Tag Archives: IAM users

Newly Updated: Example AWS IAM Policies for You to Use and Customize

Post Syndicated from Deren Smith original https://aws.amazon.com/blogs/security/newly-updated-example-policies-for-you-to-use-and-customize/

To help you grant access to specific resources and conditions, the Example Policies page in the AWS Identity and Access Management (IAM) documentation now includes more than thirty policies for you to use or customize to meet your permissions requirements. The AWS Support team developed these policies from their experiences working with AWS customers over the years. The example policies cover common permissions use cases you might encounter across services such as Amazon DynamoDB, Amazon EC2, AWS Elastic Beanstalk, Amazon RDS, Amazon S3, and IAM.

In this blog post, I introduce the updated Example Policies page and explain how to use and customize these policies for your needs.

The new Example Policies page

The Example Policies page in the IAM User Guide now provides an overview of the example policies and includes a link to view each policy on a separate page. Note that each of these policies has been reviewed and approved by AWS Support. If you would like to submit a policy that you have found to be particularly useful, post it on the IAM forum.

To give you an idea of the policies we have included on this page, the following are a few of the EC2 policies on the page:

To see the full list of available policies, see the Example Polices page.

In the following section, I demonstrate how to use a policy from the Example Policies page and customize it for your needs.

How to customize an example policy for your needs

Suppose you want to allow an IAM user, Bob, to start and stop EC2 instances with a specific resource tag. After looking through the Example Policies page, you see the policy, Allows Starting or Stopping EC2 Instances a User Has Tagged, Programmatically and in the Console.

To apply this policy to your specific use case:

  1. Navigate to the Policies section of the IAM console.
  2. Choose Create policy.
    Screenshot of choosing "Create policy"
  3. Choose the Select button next to Create Your Own Policy. You will see an empty policy document with boxes for Policy Name, Description, and Policy Document, as shown in the following screenshot.
  4. Type a name for the policy, copy the policy from the Example Policies page, and paste the policy in the Policy Document box. In this example, I use “start-stop-instances-for-owner-tag” as the policy name and “Allows users to start or stop instances if the instance tag Owner has the value of their user name” as the description.
  5. Update the placeholder text in the policy (see the full policy that follows this step). For example, replace <REGION> with a region from AWS Regions and Endpoints and <ACCOUNTNUMBER> with your 12-digit account number. The IAM policy variable, ${aws:username}, is a dynamic property in the policy that automatically applies to the user to which it is attached. For example, when the policy is attached to Bob, the policy replaces ${aws:username} with Bob. If you do not want to use the key value pair of Owner and ${aws:username}, you can edit the policy to include your desired key value pair. For example, if you want to use the key value pair, CostCenter:1234, you can modify “ec2:ResourceTag/Owner”: “${aws:username}” to “ec2:ResourceTag/CostCenter”: “1234”.
        "Version": "2012-10-17",
        "Statement": [
          "Effect": "Allow",
          "Action": [
                 "Resource": "arn:aws:ec2:<REGION>:<ACCOUNTNUMBER>:instance/*",
                 "Condition": {
              "StringEquals": {
                  "ec2:ResourceTag/Owner": "${aws:username}"
                 "Effect": "Allow",
                 "Action": "ec2:DescribeInstances",
                 "Resource": "*"

  6. After you have edited the policy, choose Create policy.

You have created a policy that allows an IAM user to stop and start EC2 instances in your account, as long as these instances have the correct resource tag and the policy is attached to your IAM users. You also can attach this policy to an IAM group and apply the policy to users by adding them to that group.


We updated the Example Policies page in the IAM User Guide so that you have a central location where you can find examples of the most commonly requested and used IAM policies. In addition to these example policies, we recommend that you review the list of AWS managed policies, including the AWS managed policies for job functions. You can choose these predefined policies from the IAM console and associate them with your IAM users, groups, and roles.

We will add more IAM policies to the Example Policies page over time. If you have a useful policy you would like to share with others, post it on the IAM forum. If you have comments about this post, submit them in the “Comments” section below.

