implementing temporary elevated access.

What is temporary elevated access?

The goal of temporary elevated access is to ensure that each time a user invokes access, there is an appropriate business reason for doing so. For example, an appropriate business reason might be to fix a specific issue or deploy a planned change.

Traditional access control systems require users to be authenticated and authorized before they can access a protected resource. Becoming authorized is typically a one-time event, and a user’s authorization status is reviewed periodically—for example as part of an access recertification process.

With persistent access, also known as standing access, a user who is authenticated and authorized can invoke access at any time just by navigating to a protected resource. The process of invoking access does not consider the reason why they are invoking it on each occurrence. Today, persistent access is the model that AWS Single Sign-On supports, and is the most common model used for IAM users and federated users.

With temporary elevated access, also known as just-in-time access, users must be authenticated and authorized as before—but furthermore, each time a user invokes access an additional process takes place, whose purpose is to identify and record the business reason for invoking access on this specific occasion. The process might involve additional human actors or it might use automation. When the process completes, the user is only granted access if the business reason is appropriate, and the scope and duration of their access is aligned to the business reason.

Why use temporary elevated access?

You can use temporary elevated access to mitigate risks related to human access scenarios that your organization considers high risk. Access generally incurs risk when two elements come together: high levels of privilege, such as ability to change configuration, modify permissions, read data, or update data; and high-value resources, such as production environments, critical services, or sensitive data. You can use these factors to define a risk threshold, above which you enforce temporary elevated access, and below which you continue to allow persistent access.

Your motivation for implementing temporary elevated access might be internal, based on your organization’s risk appetite; or external, such as regulatory requirements applicable to your industry. If your organization has regulatory requirements, you are responsible for interpreting those requirements and determining whether a temporary elevated access solution is required, and how it should operate.

Regardless of the source of requirement, the overall goal is to reduce risk.

Important: While temporary elevated access can reduce risk, the preferred approach is always to automate your way out of needing human access in the first place. Aim to use temporary elevated access only for infrequent activities that cannot yet be automated. From a risk perspective, the best kind of human access is the kind that doesn’t happen at all.

The AWS Well-Architected Framework provides guidance on using automation to reduce the need for human user access:

How can temporary elevated access help reduce risk?

In scenarios that require human intervention, temporary elevated access can help manage the risks involved. It’s important to understand that temporary elevated access does not replace your standard access control and other security processes, such as access governance, strong authentication, session logging and monitoring, and anomaly detection and response. Temporary elevated access supplements the controls you already have in place.

The following are some of the ways that using temporary elevated access can help reduce risk:

1. Ensuring users only invoke elevated access when there is a valid business reason. Users are discouraged from invoking elevated access habitually, and service owners can avoid potentially disruptive operations during critical time periods.

2. Visibility of access to other people. With persistent access, user activity is logged—but no one is routinely informed when a user invokes access, unless their activity causes an incident or security alert. With temporary elevated access, every access invocation is typically visible to at least one other person. This can arise from their participation in approvals, notifications, or change and incident management processes which are multi-party by nature. With greater visibility to more people, inappropriate access by users is more likely to be noticed and acted upon.

3. A reminder to be vigilant. Temporary elevated access provides an overt reminder for users to be vigilant when they invoke high-risk access. This is analogous to the kind security measures you see in a physical security setting. Imagine entering a secure facility. You see barriers, fences, barbed wire, CCTV, lighting, guards, and signs saying “You are entering a restricted area.” Temporary elevated access has a similar effect. It reminds users there is a heightened level of control, their activity is being monitored, and they will be held accountable for any actions they perform.

4. Reporting, analytics, and continuous improvement. A temporary elevated access process records the reasons why users invoke access. This provides a rich source of data to analyze and derive insights. Management can see why users are invoking access, which systems need the most human access, and what kind of tasks they are performing. Your organization can use this data to decide where to invest in automation. You can measure the amount of human access and set targets to reduce it. The presence of temporary elevated access might also incentivize users to automate common tasks, or ask their engineering teams to do so.

Implementing temporary elevated access

Before you examine the reference implementation, first take a look at a logical architecture for temporary elevated access, so you can understand the process flow at a high level.

A typical temporary elevated access solution involves placing an additional component between your identity provider and the AWS environment that your users need to access. This is referred to as a temporary elevated access broker, shown in Figure 1.
 

Figure 1: A logical architecture for temporary elevated access

Figure 1: A logical architecture for temporary elevated access

When a user needs to perform a task requiring temporary elevated access to your AWS environment, they will use the broker to invoke access. The broker performs the following steps:

1. Authenticate the user and determine eligibility. The broker integrates with your organization’s existing identity provider to authenticate the user with multi-factor authentication (MFA), and determine whether they are eligible for temporary elevated access.

