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Education Unplugged: Google Ends Unlimited Storage for Schools

Post Syndicated from Barry Kaufman original https://www.backblaze.com/blog/education-unplugged-google-ends-unlimited-storage-for-schools/

For schools and universities, data storage is paramount. Staff, administrators, and educators, not to mention students, need a secure place to store files. Add to that the legacy accounts of alumni storing irreplaceable files from their education, and you have a massive need for storage.

For a long time, Google was happy to oblige. In 2006, the company launched Google Apps for Education (later G Suite for Education; now Google Workplace for Education), offering free unlimited storage for qualifying schools and districts. But when they’d reached market penetration—somewhere in the neighborhood of 83% of school districts according to EdWeek Research Center—they ended the unlimited storage policy many schools had come to rely on.

If you already know about Google’s policy change and are looking for a solution to save your data and your budget, getting started with Backblaze B2 is easy. Otherwise, read on to learn more about the change, what it may mean for you in the long-term, and a Backblaze partnership with Carahsoft that eases purchasing through local, state, and federal buying programs.

Office Hours Are Over—Google Ends Unlimited Storage for Educational Institutions

Google’s policy change took effect in July 2022, and many schools and universities had to find alternative storage solutions or change their internal storage policies to stay within the new limits. Under the terms of the new policy, Google offers a baseline of 100TB of pooled storage shared across all users.

The policy shift was spurred, Google says, because “as we’ve grown to serve more schools and universities each year, storage consumption has also rapidly accelerated. Storage is not being consumed equitably across—nor within—institutions, and school leaders often don’t have the tools they need to manage this.”

For some school districts, colleges, and universities, this policy shift meant having to reach out to alumni with the request that they back up all their own data. It also hit some already-strapped IT budgets particularly hard. Estimates vary, but depending on the size of the school and their data needs, they could be looking at anywhere up to an extra $70,000 a year in storage costs.

That’s a non-negligible fee for a service that has become increasingly vital for schools. We’ve written about how important cloud storage is for schools, but it’s worth reiterating here.

School is in Session

Not only will a secure cloud storage solution help protect school districts from threats of ransomware, it can also help maintain predictable operating expenses and create opportunities for collaboration through remote learning. In cases like Kansas’ Pittsburg State University, it helped keep data safe from natural disasters that abound in places like Tornado Alley. Pittsburg State implemented Backblaze B2 as their off-site backup in the event of disaster and used Object Lock functionality to safeguard data from ransomware.

Photo Credit: Pittsburg State University

The academic world is still adjusting to Google’s policy change. Stories have emerged of schools simply dropping Google and being forced to move data out of thousands of alumni accounts. A quick-fix solution to avoid Google’s new fee structure, this strategy is being undertaken without a clear answer to the question of how alumni can access their own data after the move. After all, how up to date are those alumni email lists?

A Google Alternative for Schools

School districts, colleges, and universities need to find a new, budget-friendly way forward. If you’re still struggling to find an alternative storage solution now that the bell has rung and Google has dismissed its free storage, Backblaze can help you find a new home on the cloud.

Backblaze B2 offers schools unlimited, pay-as-you-go storage at a fraction of the price of Google, enabling you to continue offering students and alumni the storage space they’ve come to expect. For colleges, universities, and school districts not buying through government purchasing programs, you can sign up for Backblaze B2 directly. We offer 10TB of storage free so that you can see if it works for you, but if you want to do a larger or customized proof of concept, reach out to our Sales team.

Accessing Backblaze Through Your Local, State, or Federal Buying Program

As we revealed during this year’s Educause conference, Backblaze has recently rolled out a partnership with Carahsoft aimed squarely at budget-conscious educational institutions. The partnership brings Backblaze services to educational institutions with a capacity-based pricing model that’s a fraction of the price of traditional cloud providers like Google. And it can be purchased through local, state, or federal buying programs. If you buy IT services for your district through a distributor, this solution could work for you. Visit the partnership announcement to learn more.

The post Education Unplugged: Google Ends Unlimited Storage for Schools appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

Better together: AWS SAM CLI and HashiCorp Terraform

Post Syndicated from Eric Johnson original https://aws.amazon.com/blogs/compute/better-together-aws-sam-cli-and-hashicorp-terraform/

This post is written by Suresh Poopandi, Senior Solutions Architect and Seb Kasprzak, Senior Solutions Architect.

Today, AWS is announcing the public preview of AWS Serverless Application Model CLI (AWS SAM CLI) support for local development, testing, and debugging of serverless applications defined using HashiCorp Terraform configuration.

AWS SAM and Terraform are open-source frameworks for building applications using infrastructure as code (IaC). Both frameworks allow building, changing, and managing cloud infrastructure in a repeatable way by defining resource configurations.

Previously, you could use the AWS SAM CLI to build, test, and debug applications defined by AWS SAM templates or through the AWS Cloud Development Kit (CDK). With this preview release, you can also use AWS SAM CLI to test and debug serverless applications defined using Terraform configurations.

Walkthrough of Terraform support

This blog post contains a sample Terraform template, which shows how developers can use AWS SAM CLI to build locally, test, and debug AWS Lambda functions defined in Terraform. This sample application has a Lambda function that stores a book review score and review text in an Amazon DynamoDB table. An Amazon API Gateway book review API uses Lambda proxy integration to invoke the book review Lambda function.