– Deren

Use CloudFormation StackSets to Provision Resources Across Multiple AWS Accounts and Regions

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/use-cloudformation-stacksets-to-provision-resources-across-multiple-aws-accounts-and-regions/

AWS CloudFormation helps AWS customers implement an Infrastructure as Code model. Instead of setting up their environments and applications by hand, they build a template and use it to create all of the necessary resources, collectively known as a CloudFormation stack. This model removes opportunities for manual error, increases efficiency, and ensures consistent configurations over time.

Today I would like to tell you about a new feature that makes CloudFormation even more useful. This feature is designed to help you to address the challenges that you face when you use Infrastructure as Code in situations that include multiple AWS accounts and/or AWS Regions. As a quick review:

Accounts – As I have told you in the past, many organizations use a multitude of AWS accounts, often using AWS Organizations to arrange the accounts into a hierarchy and to group them into Organizational Units, or OUs (read AWS Organizations – Policy-Based Management for Multiple AWS Accounts to learn more). Our customers use multiple accounts for business units, applications, and developers. They often create separate accounts for development, testing, staging, and production on a per-application basis.

Regions – Customers also make great use of the large (and ever-growing) set of AWS Regions. They build global applications that span two or more regions, implement sophisticated multi-region disaster recovery models, replicate S3, Aurora, PostgreSQL, and MySQL data in real time, and choose locations for storage and processing of sensitive data in accord with national and regional regulations.

This expansion into multiple accounts and regions comes with some new challenges with respect to governance and consistency. Our customers tell us that they want to make sure that each new account is set up in accord with their internal standards. Among other things, they want to set up IAM users and roles, VPCs and VPC subnets, security groups, Config Rules, logging, and AWS Lambda functions in a consistent and reliable way.

Introducing StackSet
In order to address these important customer needs, we are launching CloudFormation StackSet today. You can now define an AWS resource configuration in a CloudFormation template and then roll it out across multiple AWS accounts and/or Regions with a couple of clicks. You can use this to set up a baseline level of AWS functionality that addresses the cross-account and cross-region scenarios that I listed above. Once you have set this up, you can easily expand coverage to additional accounts and regions.

This feature always works on a cross-account basis. The master account owns one or more StackSets and controls deployment to one or more target accounts. The master account must include an assumable IAM role and the target accounts must delegate trust to this role. To learn how to do this, read Prerequisites in the StackSet Documentation.

Each StackSet references a CloudFormation template and contains lists of accounts and regions. All operations apply to the cross-product of the accounts and regions in the StackSet. If the StackSet references three accounts (A1, A2, and A3) and four regions (R1, R2, R3, and R4), there are twelve targets:

  • Region R1: Accounts A1, A2, and A3.
  • Region R2: Accounts A1, A2, and A3.
  • Region R3: Accounts A1, A2, and A3.
  • Region R4: Accounts A1, A2, and A3.

Deploying a template initiates creation of a CloudFormation stack in an account/region pair. Templates are deployed sequentially to regions (you control the order) to multiple accounts within the region (you control the amount of parallelism). You can also set an error threshold that will terminate deployments if stack creation fails.

You can use your existing CloudFormation templates (taking care to make sure that they are ready to work across accounts and regions), create new ones, or use one of our sample templates. We are launching with support for the AWS partition (all public regions except those in China), and expect to expand it to to the others before too long.

Using StackSets
You can create and deploy StackSets from the CloudFormation Console, via the CloudFormation APIs, or from the command line.

Using the Console, I start by clicking on Create StackSet. I can use my own template or one of the samples. I’ll use the last sample (Add config rule encrypted volumes):

I click on View template to learn more about the template and the rule:

I give my StackSet a name. The template that I selected accepts an optional parameter, and I can enter it at this time:

Next, I choose the accounts and regions. I can enter account numbers directly, reference an AWS organizational unit, or upload a list of account numbers:

I can set up the regions and control the deployment order:

I can also set the deployment options. Once I am done I click on Next to proceed:

I can add tags to my StackSet. They will be applied to the AWS resources created during the deployment:

The deployment begins, and I can track the status from the Console:

I can open up the Stacks section to see each stack. Initially, the status of each stack is OUTDATED, indicating that the template has yet to be deployed to the stack; this will change to CURRENT after a successful deployment. If a stack cannot be deleted, the status will change to INOPERABLE.