Note: Eligibility is a key concept in temporary elevated access. You can think of it as pre-authorization to invoke access that is contingent upon additional conditions being met, described in step 3. A user typically becomes eligible by becoming a trusted member of a team of admins or operators, and the scope of their eligibility is based on the tasks they’re expected to perform as part of their job function. Granting and revoking eligibility is generally based on your organization’s standard access governance processes. Eligibility can be expressed as group memberships (if using role-based access control, or RBAC) or user attributes (if using attribute-based access control, or ABAC). Unlike regular authorization, eligibility is not sufficient to grant access on its own.

2. Initiate the process for temporary elevated access. The broker provides a way to start the process for gaining temporary elevated access. In most cases a user will submit a request on their own behalf—but some broker designs allow access to be initiated in other ways, such as an operations user inviting an engineer to assist them. The scope of a user’s requested access must be a subset of their eligibility. The broker might capture additional information about the context of the request in order to perform the next step.

3. Establish a business reason for invoking access. The broker tries to establish whether there is a valid business reason for invoking access with a given scope on this specific occasion. Why does this user need this access right now? The process of establishing a valid business reason varies widely between organizations. It might be a simple approval workflow, a quorum-based authorization, or a fully automated process. It might integrate with existing change and incident management systems to infer the business reason for access. A broker will often provide a way to expedite access in a time-critical emergency, which is a form of break-glass access. A typical broker implementation allows you to customize this step.

4. Grant time-bound access. If the business reason is valid, the broker grants time-bound access to the AWS target environment. The scope of access that is granted to the user must be a subset of their eligibility. Further, the scope and duration of access granted should be necessary and sufficient to fulfill the business reason identified in the previous step, based on the principle of least privilege.

A minimal reference implementation for temporary elevated access

To get started with temporary elevated access, you can deploy a minimal reference implementation accompanying this blog post. Information about deploying, running and extending the reference implementation is available in the Git repo README page.

Note: You can use this reference implementation to complement the persistent access that you manage for IAM users, federated users, or manage through AWS Single Sign-On. For example, you can use the multi-account access model of AWS SSO for persistent access management, and create separate roles for temporary elevated access using this reference implementation.

To establish a valid business reason for invoking access, the reference implementation uses a single-step approval workflow. You can adapt the reference implementation and replace this with a workflow or business logic of your choice.

To grant time-bound access, the reference implementation uses the identity broker pattern. In this pattern, the broker itself acts as an intermediate identity provider which conditionally federates the user into the AWS target environment granting a time-bound session with limited scope.

Figure 2 shows the architecture of the reference implementation.
 

Figure 2: Architecture of the reference implementation

Figure 2: Architecture of the reference implementation

To illustrate how the reference implementation works, the following steps walk you through a user’s experience end-to-end, using the numbers highlighted in the architecture diagram.

Starting the process

Consider a scenario where a user needs to perform a task that requires privileged access to a critical service running in your AWS environment, for which your security team has configured temporary elevated access.

Loading the application

The user first needs to access the temporary elevated access broker so that they can request the AWS access they need to perform their task.

  1. The user navigates to the temporary elevated access broker in their browser.
  2. The user’s browser loads a web application using web static content from an Amazon CloudFront distribution whose target is an Amazon S3 bucket.

The broker uses a web application that runs in the browser, known as a Single Page Application (SPA).

Note: CloudFront and S3 are only used for serving web static content. If you prefer, you can modify the solution to serve static content from a web server in your private network.

Authenticating users

  1. The user is redirected to your organization’s identity provider to authenticate. The reference implementation uses the OpenID Connect Authorization Code flow with Proof Key for Code Exchange (PKCE).
  2. The user returns to the application as an authenticated user with an access token and ID token signed by the identity provider.

The access token grants delegated authority to the browser-based application to call server-side APIs on the user’s behalf. The ID token contains the user’s attributes and group memberships, and is used for authorization.

Calling protected APIs

  1. The application calls APIs hosted by Amazon API Gateway and passes the access token and ID token with each request.
  2. For each incoming request, API Gateway invokes a Lambda authorizer using AWS Lambda.

The Lambda authorizer checks whether the user’s access token and ID token are valid. It then uses the ID token to determine the user’s identity and their authorization based on their group memberships.

Displaying information

  1. The application calls one of the /get… API endpoints to fetch data about previous temporary elevated access requests.
  2. The /get… API endpoints invoke Lambda functions which fetch data from a table in Amazon DynamoDB.

The application displays information about previously-submitted temporary elevated access requests in a request dashboard, as shown in Figure 3.
 