Demo application architecture

Demo application architecture

Prerequisites

Before running this example:

  • Install the AWS CLI.
    • Configure with valid AWS credentials.
    • Note that AWS CLI now requires Python runtime.
  • Install HashiCorp Terraform.
  • Install the AWS SAM CLI.
  • Install Docker (required to run AWS Lambda function locally).

Since Terraform support is currently in public preview, you must provide a –beta-features flag while executing AWS SAM commands. Alternatively, set this flag in samconfig.toml file by adding beta_features=”true”.

Deploying the example application

This Lambda function interacts with DynamoDB. For the example to work, it requires an existing DynamoDB table in an AWS account. Deploying this creates all the required resources for local testing and debugging of the Lambda function.

To deploy:

  1. Clone the aws-sam-terraform-examples repository locally: 
    git clone https://github.com/aws-samples/aws-sam-terraform-examples
  2. Change to the project directory: 
    cd aws-sam-terraform-examples/zip_based_lambda_functions/api-lambda-dynamodb-example/

    Terraform must store the state of the infrastructure and configuration it creates. Terraform uses this state to map cloud resources to configuration and track changes. This example uses a local backend to store the state file on the local filesystem.

  3. Open the main.tf file and review its contents. Locate the backend section of the code, updating the region field with the target deployment Region of this sample solution: 
    provider “aws” {
    region = “<AWS region>” # e.g. us-east-1
}
  4. Initialize a working directory containing Terraform configuration files: 
    terraform init
  5. Deploy the application using Terraform CLI. When prompted by “Do you want to perform these actions?”, enter Yes. 
    terraform apply

Terraform deploys the application, as shown in the terminal output.

Terminal output

Terminal output

After completing the deployment process, the AWS account is ready for use by the Lambda function with all the required resources.

Terraform Configuration for local testing

Lambda functions require application dependencies bundled together with function code as a deployment package (typically a .zip file) to run correctly. Terraform natively does not create the deployment package and a separate build process handles this package creation.

This sample application uses Terraform’s null_resource and local-exec provisioner to trigger a build process script. This installs Python dependencies in a temporary folder and creates a .zip file with dependencies and function code. It contains this logic within the main.tf file of the example application.

To explain each code segment in more detail:

Terraform example

Terraform example

  1. aws_lambda_function: This sample defines a Lambda function resource. It contains properties such as environment variables (in this example, the DynamoDB table_id) and the depends_on argument, which creates the .zip package before deploying the Lambda function.

    Terraform example

    Terraform example

  2. null_resource: When the AWS SAM CLI build command runs, AWS SAM reviews Terraform code for any null_resource starting with sam_metadata_ and uses the information contained within this resource block to gather the location of the Lambda function source code and .zip package. This information allows the AWS SAM CLI to start the local execution of the Lambda function. This special resource should contain the following attributes:
    • resource_name: The Lambda function address as defined in the current module (aws_lambda_function.publish_book_review)
    • resource_type: Packaging type of the Lambda function (ZIP_LAMBDA_FUNCTION)
    • original_source_code: Location of Lambda function code
    • built_output_path: Location of .zip deployment package

Local testing

With the backend services now deployed, run local tests to see if everything is working. The locally running sample Lambda function interacts with the services deployed in the AWS account. Run the sam build to reflect the local sam testing environment with changes after each code update.

  1. Local Build: To create a local build of the Lambda function for testing, use the sam build command: 
    sam build --hook-name terraform --beta-features
  2. Local invoke: The first test is to invoke the Lambda function with a mocked event payload from the API Gateway. These events are in the events directory. Run this command, passing in a mocked event: 
    AWS_DEFAULT_REGION=<Your Region Name>
sam local invoke aws_lambda_function.publish_book_review -e events/new-review.json --beta-features

    AWS SAM mounts the Lambda function runtime and code and runs it locally. The function makes a request to the DynamoDB table in the cloud to store the information provided via the API. It returns a 200 response code, signaling the successful completion of the function.

  3. Local invoke from AWS CLI
    Another test is to run a local emulation of the Lambda service using “sam local start-lambda” and invoke the function directly using AWS SDK or the AWS CLI. Start the local emulator with the following command: 

    sam local start-lambda
    Terminal output

    Terminal output

    AWS SAM starts the emulator and exposes a local endpoint for the AWS CLI or a software development kit (SDK) to call. With the start-lambda command still running, run the following command to invoke this function locally with the AWS CLI:

    aws lambda invoke --function-name aws_lambda_function.publish_book_review --endpoint-url http://127.0.0.1:3001/ response.json --cli-binary-format raw-in-base64-out --payload file://events/new-review.json

    The AWS CLI invokes the local function and returns a status report of the service to the screen. The response from the function itself is in the response.json file. The window shows the following messages:

    Invocation results

    Invocation results

  4. Debugging the Lambda function

Developers can use AWS SAM with a variety of AWS toolkits and debuggers to test and debug serverless applications locally. For example, developers can perform local step-through debugging of Lambda functions by setting breakpoints, inspecting variables, and running function code one line at a time.