After my initial deployment, I can click on Manage StackSet to add additional accounts, regions, or both, to create additional stacks:

Now Available
This new feature is available now and you can start using it today at no extra charge (you pay only for the AWS resources created on your behalf).


PS – If you create some useful templates and would like to share them with other AWS users, please send a pull request to our AWS Labs GitHub repo.

Manage Kubernetes Clusters on AWS Using Kops

Post Syndicated from Arun Gupta original https://aws.amazon.com/blogs/compute/kubernetes-clusters-aws-kops/

Any containerized application typically consists of multiple containers. There is a container for the application itself, one for database, possibly another for web server, and so on. During development, its normal to build and test this multi-container application on a single host. This approach works fine during early dev and test cycles but becomes a single point of failure for production where the availability of the application is critical. In such cases, this multi-container application is deployed on multiple hosts. There is a need for an external tool to manage such a multi-container multi-host deployment. Container orchestration frameworks provides the capability of cluster management, scheduling containers on different hosts, service discovery and load balancing, crash recovery and other related functionalities. There are multiple options for container orchestration on Amazon Web Services: Amazon ECS, Docker for AWS, and DC/OS.

Another popular option for container orchestration on AWS is Kubernetes. There are multiple ways to run a Kubernetes cluster on AWS. This multi-part blog series provides a brief overview and explains some of these approaches in detail. This first post explains how to create a Kubernetes cluster on AWS using kops.

Kubernetes and Kops overview

Kubernetes is an open source, container orchestration platform. Applications packaged as Docker images can be easily deployed, scaled, and managed in a Kubernetes cluster. Some of the key features of Kubernetes are:

  • Self-healing
    Failed containers are restarted to ensure that the desired state of the application is maintained. If a node in the cluster dies, then the containers are rescheduled on a different node. Containers that do not respond to application-defined health check are terminated, and thus rescheduled.
  • Horizontal scaling
    Number of containers can be easily scaled up and down automatically based upon CPU utilization, or manually using a command.
  • Service discovery and load balancing
    Multiple containers can be grouped together discoverable using a DNS name. The service can be load balanced with integration to the native LB provided by the cloud provider.
  • Application upgrades and rollbacks
    Applications can be upgraded to a newer version without an impact to the existing one. If something goes wrong, Kubernetes rolls back the change.

Kops, short for Kubernetes Operations, is a set of tools for installing, operating, and deleting Kubernetes clusters in the cloud. A rolling upgrade of an older version of Kubernetes to a new version can also be performed. It also manages the cluster add-ons. After the cluster is created, the usual kubectl CLI can be used to manage resources in the cluster.

Download Kops and Kubectl

There is no need to download the Kubernetes binary distribution for creating a cluster using kops. However, you do need to download the kops CLI. It then takes care of downloading the right Kubernetes binary in the cloud, and provisions the cluster.

The different download options for kops are explained at github.com/kubernetes/kops#installing. On MacOS, the easiest way to install kops is using the brew package manager.

brew update && brew install kops

The version of kops can be verified using the kops version command, which shows:

Version 1.6.1

In addition, download kubectl. This is required to manage the Kubernetes cluster. The latest version of kubectl can be downloaded using the following command:

curl -LO https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/darwin/amd64/kubectl

Make sure to include the directory where kubectl is downloaded in your PATH.

IAM user permission

The IAM user to create the Kubernetes cluster must have the following permissions:

  • AmazonEC2FullAccess
  • AmazonRoute53FullAccess
  • AmazonS3FullAccess
  • IAMFullAccess
  • AmazonVPCFullAccess

Alternatively, a new IAM user may be created and the policies attached as explained at github.com/kubernetes/kops/blob/master/docs/aws.md#setup-iam-user.