Figure 3: The request dashboard

Figure 3: The request dashboard

Submitting requests

A user who is eligible for temporary elevated access can submit a new request in the request dashboard by choosing Create request. As shown in Figure 4, the application then displays a form with input fields for the IAM role name and AWS account ID the user wants to access, a justification for invoking access, and the duration of access required.
 

Figure 4: Submitting requests

Figure 4: Submitting requests

The user can only request an IAM role and AWS account combination for which they are eligible, based on their group memberships.

Note: The duration specified here determines a time window during which the user can invoke sessions to access the AWS target environment if their request is approved. It does not affect the duration of each session. Session duration can be configured independently.

  1. When a user submits a new request for temporary elevated access, the application calls the /create… API endpoint, which writes information about the new request to the DynamoDB table.

The user can submit multiple concurrent requests for different role and account combinations, as long as they are eligible.

Generating notifications

The broker generates notifications when temporary elevated access requests are created, approved, or rejected.

  1. When a request is created, approved, or rejected, a DynamoDB stream record is created for notifications.
  2. The stream record then invokes a Lambda function to handle notifications.
  3. The Lambda function reads data from the stream record, and generates a notification using Amazon Simple Notification Service (Amazon SNS).

By default, when a user submits a new request for temporary elevated access, an email notification is sent to all authorized reviewers. When a reviewer approves or rejects a request, an email notification is sent to the original requester.

Reviewing requests

A user who is authorized to review requests can approve or reject requests submitted by other users in a review dashboard, as shown in Figure 5. For each request awaiting their review, the application displays information about the request, including the business justification provided by the requester.
 

Figure 5: The review dashboard

Figure 5: The review dashboard

The reviewer can select a request, determine whether the request is appropriate, and choose either Approve or Reject.

  1. When a reviewer approves or rejects a request, the application calls the /approve… or /reject… API endpoint, which updates the status of the request in the DynamoDB table and initiates a notification.

Invoking sessions

After a requester is notified that their request has been approved, they can log back into the application and see their approved requests, as shown in Figure 6. For each approved request, they can invoke sessions. There are two ways they can invoke a session, by choosing either Access console or CLI.

Figure 6: Invoking sessions

Figure 6: Invoking sessions

Both options grant the user a session in which they assume the IAM role in the AWS account specified in their request.

When a user invokes a session, the broker performs the following steps.

  1. When the user chooses Access console or CLI, the application calls one of the /federate… API endpoints.
  2. The /federate… API endpoint invokes a Lambda function, which performs the following three checks before proceeding:
    1. Is the user authenticated? The Lambda function checks that the access and ID tokens are valid and uses the ID token to determine their identity.
    2. Is the user eligible? The Lambda function inspects the user’s group memberships in their ID token to confirm they are eligible for the AWS role and account combination they are seeking to invoke.
    3. Is the user elevated? The Lambda function confirms the user is in an elevated state by querying the DynamoDB table, and verifying whether there is an approved request for this user whose duration has not yet ended for the role and account combination they are seeking to invoke.
  3. If all three checks succeed, the Lambda function calls sts:AssumeRole to fetch temporary credentials on behalf of the user for the IAM role and AWS account specified in the request.
  4. The application returns the temporary credentials to the user.
  5. The user obtains a session with temporary credentials for the IAM role in the AWS account specified in their request, either in the AWS Management Console or AWS CLI.

Once the user obtains a session, they can complete the task they need to perform in the AWS target environment using either the AWS Management Console or AWS CLI.

The IAM roles that users assume when they invoke temporary elevated access should be dedicated for this purpose. They must have a trust policy that allows the broker to assume them. The trusted principal is the Lambda execution role used by the broker’s /federate… API endpoints. This ensures that the only way to assume those roles is through the broker.

In this way, when the necessary conditions are met, the broker assumes the requested role in your AWS target environment on behalf of the user, and passes the resulting temporary credentials back to them. By default, the temporary credentials last for one hour. For the duration of a user’s elevated access they can invoke multiple sessions through the broker, if required.

Session expiry

When a user’s session expires in the AWS Management Console or AWS CLI, they can return to the broker and invoke new sessions, as long as their elevated status is still active.

Ending elevated access

A user’s elevated access ends when the requested duration elapses following the time when the request was approved.
 

Figure 7: Ending elevated access

Figure 7: Ending elevated access

Once elevated access has ended for a particular request, the user can no longer invoke sessions for that request, as shown in Figure 7. If they need further access, they need to submit a new request.

Viewing historical activity

An audit dashboard, as shown in Figure 8, provides a read-only view of historical activity to authorized users.
 

Figure 8: The audit dashboard

Figure 8: The audit dashboard

Logging session activity

When a user invokes temporary elevated access, their session activity in the AWS control plane is logged to AWS CloudTrail. Each time they perform actions in the AWS control plane, the corresponding CloudTrail events contain the unique identifier of the user, which provides traceability back to the identity of the human user who performed the actions.