The AWS Toolkit Integrated Development Environment (IDE) plugin provides the ability to perform many common debugging tasks, like setting breakpoints, inspecting variables, and running function code one line at a time. AWS Toolkits make it easier to develop, debug, and deploy serverless applications defined using AWS SAM. They provide an experience for building, testing, debugging, deploying, and invoking Lambda functions integrated into IDE. Refer to this link that lists common IDE/runtime combinations that support step-through debugging of AWS SAM applications.

Visual Studio Code keeps debugging configuration information in a launch.json file in a workspace .vscode folder. Here is a sample launch configuration file to debug Lambda code locally using AWS SAM and Visual Studio Code.

{
    "version": "0.2.0",
    "configurations": [
          {
            "name": "Attach to SAM CLI",
            "type": "python",
            "request": "attach",
            "address": "localhost",
            "port": 9999,
            "localRoot": "${workspaceRoot}/sam-terraform/book-reviews",
            "remoteRoot": "/var/task",
            "protocol": "inspector",
            "stopOnEntry": false
          }
    ]
}

After adding the launch configuration, start a debug session in the Visual Studio Code.

Step 1: Uncomment the following two lines in zip_based_lambda_functions/api-lambda-dynamodb-example/src/index.py

Enable debugging in the Lambda function

Enable debugging in the Lambda function

Step 2: Run the Lambda function in the debug mode and wait for the Visual Studio Code to attach to this debugging session:

sam local invoke aws_lambda_function.publish_book_review -e events/new-review.json -d 9999

Step 3: Select the Run and Debug icon in the Activity Bar on the side of VS Code. In the Run and Debug view, select “Attach to SAM CLI” and choose Run.

For this example, set a breakpoint at the first line of lambda_handler. This breakpoint allows viewing the input data coming into the Lambda function. Also, it helps in debugging code issues before deploying to the AWS Cloud.

Debugging in then IDE

Debugging in then IDE

Lambda Terraform module

A community-supported Terraform module for lambda (terraform-aws-lambda) has added support for SAM metadata null_resource. When using the latest version of this module, AWS SAM CLI will automatically support local invocation of the Lambda function, without additional resource blocks required.

Conclusion

This blog post shows how to use the AWS SAM CLI together with HashiCorp Terraform to develop and test serverless applications in a local environment. With AWS SAM CLI’s support for HashiCorp Terraform, developers can now use the AWS SAM CLI to test their serverless functions locally while choosing their preferred infrastructure as code tooling.

For more information about the features supported by AWS SAM, visit AWS SAM. For more information about the Metadata resource, visit HashiCorp Terraform.

Support for the Terraform configuration is currently in preview, and the team is asking for feedback and feature request submissions. The goal is for both communities to help improve the local development process using AWS SAM CLI. Submit your feedback by creating a GitHub issue here.

For more serverless learning resources, visit Serverless Land.

Another Event-Related Spyware App

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/another-event-related-spyware-app.html

Last month, we were warned not to install Qatar’s World Cup app because it was spyware. This month, it’s Egypt’s COP27 Summit app:

The app is being promoted as a tool to help attendees navigate the event. But it risks giving the Egyptian government permission to read users’ emails and messages. Even messages shared via encrypted services like WhatsApp are vulnerable, according to POLITICO’s technical review of the application, and two of the outside experts.

The app also provides Egypt’s Ministry of Communications and Information Technology, which created it, with other so-called backdoor privileges, or the ability to scan people’s devices.

On smartphones running Google’s Android software, it has permission to potentially listen into users’ conversations via the app, even when the device is in sleep mode, according to the three experts and POLITICO’s separate analysis. It can also track people’s locations via smartphone’s built-in GPS and Wi-Fi technologies, according to two of the analysts.

A Digital Red Cross

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/a-digital-red-cross.html

The International Committee of the Red Cross wants some digital equivalent to the iconic red cross, to alert would-be hackers that they are accessing a medical network.

The emblem wouldn’t provide technical cybersecurity protection to hospitals, Red Cross infrastructure or other medical providers, but it would signal to hackers that a cyberattack on those protected networks during an armed conflict would violate international humanitarian law, experts say, Tilman Rodenhäuser, a legal adviser to the International Committee of the Red Cross, said at a panel discussion hosted by the organization on Thursday.

I can think of all sorts of problems with this idea and many reasons why it won’t work, but those also apply to the physical red cross on buildings, vehicles, and people’s clothing. So let’s try it.

EDITED TO ADD: Original reference.

New Book: A Hacker’s Mind

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/new-book-a-hackers-mind.html

I have a new book coming out in February. It’s about hacking.

A Hacker’s Mind: How the Powerful Bend Society’s Rules, and How to Bend them Back isn’t about hacking computer systems; it’s about hacking more general economic, political, and social systems. It generalizes the term hack as a means of subverting a system’s rules in unintended ways.

What sorts of system? Any system of rules, really. Take the tax code, for example. It’s not computer code, but it’s a series of algorithms—supposedly deterministic—that take a bunch of inputs about your income and produce an output that’s the amount of money you owe. This code has vulnerabilities; we call them loopholes. It has exploits; those are tax avoidance strategies. And there is an entire industry of black-hat hackers who exploit vulnerabilities in the tax code: we call them accountants and tax attorneys.