Create an Amazon S3 bucket for the Kubernetes state store

Kops needs a “state store” to store configuration information of the cluster.  For example, how many nodes, instance type of each node, and Kubernetes version. The state is stored during the initial cluster creation. Any subsequent changes to the cluster are also persisted to this store as well. As of publication, Amazon S3 is the only supported storage mechanism. Create a S3 bucket and pass that to the kops CLI during cluster creation.

This post uses the bucket name kubernetes-aws-io. Bucket names must be unique; you have to use a different name. Create an S3 bucket:

aws s3api create-bucket --bucket kubernetes-aws-io

I strongly recommend versioning this bucket in case you ever need to revert or recover a previous version of the cluster. This can be enabled using the AWS CLI as well:

aws s3api put-bucket-versioning --bucket kubernetes-aws-io --versioning-configuration Status=Enabled

For convenience, you can also define KOPS_STATE_STORE environment variable pointing to the S3 bucket. For example:

export KOPS_STATE_STORE=s3://kubernetes-aws-io

This environment variable is then used by the kops CLI.

DNS configuration

As of Kops 1.6.1, a top-level domain or a subdomain is required to create the cluster. This domain allows the worker nodes to discover the master and the master to discover all the etcd servers. This is also needed for kubectl to be able to talk directly with the master.

This domain may be registered with AWS, in which case a Route 53 hosted zone is created for you. Alternatively, this domain may be at a different registrar. In this case, create a Route 53 hosted zone. Specify the name server (NS) records from the created zone as NS records with the domain registrar.

This post uses a kubernetes-aws.io domain registered at a third-party registrar.

Generate a Route 53 hosted zone using the AWS CLI. Download jq to run this command:

ID=$(uuidgen) && \
aws route53 create-hosted-zone \
--name cluster.kubernetes-aws.io \
--caller-reference $ID \
| jq .DelegationSet.NameServers

This shows an output such as the following:


Create NS records for the domain with your registrar. Different options on how to configure DNS for the cluster are explained at github.com/kubernetes/kops/blob/master/docs/aws.md#configure-dns.

Experimental support to create a gossip-based cluster was added in Kops 1.6.2. This post uses a DNS-based approach, as that is more mature and well tested.

Create the Kubernetes cluster

The Kops CLI can be used to create a highly available cluster, with multiple master nodes spread across multiple Availability Zones. Workers can be spread across multiple zones as well. Some of the tasks that happen behind the scene during cluster creation are:

  • Provisioning EC2 instances
  • Setting up AWS resources such as networks, Auto Scaling groups, IAM users, and security groups
  • Installing Kubernetes.

Start the Kubernetes cluster using the following command:

kops create cluster \
--name cluster.kubernetes-aws.io \
--zones us-west-2a \
--state s3://kubernetes-aws-io \

In this command:

  • --zones
    Defines the zones in which the cluster is going to be created. Multiple comma-separated zones can be specified to span the cluster across multiple zones.
  • --name
    Defines the cluster’s name.
  • --state
    Points to the S3 bucket that is the state store.
  • --yes
    Immediately creates the cluster. Otherwise, only the cloud resources are created and the cluster needs to be started explicitly using the command kops update --yes. If the cluster needs to be edited, then the kops edit cluster command can be used.

This starts a single master and two worker node Kubernetes cluster. The master is in an Auto Scaling group and the worker nodes are in a separate group. By default, the master node is m3.medium and the worker node is t2.medium. Master and worker nodes are assigned separate IAM roles as well.

Wait for a few minutes for the cluster to be created. The cluster can be verified using the command kops validate cluster --state=s3://kubernetes-aws-io. It shows the following output:

Using cluster from kubectl context: cluster.kubernetes-aws.io

Validating cluster cluster.kubernetes-aws.io

NAME                 ROLE      MACHINETYPE    MIN    MAX    SUBNETS
master-us-west-2a    Master    m3.medium      1      1      us-west-2a
nodes                Node      t2.medium      2      2      us-west-2a

NAME                                           ROLE      READY
ip-172-20-38-133.us-west-2.compute.internal    node      True
ip-172-20-38-177.us-west-2.compute.internal    master    True
ip-172-20-46-33.us-west-2.compute.internal     node      True

Your cluster cluster.kubernetes-aws.io is ready

It shows the different instances started for the cluster, and their roles. If multiple cluster states are stored in the same bucket, then --name <NAME> can be used to specify the exact cluster name.