The following example shows the userIdentity element of a CloudTrail event for an action performed by user [email protected] using temporary elevated access.

"userIdentity": {
    "type": "AssumedRole",
    "principalId": "AROACKCEVSQ6C2EXAMPLE:[email protected]-TempAccessRoleS3Admin",
    "arn": "arn:aws:sts::111122223333:assumed-role/TempAccessRoleS3Admin/[email protected]-TempAccessRoleS3Admin",
    "accountId": "111122223333",
    "sessionContext": {
        "sessionIssuer": {
            "type": "Role",
            "principalId": "AROACKCEVSQ6C2EXAMPLE",
            "arn": "arn:aws:iam::111122223333:role/TempAccessRoleS3Admin",
            "accountId": "111122223333",
            "userName": "TempAccessRoleS3Admin"
        },
        "webIdFederationData": {},
        "attributes": {
            "mfaAuthenticated": "true",
            "creationDate": "2021-07-02T13:24:06Z"
        }
    }
}

Security considerations

The temporary elevated access broker controls access to your AWS environment, and must be treated with extreme care in order to prevent unauthorized access. It is also an inline dependency for accessing your AWS environment and must operate with sufficient resiliency.

The broker should be deployed in a dedicated AWS account with a minimum of dependencies on the AWS target environment for which you’ll manage access. It should use its own access control configuration following the principle of least privilege. Ideally the broker should be managed by a specialized team and use its own deployment pipeline, with a two-person rule for making changes—for example by requiring different users to check in code and approve deployments. Special care should be taken to protect the integrity of the broker’s code and configuration and the confidentiality of the temporary credentials it handles.

See the reference implementation README for further security considerations.

Extending the solution

You can extend the reference implementation to fit the requirements of your organization. Here are some ways you can extend the solution:

  • Customize the UI, for example to use your organization’s branding.
  • Keep network traffic within your private network, for example to comply with network security policies.
  • Change the process for initiating and evaluating temporary elevated access, for example to integrate with a change or incident management system.
  • Change the authorization model, for example to use groups with different scope, granularity, or meaning.
  • Use SAML 2.0, for example if your identity provider does not support OpenID Connect.

See the reference implementation README for further details on extending the solution.

Conclusion

In this blog post you learned about temporary elevated access and how it can help reduce risk relating to human user access. You learned that you should aim to eliminate the need to use high-risk human access through the use of automation, and only use temporary elevated access for infrequent activities that cannot yet be automated. Finally, you studied a minimal reference implementation for temporary elevated access which you can download and customize to fit your organization’s needs.

If you have feedback about this post, submit comments in the Comments section below. If you have questions about this post, start a new thread on the AWS IAM forum or contact AWS Support.

Want more AWS Security how-to content, news, and feature announcements? Follow us on Twitter.

Author

James Greenwood

James is a principal security solutions architect who helps helps AWS Financial Services customers meet their security and compliance objectives in the AWS cloud. James has a background in identity and access management, authentication, credential management, and data protection with more than 20 years experience in the financial services industry.

Author

Bikash Behera

Bikash is a principal solutions architect who provides transformation guidance to AWS Financial Services customers and develops solutions for high priority customer objectives. Bikash has been delivering transformation guidance and technology solutions to the financial services industry for the last 25 years.

Author

Kevin Higgins

Kevin is a principal cloud architect with AWS Professional Services. He helps customers with the architecture, design, and development of cloud-optimized infrastructure solutions. As a member of the Microsoft Global Specialty Practice, he collaborates with AWS field sales, training, support, and consultants to help drive AWS product feature roadmap and go-to-market strategies.

Heads-Up: AWS Support for Internet Explorer 11 is Ending

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/heads-up-aws-support-for-internet-explorer-11-is-ending/

If you are using Internet Explorer 11 (IE 11) to access the AWS Management Console, web-based services such as Amazon Chime or Amazon Honeycode, or other parts of the AWS web site (AWS Documentation, AWS Marketing, AWS Marketplace, or AWS Support), it is time to upgrade to a more modern & secure browser such as Edge, Firefox, or Chrome.

Here are the dates that you need to know:

July 31, 2021 – Effective today, we will no longer ensure that new AWS Management Console features and web pages function properly on IE 11. We will fix bugs that are specific to IE 11 for existing features and pages.

Late 2021 – Later this year you will receive a pop-up notification (and a reminder to upgrade your browser) if you use IE 11 to access any of the services or pages listed above.

July 31, 2022 – One year from today we will discontinue our support for IE 11 and you will need to use a browser that we support.

Jeff;