In my conception, a “hack” is something a system permits, but is unanticipated and unwanted by its designers. It’s unplanned: a mistake in the system’s design or coding. It’s subversion, or an exploitation. It’s a cheat—but only sort of. Just as a computer vulnerability can be exploited over the Internet because the code permits it, a tax loophole is “allowed” by the system because it follows the rules, even though it might subvert the intent of those rules.

Once you start thinking of hacking in this way, you’ll start seeing hacks everywhere. You can find hacks in professional sports, in customer reward programs, in financial systems, in politics; in lots of economic, political, and social systems; against our cognitive functions. A curved hockey stick is a hack, and we know the name of the hacker who invented it. Airline frequent-flier mileage runs are a hack. The filibuster was originally a hack, invented by Cato the Younger, A Roman senator in 60 BCE. Hedge funds are full of hacks.

A system is just a set of rules. Or norms, since the “rules” aren’t always formal. And even the best-thought-out sets of rules will be incomplete or inconsistent. It’ll have ambiguities, and things the designers haven’t thought of. As long as there are people who want to subvert the goals of a system, there will be hacks.

I use this framework in A Hacker’s Mind to tease out a lot of why today’s economic, political, and social systems are failing us so badly, and apply what we have learned about hacking defenses in the computer world to those more general hacks. And I end by looking at artificial intelligence, and what will happen when AIs start hacking. Not the problems of hacking AI, which are both ubiquitous and super weird, but what happens when an AI is able to discover new hacks against these more general systems. What happens when AIs find tax loopholes, or loopholes in financial regulations. We have systems in place to deal with these sorts of hacks, but they were invented when hackers were human and reflect the human pace of hack discovery. They won’t be able to withstand an AI finding dozens, or hundreds, of loopholes in financial regulations. We’re simply not ready for the speed, scale, scope, and sophistication of AI hackers.

A Hacker’s Mind is my pandemic book, written in 2020 and 2021. It represents another step in my continuing journey of increasing generalizations. And I really like the cover. It will be published on February 7. It makes an excellent belated holiday gift. Order yours today and avoid the rush.

NSA Over-surveillance

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/nsa-over-surveillance.html

Here in 2022, we have a newly declassified 2016 Inspector General report—”Misuse of Sigint Systems”—about a 2013 NSA program that resulted in the unauthorized (that is, illegal) targeting of Americans.

Given all we learned from Edward Snowden, this feels like a minor coda. There’s nothing really interesting in the IG document, which is heavily redacted.

News story.

EDITED TO ADD (11/14): Non-paywalled copy of the Bloomberg link.

An Untrustworthy TLS Certificate in Browsers

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/an-untrustworthy-tls-certificate-in-browsers.html

The major browsers natively trust a whole bunch of certificate authorities, and some of them are really sketchy:

Google’s Chrome, Apple’s Safari, nonprofit Firefox and others allow the company, TrustCor Systems, to act as what’s known as a root certificate authority, a powerful spot in the internet’s infrastructure that guarantees websites are not fake, guiding users to them seamlessly.

The company’s Panamanian registration records show that it has the identical slate of officers, agents and partners as a spyware maker identified this year as an affiliate of Arizona-based Packet Forensics, which public contracting records and company documents show has sold communication interception services to U.S. government agencies for more than a decade.

[…]

In the earlier spyware matter, researchers Joel Reardon of the University of Calgary and Serge Egelman of the University of California at Berkeley found that a Panamanian company, Measurement Systems, had been paying developers to include code in a variety of innocuous apps to record and transmit users’ phone numbers, email addresses and exact locations. They estimated that those apps were downloaded more than 60 million times, including 10 million downloads of Muslim prayer apps.

Measurement Systems’ website was registered by Vostrom Holdings, according to historic domain name records. Vostrom filed papers in 2007 to do business as Packet Forensics, according to Virginia state records. Measurement Systems was registered in Virginia by Saulino, according to another state filing.

More details by Reardon.

Cory Doctorow does a great job explaining the context and the general security issues.

EDITED TO ADD (11/10): Slashdot thread.

Simplifying Amazon EC2 instance type flexibility with new attribute-based instance type selection features

Post Syndicated from Sheila Busser original https://aws.amazon.com/blogs/compute/simplifying-amazon-ec2-instance-type-flexibility-with-new-attribute-based-instance-type-selection-features/

This blog is written by Rajesh Kesaraju, Sr. Solution Architect, EC2-Flexible Compute and Peter Manastyrny, Sr. Product Manager, EC2.

Today AWS is adding two new attributes for the attribute-based instance type selection (ABS) feature to make it even easier to create and manage instance type flexible configurations on Amazon EC2. The new network bandwidth attribute allows customers to request instances based on the network requirements of their workload. The new allowed instance types attribute is useful for workloads that have some instance type flexibility but still need more granular control over which instance types to run on.

The two new attributes are supported in EC2 Auto Scaling Groups (ASG), EC2 Fleet, Spot Fleet, and Spot Placement Score.

Before exploring the new attributes in detail, let us review the core ABS capability.