Check all nodes in the cluster using the command kubectl get nodes:

NAME                                          STATUS         AGE       VERSION
ip-172-20-38-133.us-west-2.compute.internal   Ready,node     14m       v1.6.2
ip-172-20-38-177.us-west-2.compute.internal   Ready,master   15m       v1.6.2
ip-172-20-46-33.us-west-2.compute.internal    Ready,node     14m       v1.6.2

Again, the internal IP address of each node, their current status (master or node), and uptime are shown. The key information here is the Kubernetes version for each node in the cluster, 1.6.2 in this case.

The kubectl value included in the PATH earlier is configured to manage this cluster. Resources such as pods, replica sets, and services can now be created in the usual way.

Some of the common options that can be used to override the default cluster creation are:

  • --kubernetes-version
    The version of Kubernetes cluster. The exact versions supported are defined at github.com/kubernetes/kops/blob/master/channels/stable.
  • --master-size and --node-size
    Define the instance of master and worker nodes.
  • --master-count and --node-count
    Define the number of master and worker nodes. By default, a master is created in each zone specified by --master-zones. Multiple master nodes can be created by a higher number using --master-count or specifying multiple Availability Zones in --master-zones.

A three-master and five-worker node cluster, with master nodes spread across different Availability Zones, can be created using the following command:

kops create cluster \
--name cluster2.kubernetes-aws.io \
--zones us-west-2a,us-west-2b,us-west-2c \
--node-count 5 \
--state s3://kubernetes-aws-io \

Both the clusters are sharing the same state store but have different names. This also requires you to create an additional Amazon Route 53 hosted zone for the name.

By default, the resources required for the cluster are directly created in the cloud. The --target option can be used to generate the AWS CloudFormation scripts instead. These scripts can then be used by the AWS CLI to create resources at your convenience.

Get a complete list of options for cluster creation with kops create cluster --help.

More details about the cluster can be seen using the command kubectl cluster-info:

Kubernetes master is running at https://api.cluster.kubernetes-aws.io
KubeDNS is running at https://api.cluster.kubernetes-aws.io/api/v1/proxy/namespaces/kube-system/services/kube-dns

To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.

Check the client and server version using the command kubectl version:

Client Version: version.Info{Major:"1", Minor:"6", GitVersion:"v1.6.4", GitCommit:"d6f433224538d4f9ca2f7ae19b252e6fcb66a3ae", GitTreeState:"clean", BuildDate:"2017-05-19T18:44:27Z", GoVersion:"go1.7.5", Compiler:"gc", Platform:"darwin/amd64"}
Server Version: version.Info{Major:"1", Minor:"6", GitVersion:"v1.6.2", GitCommit:"477efc3cbe6a7effca06bd1452fa356e2201e1ee", GitTreeState:"clean", BuildDate:"2017-04-19T20:22:08Z", GoVersion:"go1.7.5", Compiler:"gc", Platform:"linux/amd64"}

Both client and server version are 1.6 as shown by the Major and Minor attribute values.

Upgrade the Kubernetes cluster

Kops can be used to create a Kubernetes 1.4.x, 1.5.x, or an older version of the 1.6.x cluster using the --kubernetes-version option. The exact versions supported are defined at github.com/kubernetes/kops/blob/master/channels/stable.

Or, you may have used kops to create a cluster a while ago, and now want to upgrade to the latest recommended version of Kubernetes. Kops supports rolling cluster upgrades where the master and worker nodes are upgraded one by one.

As of kops 1.6.1, upgrading a cluster is a three-step process.

First, check and apply the latest recommended Kubernetes update.

kops upgrade cluster \
--name cluster2.kubernetes-aws.io \
--state s3://kubernetes-aws-io \

The --yes option immediately applies the changes. Not specifying the --yes option shows only the changes that are applied.

Second, update the state store to match the cluster state. This can be done using the following command:

kops update cluster \
--name cluster2.kubernetes-aws.io \
--state s3://kubernetes-aws-io \

Lastly, perform a rolling update for all cluster nodes using the kops rolling-update command:

kops rolling-update cluster \
--name cluster2.kubernetes-aws.io \
--state s3://kubernetes-aws-io \

Previewing the changes before updating the cluster can be done using the same command but without specifying the --yes option. This shows the following output:

NAME                 STATUS        NEEDUPDATE    READY    MIN    MAX    NODES
master-us-west-2a    NeedsUpdate   1             0        1      1      1
nodes                NeedsUpdate   2             0        2      2      2

Using --yes updates all nodes in the cluster, first master and then worker. There is a 5-minute delay between restarting master nodes, and a 2-minute delay between restarting nodes. These values can be altered using --master-interval and --node-interval options, respectively.

Only the worker nodes may be updated by using the --instance-group node option.

Delete the Kubernetes cluster

Typically, the Kubernetes cluster is a long-running cluster to serve your applications. After its purpose is served, you may delete it. It is important to delete the cluster using the kops command. This ensures that all resources created by the cluster are appropriately cleaned up.

The command to delete the Kubernetes cluster is:

kops delete cluster --state=s3://kubernetes-aws-io --yes

If multiple clusters have been created, then specify the cluster name as in the following command:

kops delete cluster cluster2.kubernetes-aws.io --state=s3://kubernetes-aws-io --yes


This post explained how to manage a Kubernetes cluster on AWS using kops. Kubernetes on AWS users provides a self-published list of companies using Kubernetes on AWS.

Try starting a cluster, create a few Kubernetes resources, and then tear it down. Kops on AWS provides a more comprehensive tutorial for setting up Kubernetes clusters. Kops docs are also helpful for understanding the details.

In addition, the Kops team hosts office hours to help you get started, from guiding you with your first pull request. You can always join the #kops channel on Kubernetes slack to ask questions. If nothing works, then file an issue at github.com/kubernetes/kops/issues.

Future posts in this series will explain other ways of creating and running a Kubernetes cluster on AWS.

— Arun

New Information in the AWS IAM Console Helps You Follow IAM Best Practices

Post Syndicated from Rob Moncur original https://aws.amazon.com/blogs/security/newly-updated-features-in-the-aws-iam-console-help-you-adhere-to-iam-best-practices/

Today, we added new information to the Users section of the AWS Identity and Access Management (IAM) console to make it easier for you to follow IAM best practices. With this new information, you can more easily monitor users’ activity in your AWS account and identify access keys and passwords that you should rotate regularly. You can also better audit users’ MFA device usage and keep track of their group memberships. In this post, I show how you can use this new information to help you follow IAM best practices.

Monitor activity in your AWS account

The IAM best practice, monitor activity in your AWS account, encourages you to monitor user activity in your AWS account by using services such as AWS CloudTrail and AWS Config. In addition to monitoring usage in your AWS account, you should be aware of inactive users so that you can remove them from your account. By only retaining necessary users, you can help maintain the security of your AWS account.

To help you find users that are inactive, we added three new columns to the IAM user table: Last activity, Console last sign-in, and Access key last used.
Screenshot showing three new columns in the IAM user table

  1. Last activity – This column tells you how long it has been since the user has either signed in to the AWS Management Console or accessed AWS programmatically with their access keys. Use this column to find users who might be inactive, and consider removing them from your AWS account.
  2. Console last sign-in – This column displays the time since the user’s most recent console sign-in. Consider removing passwords from users who are not signing in to the console.
  3. Access key last used – This column displays the time since a user last used access keys. Use this column to find any access keys that are not being used, and deactivate or remove them.

Rotate credentials regularly

The IAM best practice, rotate credentials regularly, recommends that all users in your AWS account change passwords and access keys regularly. With this practice, if a password or access key is compromised without your knowledge, you can limit how long the credentials can be used to access your resources. To help your management efforts, we added three new columns to the IAM user table: Access key age, Password age, and Access key ID.

Screenshot showing three new columns in the IAM user table

  1. Access key age – This column shows how many days it has been since the oldest active access key was created for a user. With this information, you can audit access keys easily across all your users and identify the access keys that may need to be rotated.