ABS refresher

ABS lets you express your instance type requirements as a set of attributes, such as vCPU, memory, and storage when provisioning EC2 instances with ASG, EC2 Fleet, or Spot Fleet. Your requirements are translated by ABS to all matching EC2 instance types, simplifying the creation and maintenance of instance type flexible configurations. ABS identifies the instance types based on attributes that you set in ASG, EC2 Fleet, or Spot Fleet configurations. When Amazon EC2 releases new instance types, ABS will automatically consider them for provisioning if they match the selected attributes, removing the need to update configurations to include new instance types.

ABS helps you to shift from an infrastructure-first to an application-first paradigm. ABS is ideal for workloads that need generic compute resources and do not necessarily require the hardware differentiation that the Amazon EC2 instance type portfolio delivers. By defining a set of compute attributes instead of specific instance types, you allow ABS to always consider the broadest and newest set of instance types that qualify for your workload. When you use EC2 Spot Instances to optimize your costs and save up to 90% compared to On-Demand prices, instance type diversification is the key to access the highest amount of Spot capacity. ABS provides an easy way to configure and maintain instance type flexible configurations to run fault-tolerant workloads on Spot Instances.

We recommend ABS as the default compute provisioning method for instance type flexible workloads including containerized apps, microservices, web applications, big data, and CI/CD.

Now, let us dive deep on the two new attributes: network bandwidth and allowed instance types.

How network bandwidth attribute for ABS works

Network bandwidth attribute allows customers with network-sensitive workloads to specify their network bandwidth requirements for compute infrastructure. Some of the workloads that depend on network bandwidth include video streaming, networking appliances (e.g., firewalls), and data processing workloads that require faster inter-node communication and high-volume data handling.

The network bandwidth attribute uses the same min/max format as other ABS attributes (e.g., vCPU count or memory) that assume a numeric value or range (e.g., min: ‘10’ or min: ‘15’; max: ‘40’). Note that setting the minimum network bandwidth does not guarantee that your instance will achieve that network bandwidth. ABS will identify instance types that support the specified minimum bandwidth, but the actual bandwidth of your instance might go below the specified minimum at times.

Two important things to remember when using the network bandwidth attribute are:

  • ABS will only take burst bandwidth values into account when evaluating maximum values. When evaluating minimum values, only the baseline bandwidth will be considered.
    • For example, if you specify the minimum bandwidth as 10 Gbps, instances that have burst bandwidth of “up to 10 Gbps” will not be considered, as their baseline bandwidth is lower than the minimum requested value (e.g., m5.4xlarge is burstable up to 10 Gbps with a baseline bandwidth of 5 Gbps).
    • Alternatively, c5n.2xlarge, which is burstable up to 25 Gbps with a baseline bandwidth of 10 Gbps will be considered because its baseline bandwidth meets the minimum requested value.
  • Our recommendation is to only set a value for maximum network bandwidth if you have specific requirements to restrict instances with higher bandwidth. That would help to ensure that ABS considers the broadest possible set of instance types to choose from.

Using the network bandwidth attribute in ASG

In this example, let us look at a high-performance computing (HPC) workload or similar network bandwidth sensitive workload that requires a high volume of inter-node communications. We use ABS to select instances that have at minimum 10 Gpbs of network bandwidth and at least 32 vCPUs and 64 GiB of memory.

To get started, you can create or update an ASG or EC2 Fleet set up with ABS configuration and specify the network bandwidth attribute.

The following example shows an ABS configuration with network bandwidth attribute set to a minimum of 10 Gbps. In this example, we do not set a maximum limit for network bandwidth. This is done to remain flexible and avoid restricting available instance type choices that meet our minimum network bandwidth requirement.

Create the following configuration file and name it: my_asg_network_bandwidth_configuration.json

{
    "AutoScalingGroupName": "network-bandwidth-based-instances-asg",
    "DesiredCapacityType": "units",
    "MixedInstancesPolicy": {
        "LaunchTemplate": {
            "LaunchTemplateSpecification": {
                "LaunchTemplateName": "LaunchTemplate-x86",
                "Version": "$Latest"
            },
            "Overrides": [
                {
                "InstanceRequirements": {
                    "VCpuCount": {"Min": 32},
                    "MemoryMiB": {"Min": 65536},
                    "NetworkBandwidthGbps": {"Min": 10} }
                 }
            ]
        },
        "InstancesDistribution": {
            "OnDemandPercentageAboveBaseCapacity": 30,
            "SpotAllocationStrategy": "capacity-optimized"
        }
    },
    "MinSize": 1,
    "MaxSize": 10,
    "DesiredCapacity":10,
    "VPCZoneIdentifier": "subnet-f76e208a, subnet-f76e208b, subnet-f76e208c"
}

Next, let us create an ASG using the following command:

my_asg_network_bandwidth_configuration.json file

aws autoscaling create-auto-scaling-group --cli-input-json file://my_asg_network_bandwidth_configuration.json

As a result, you have created an ASG that may include instance types m5.8xlarge, m5.12xlarge, m5.16xlarge, m5n.8xlarge, and c5.9xlarge, among others. The actual selection at the time of the request is made by capacity optimized Spot allocation strategy. If EC2 releases an instance type in the future that would satisfy the attributes provided in the request, that instance will also be automatically considered for provisioning.