Based on the number of days since the access key has been rotated, a green, yellow, or red icon is displayed. To see the corresponding time frame for each icon, pause your mouse pointer on the Access key age column heading to see the tooltip, as shown in the following screenshot.

Icons showing days since the oldest active access key was created

  1. Password age – This column shows the number of days since a user last changed their password. With this information, you can audit password rotation and identify users who have not changed their password recently. The easiest way to make sure that your users are rotating their password often is to establish an account password policy that requires users to change their password after a specified time period.
  2. Access key ID – This column displays the access key IDs for users and the current status (Active/Inactive) of those access key IDs. This column makes it easier for you to locate and see the state of access keys for each user, which is useful for auditing. To find a specific access key ID, use the search box above the table.

Enable MFA for privileged users

Another IAM best practice is to enable multi-factor authentication (MFA) for privileged IAM users. With MFA, users have a device that generates a unique authentication code (a one-time password [OTP]). Users must provide both their normal credentials (such as their user name and password) and the OTP when signing in.

To help you see if MFA has been enabled for your users, we’ve improved the MFA column to show you if MFA is enabled and which type of MFA (hardware, virtual, or SMS) is enabled for each user, where applicable.

Screenshot showing the improved "MFA" column

Use groups to assign permissions to IAM users

Instead of defining permissions for individual IAM users, it’s usually more convenient to create groups that relate to job functions (such as administrators, developers, and accountants), define the relevant permissions for each group, and then assign IAM users to those groups. All the users in an IAM group inherit the permissions assigned to the group. This way, if you need to modify permissions, you can make the change once for everyone in a group instead of making the change one time for each user. As people move around in your company, you can change the group membership of the IAM user.

To better understand which groups your users belong to, we’ve made updates:

  1. Groups – This column now lists the groups of which a user is a member. This information makes it easier to understand and compare multiple users’ permissions at once.
  2. Group count – This column shows the number of groups to which each user belongs.Screenshot showing the updated "Groups" and "Group count" columns

Customize your view

Choosing which columns you see in the User table is easy to do. When you click the button with the gear icon in the upper right corner of the table, you can choose the columns you want to see, as shown in the following screenshots.

Screenshot showing gear icon  Screenshot of "Manage columns" dialog box


We made these improvements to the Users section of the IAM console to make it easier for you to follow IAM best practices in your AWS account. Following these best practices can help you improve the security of your AWS resources and make your account easier to manage.

If you have comments about this post, submit them in the “Comments” section below. If you have questions or suggestions, please start a new thread on the IAM forum.

– Rob

Validating AWS CloudFormation Templates

Post Syndicated from Remek Hetman original https://aws.amazon.com/blogs/devops/validating-aws-cloudformation-templates/

For their continuous integration and continuous deployment (CI/CD) pipeline path, many companies use tools like Jenkins, Chef, and AWS CloudFormation. Usually, the process is managed by two or more teams. One team is responsible for designing and developing an application, CloudFormation templates, and so on. The other team is generally responsible for integration and deployment.

One of the challenges that a CI/CD team has is to validate the CloudFormation templates provided by the development team. Validation provides early warning about any incorrect syntax and ensures that the development team follows company policies in terms of security and the resources created by CloudFormation templates.

In this post, I focus on the validation of AWS CloudFormation templates for syntax as well as in the context of business rules.

Scripted validation solution

For CloudFormation syntax validation, one option is to use the AWS CLI to call the validate-template command. For security and resource management, another approach is to run a Jenkins pipeline from an Amazon EC2 instance under an EC2 role that has been granted only the necessary permissions.

What if you need more control over your CloudFormation templates, such as managing parameters or attributes? What if you have many development teams where permissions to the AWS environment required by one team are either too open or not open enough for another team?

To have more control over the contents of your CloudFormation template, you can use the cf-validator Python script, which shows you how to validate different template aspects. With this script, you can validate:

  • JSON syntax
  • IAM capabilities
  • Root tags
  • Parameters
  • CloudFormation resources
  • Attributes
  • Reference resources

You can download this script from the cf-validator GitHub repo. Use the following command to run the script:

python cf-validator.py

The script takes the following parameters:

  • –cf_path [Required]

    The location of the CloudFormation template in JSON format. Supported location types:

    • File system – Path to the CloudFormation template on the file system
    • Web – URL, for example, https://my-file.com/my_cf.json
    • Amazon S3 – Amazon S3 bucket, for example, s3://my_bucket/my_cf.json
  • –cf_rules [Required]

    The location of the JSON file with the validation rules. This parameter supports the same locations as –cf_path. The next section of this post has more information about defining rules.

  • –cf_res [Optional]

    The location of the JSON file with the defined AWS resources, which need to be confirmed before launching the CloudFormation template. A later section of this post has more information about resource validation.

  • –allow_cap [Optional][yes/no]

    Controls whether you allow the creation of IAM resources by the CloudFormation template, such as policies, rules, or IAM users. The default value is no.

  • –region [Optional]

    The AWS region where the existing resources were created. The default value is us-east-1.

Defining rules

All rules are defined in the JSON format file. Rules consist of the following keys:

  • “allow_root_keys”

    Lists allowed root CloudFormation keys. Example of root keys are Parameters, Resources, Output, and so on. An empty list means that any key is allowed.

  • “allow_parameters”

    Lists allowed CloudFormation parameters. For instance, to force each CloudFormation template to use only the set of parameters defined in your pipeline, list them under this key. An empty list means that any parameter is allowed.

  • “allow_resources”

    Lists the AWS resources allowed for creation by a CloudFormation template. The format of the resource is the same as resource types in CloudFormation, but without the “AWS::” prefix. Examples:  EC2::Instance, EC2::Volume, and so on. If you allow the creation of all resources from the given group, you can use a wildcard. For instance, if you allow all resources related to CloudFormation, you can add CloudFormation::* to the list instead of typing CloudFormation::Init, CloudFormation:Stack, and so on. An empty list means that all resources are allowed.

  • “require_ref_attributes”

    Lists attributes (per resource) that have to be defined in CloudFormation. The value must be referenced and cannot be hardcoded. For instance, you can require that each EC2 instance must be created from a specific AMI where Image ID has to be a passed-in parameter. An empty list means that you are not requiring specific attributes to be present for a given resource.

  • “allow_additional_attributes”

    Lists additional attributes (per resource) that can be defined and have any value in the CloudFormation template. An empty list means that any additional attribute is allowed. If you specify additional attributes for this key, then any resource attribute defined in a CloudFormation template that is not listed in this key or in the require_ref_attributes key causes validation to fail.

  • “not_allow_attributes”

    Lists attributes (per resource) that are not allowed in the CloudFormation template. This key takes precedence over the require_ref_attributes and allow_additional_attributes keys.

Rule file example

The following is an example of a rule file:

  "allow_root_keys" : ["AWSTemplateFormatVersion", "Description", "Parameters", "Conditions", "Resources", "Outputs"],
  "allow_parameters" : [],
  "allow_resources" : [
  "require_ref_attributes" :
      "EC2::Instance" : [ "InstanceType", "ImageId", "SecurityGroupIds", "SubnetId", "KeyName", "IamInstanceProfile" ],
      "ElasticLoadBalancing::LoadBalancer" : ["SecurityGroups", "Subnets"]
  "allow_additional_attributes" : {},
  "not_allow_attributes" : {}

Validating resources

You can use the –cf_res parameter to validate that the resources you are planning to reference in the CloudFormation template exist and are available. As a value for this parameter, point to the JSON file with defined resources. The format should be as follows:

  { "Type" : "SG",
    "ID" : "sg-37c9b448A"
  { "Type" : "AMI",
    "ID" : "ami-e7e523f1"
  { "Type" : "Subnet",
    "ID" : "subnet-034e262e"


At this moment, this CloudFormation template validation script supports only security groups, AMIs, and subnets. But anyone with some knowledge of Python and the boto3 package can add support for additional resources type, as needed.

For more tips please visit our AWS CloudFormation blog