Considered Instances (not an exhaustive list)


Instance Type        Network Bandwidth
m5.8xlarge             “10 Gbps”

m5.12xlarge           “12 Gbps”

m5.16xlarge           “20 Gbps”

m5n.8xlarge          “25 Gbps”

c5.9xlarge               “10 Gbps”

c5.12xlarge             “12 Gbps”

c5.18xlarge             “25 Gbps”

c5n.9xlarge            “50 Gbps”

c5n.18xlarge          “100 Gbps”

…

Now let us focus our attention on another new attribute – allowed instance types.

How allowed instance types attribute works in ABS

As discussed earlier, ABS lets us provision compute infrastructure based on our application requirements instead of selecting specific EC2 instance types. Although this infrastructure agnostic approach is suitable for many workloads, some workloads, while having some instance type flexibility, still need to limit the selection to specific instance families, and/or generations due to reasons like licensing or compliance requirements, application performance benchmarking, and others. Furthermore, customers have asked us to provide the ability to restrict the auto-consideration of newly released instances types in their ABS configurations to meet their specific hardware qualification requirements before considering them for their workload. To provide this functionality, we added a new allowed instance types attribute to ABS.

The allowed instance types attribute allows ABS customers to narrow down the list of instance types that ABS considers for selection to a specific list of instances, families, or generations. It takes a comma separated list of specific instance types, instance families, and wildcard (*) patterns. Please note, that it does not use the full regular expression syntax.

For example, consider container-based web application that can only run on any 5th generation instances from compute optimized (c), general purpose (m), or memory optimized (r) families. It can be specified as “AllowedInstanceTypes”: [“c5*”, “m5*”,”r5*”].

Another example could be to limit the ABS selection to only memory-optimized instances for big data Spark workloads. It can be specified as “AllowedInstanceTypes”: [“r6*”, “r5*”, “r4*”].

Note that you cannot use both the existing exclude instance types and the new allowed instance types attributes together, because it would lead to a validation error.

Using allowed instance types attribute in ASG

Let us look at the InstanceRequirements section of an ASG configuration file for a sample web application. The AllowedInstanceTypes attribute is configured as [“c5.*”, “m5.*”,”c4.*”, “m4.*”] which means that ABS will limit the instance type consideration set to any instance from 4th and 5th generation of c or m families. Additional attributes are defined to a minimum of 4 vCPUs and 16 GiB RAM and allow both Intel and AMD processors.

Create the following configuration file and name it: my_asg_allow_instance_types_configuration.json

{
    "AutoScalingGroupName": "allow-instance-types-based-instances-asg",
    "DesiredCapacityType": "units",
    "MixedInstancesPolicy": {
        "LaunchTemplate": {
            "LaunchTemplateSpecification": {
                "LaunchTemplateName": "LaunchTemplate-x86",
                "Version": "$Latest"
            },
            "Overrides": [
                {
                "InstanceRequirements": {
                    "VCpuCount": {"Min": 4},
                    "MemoryMiB": {"Min": 16384},
                    "CpuManufacturers": ["intel","amd"],
                    "AllowedInstanceTypes": ["c5.*", "m5.*","c4.*", "m4.*"] }
            }
            ]
        },
        "InstancesDistribution": {
            "OnDemandPercentageAboveBaseCapacity": 30,
            "SpotAllocationStrategy": "capacity-optimized"
        }
    },
    "MinSize": 1,
    "MaxSize": 10,
    "DesiredCapacity":10,
    "VPCZoneIdentifier": "subnet-f76e208a, subnet-f76e208b, subnet-f76e208c"
}

As a result, you have created an ASG that may include instance types like m5.xlarge, m5.2xlarge, c5.xlarge, and c5.2xlarge, among others. The actual selection at the time of the request is made by capacity optimized Spot allocation strategy. Please note that if EC2 will in the future release a new instance type which will satisfy the other attributes provided in the request, but will not be a member of 4th or 5th generation of m or c families specified in the allowed instance types attribute, the instance type will not be considered for provisioning.

Selected Instances (not an exhaustive list)

m5.xlarge

m5.2xlarge

m5.4xlarge

…

c5.xlarge

c5.2xlarge

…

m4.xlarge

m4.2xlarge

m4.4xlarge

…

c4.xlarge

c4.2xlarge

…

As you can see, ABS considers a broad set of instance types for provisioning, however they all meet the compute attributes that are required for your workload.

Cleanup

To delete both ASGs and terminate all the instances, execute the following commands:

aws autoscaling delete-auto-scaling-group --auto-scaling-group-name network-bandwidth-based-instances-asg --force-delete

aws autoscaling delete-auto-scaling-group --auto-scaling-group-name allow-instance-types-based-instances-asg --force-delete

Conclusion

In this post, we explored the two new ABS attributes – network bandwidth and allowed instance types. Customers can use these attributes to select instances based on network bandwidth and to limit the set of instances that ABS selects from. The two new attributes, as well as the existing set of ABS attributes enable you to save time on creating and maintaining instance type flexible configurations and make it even easier to express the compute requirements of your workload.

ABS represents the paradigm shift in the way that our customers interact with compute, making it easier than ever to request diversified compute resources at scale. We recommend ABS as a tool to help you identify and access the largest amount of EC2 compute capacity for your instance type flexible workloads.

Defeating Phishing-Resistant Multifactor Authentication

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/defeating-phishing-resistant-multifactor-authentication.html

CISA is now pushing phishing-resistant multifactor authentication.

Roger Grimes has an excellent post reminding everyone that “phishing-resistant” is not “phishing proof,” and that everyone needs to stop pretending otherwise. His list of different attacks is particularly useful.

Using Wi-FI to See through Walls

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/using-wi-fi-to-see-through-walls.html

This technique measures device response time to determine distance:

The scientists tested the exploit by modifying an off-the-shelf drone to create a flying scanning device, the Wi-Peep. The robotic aircraft sends several messages to each device as it flies around, establishing the positions of devices in each room. A thief using the drone could find vulnerable areas in a home or office by checking for the absence of security cameras and other signs that a room is monitored or occupied. It could also be used to follow a security guard, or even to help rival hotels spy on each other by gauging the number of rooms in use.

There have been attempts to exploit similar WiFi problems before, but the team says these typically require bulky and costly devices that would give away attempts. Wi-Peep only requires a small drone and about $15 US in equipment that includes two WiFi modules and a voltage regulator. An intruder could quickly scan a building without revealing their presence.

Research paper.

The Conviction of Uber’s Chief Security Officer

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/the-conviction-of-ubers-chief-security-officer.html

I have been meaning to write about Joe Sullivan, Uber’s former Chief Security Officer. He was convicted of crimes related to covering up a cyberattack against Uber. It’s a complicated case, and I’m not convinced that he deserved a guilty ruling or that it’s a good thing for the industry.

I may still write something, but until then, this essay on the topic is worth reading.

Friday Squid Blogging: Newfoundland Giant Squid Sculpture

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/friday-squid-blogging-newfoundland-giant-squid-sculpture.html

In 1878, a 55-foot-long giant squid washed up on the shores of Glover’s Harbour, Newfoundland. It’s the largest giant squid ever recorded—although scientists now think that the size was an exaggeration or the result of postmortem stretching—and there’s a full-sized statue of it near the beach where it was found.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Read my blog posting guidelines here.

NSA on Supply Chain Security

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/nsa-on-supply-chain-security.html

The NSA (together with CISA) has published a long report on supply-chain security: “Securing the Software Supply Chain: Recommended Practices Guide for Suppliers.“:

Prevention is often seen as the responsibility of the software developer, as they are required to securely develop and deliver code, verify third party components, and harden the build environment. But the supplier also holds a critical responsibility in ensuring the security and integrity of our software. After all, the software vendor is responsible for liaising between the customer and software developer. It is through this relationship that additional security features can be applied via contractual agreements, software releases and updates, notifications and mitigations of vulnerabilities.

Software suppliers will find guidance from NSA and our partners on preparing organizations by defining software security checks, protecting software, producing well-secured software, and responding to vulnerabilities on a continuous basis. Until all stakeholders seek to mitigate concerns specific to their area of responsibility, the software supply chain cycle will be vulnerable and at risk for potential compromise.

They previously published “Securing the Software Supply Chain: Recommended Practices Guide for Developers.” And they plan on publishing one focused on customers.

Your guide to Amazon Communication Developer Services (CDS) at re:Invent 2022

Post Syndicated from Lauren Cudney original https://aws.amazon.com/blogs/messaging-and-targeting/your-guide-to-amazon-communication-developer-services-cds-at-reinvent-2022/

Your guide to AWS Communication Developer Services (CDS) at re:Invent 2022

AWS Communication Developer Services  has an exciting lineup at re:Invent this year, with 12 sessions spanning communication solutions through Amazon Pinpoint, Amazon Simple Email Service, and Amazon Chime SDK. With breakouts, workshops, and an in-person customer reception, there will be something for everyone. Here is a detailed guide to help you build your agenda and get the most our of your re:Invent 2022 experience.

AWS guide to CDS CPaaS at reInvent

In addition to AWS executive keynotes, like Adam Selipsky’s on Tuesday morning, there are several session you don’t want to miss:

Topic – CPaaS and AWS Communication Services

Improving multichannel communications (BIZ201) – Breakout session
Wednesday November 30, 11:30 PM – 12:30 PM PDT
Your communication strategy directly impacts customer satisfaction, revenue, growth, and retention. This session covers how the customer communication landscape is changing and how you can shift your product strategies to impact business outcomes. Learn how AWS Communication Developer Services (CDS) improve customer communication through CPaaS channels like email, SMS, push notifications, telephony, audio, and video. Explore how building a multichannel architecture can shift user habits and increase satisfaction. This session is tailored for chief marketing officers, chief product officers, chief innovation officers, marketing technologists, and communication builders.
Speaker: Siddhartha Rao, GM, Amazon Chime SDK, Amazon Web Services

Topic – Email (Amazon Simple Email Service)

Improve email inbox deliverability with innovation from Amazon SES (BIZ306) – Chalk Talk
Wednesday, November 30, 4:00 – 5:00 PM PDT
This chalk talk demonstrates how to improve email deliverability, leading to increased email ROI. Learn how to build new features in Amazon SES that increase deliverability through system and configuration suggestions, and then automatically implement those changes for more seamless sending. This chalk talk is designed for email data engineers, marketing operations professionals, and marketing engineers.

Topic – Messaging and Orchestration through SMS, Push, In App (Amazon Pinpoint)

Successfully engage customers using Amazon Pinpoint’s SMS channel (BIZ301) – Chalk Talk
Monday, November 28, 1:00 – 2:00 PM PDT
Developing or upgrading an SMS program can be challenging for any enterprise undergoing digital transformation. In this chalk talk, Amazon Pinpoint experts demonstrate how to build a two-way SMS solution and how to monitor global message deliverability. This talk is designed for communication builders, marketing technologists, and IT decision-makers.

Integrate AI and ML into customer engagement (BIZ309) – Chalk Talk
Thursday, December 1, 3:30 – 4:30 PM PDT
In this chalk talk, learn how to use Amazon Lex AI and Amazon Personalize ML to create two-way engagements with customers in Amazon Pinpoint. Amazon Pinpoint is an omni-channel messaging platform on AWS, supporting SMS, push notifications, email, voice, and custom channels. Follow along as Amazon Pinpoint specialists walk through sample architecture and code that uses Amazon Lex AI chatbots to check order status, share updates via the customer’s preferred channel, and personalize responses to the customer, taking customer engagement to the next level.

Topic – Voice and Video (Amazon Chime SDK)

Use AI to live transcribe and translate multiparty video calls – Workshop
Thursday, December 1, 2:00 – 4:00 PM PDT
Harness the power of real-time transcription in web-based voice or video calls through the Amazon Chime SDK. Join this interactive workshop to learn how to build transcription and translation into multiparty video calls requiring additional compliance and language accessibility, such as telehealth appointments, government services, parent-teacher interactions, or financial services. Experts guide attendees in a hands-on demo that combines the power of Amazon Chime SDK, Amazon Transcribe, and Amazon Translate into one simple interface. This workshop is designed for communication developers. You must bring your laptop to participate.

We look forward to seeing you at re:Invent!

Iran’s Digital Surveillance Tools Leaked

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/11/irans-digital-surveillance-tools-leaked.html

It’s Iran’s turn to have its digital surveillance tools leaked:

According to these internal documents, SIAM is a computer system that works behind the scenes of Iranian cellular networks, providing its operators a broad menu of remote commands to alter, disrupt, and monitor how customers use their phones. The tools can slow their data connections to a crawl, break the encryption of phone calls, track the movements of individuals or large groups, and produce detailed metadata summaries of who spoke to whom, when, and where. Such a system could help the government invisibly quash the ongoing protests ­—or those of tomorrow ­—an expert who reviewed the SIAM documents told The Intercept.

[…]

SIAM gives the government’s Communications Regulatory Authority ­—Iran’s telecommunications regulator ­—turnkey access to the activities and capabilities of the country’s mobile users. “Based on CRA rules and regulations all telecom operators must provide CRA direct access to their system for query customers information and change their services via web service,” reads an English-language document obtained by The Intercept. (Neither the CRA nor Iran’s mission to the United Nations responded to a requests for comment.)

Lots of details, and links to the leaked documents, at the Intercept webpage.

Apple Only Commits to Patching Latest OS Version

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/10/apple-only-commits-to-patching-latest-os-version.html

People have suspected this for a while, but Apple has made it official. It only commits to fully patching the latest version of its OS, even though it claims to support older versions.

From ArsTechnica:

In other words, while Apple will provide security-related updates for older versions of its operating systems, only the most recent upgrades will receive updates for every security problem Apple knows about. Apple currently provides security updates to macOS 11 Big Sur and macOS 12 Monterey alongside the newly released macOS Ventura, and in the past, it has released security updates for older iOS versions for devices that can’t install the latest upgrades.

This confirms something that independent security researchers have been aware of for a while but that Apple hasn’t publicly articulated before. Intego Chief Security Analyst Joshua Long has tracked the CVEs patched by different macOS and iOS updates for years and generally found that bugs patched in the newest OS versions can go months before being patched in older (but still ostensibly “supported”) versions, when they’re patched at all.

Friday Squid Blogging: Chinese Squid Fishing

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/10/friday-squid-blogging-chinese-squid-fishing.html

China claims that it is “engaging in responsible squid fishing”:

Chen Xinjun, dean of the College of Marine Sciences at Shanghai Ocean University, made the remarks in response to recent accusations by foreign reporters and actor Leonardo DiCaprio that China is depleting its own fish stock and that Chinese boats have sailed to other waters to continue deep-sea fishing, particularly near Ecuador, affecting local fish stocks in the South American nation.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Read my blog posting guidelines here.

Critical Vulnerability in Open SSL

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2022/10/critical-vulnerability-in-open-ssl.html

There are no details yet, but it’s really important that you patch Open SSL 3.x when the new version comes out on Tuesday.

How bad is “Critical”? According to OpenSSL, an issue of critical severity affects common configurations and is also likely exploitable.

It’s likely to be abused to disclose server memory contents, and potentially reveal user details, and could be easily exploited remotely to compromise server private keys or execute code execute remotely. In other words, pretty much everything you don’t want happening on your production systems.

Slashdot thread.