DEV Community

Cover image for AWS Lambda powered up by AWS Graviton2
Jones Zachariah Noel for AWS Community ASEAN

Posted on • Updated on

AWS Lambda powered up by AWS Graviton2

AWS Lambda recently announced the launch of AWS Graviton2 processor (arm64 architecture) for Lambda functions which would not only make your Lambda function to execute faster but also optimizes the cost for execution. Graviton2 is an AWS built and owned processor.

You can read more about it from the announcement blog.

Lambda functions which are executing with Amazon Linux 2 runtime, now supports two architectures -

  • arm64 - 64-bit ARM architecture, for the AWS Graviton2 processor.
  • x86_64 – 64-bit x86 architecture, for x86-based processors.

All the existing Lambda functions would be running on x86_64 architecture and this architecture is the default architecture for any new Lambda function.

Key takeaways from the blog

Graviton2 (arm64) for Lambda functions

The Gaviton2 based arm64 architecture makes the computation faster which results in faster execution of the Lambda function and in turn the cost for Lambda is also optimized.

AWS Lambda functions running on Graviton2, using an Arm-based processor architecture designed by AWS, deliver up to 34% better price performance compared to functions running on x86 processors.

The arm64 architecture for Lambda functions is currently available in selected AWS Regions -

  • US East (N. Virginia) us-east-1
  • US East (Ohio) us-east-2
  • US West (Oregon) us-west-2
  • Asia Pacific (Mumbai) ap-south-1
  • Asia Pacific (Singapore) ap-southeast-1
  • Asia Pacific (Sydney) ap-southeast-2
  • Asia Pacific (Tokyo) ap-northeast-1
  • EU (Frankfurt) eu-central-1
  • EU (Ireland) eu-west-1
  • EU (London) eu-west-2

The supported runtimes based on Amazon Linux 2 are -

  • NodeJS 12.x and 14.x
  • Python 3.8 and 3.9
  • Java 8 (java8.al2) and 11
  • .NET Core 3.1
  • Ruby 2.7
  • Custom runtime (provided.al2)

Graviton2 processor is well suited for Lambda functions which are processing heavy high-performance computations, video encoding, simulation workloads.

Setting up Graviton2 (arm64) powered Lambda function

When creating a new Lambda function from the web-console, you can select one of the architecture options - x86_84 (default) or arm64 (Graviton2 Processor).
New Lambda Function
If you want to change the architecture for the existing Lambda function, navigate to the Runtime settings.
Runtime settings
Click on Edit to change the settings.
Edit runtime settings

If you are trying to change an existing Lambda function from x86_64 to arm64 architecture, ensure to check the function code compatibility with arm64 architecture and also suggested migration steps.

Creating and updating Lambda functions with AWS SAM and AWS CDK will soon support both the architectures.

Running Lambda functions with arm64 architecture on x86_64 machine

docker run --rm --privileged multiarch/qemu-user-static --reset -p yes
Enter fullscreen mode Exit fullscreen mode

Performance with arm64 vs x86_64 architecture

For determining the performance I would be reusing the DynamoDB operation performance SAM template from my previous blog post.



With some modifications -

  • Change the number of StepFunctionIndex to 10.
  • Added LambdaMemory and LambdaProcessor parameters to the CloudWatch Custom Metrics. LambdaMemory is taken from Lambda's environment variable and LambdaProcessor is a value set explicitly as environment variable.
await cloudwatch.putMetricData({
        'MetricData': [{
            'MetricName': 'LambdaProcessorMeteric',
            'Dimensions': [{
                    'Name': 'OPERATION',
                    'Value': metric
                },
                {
                    'Name': 'LambdaMemory',
                    'Value': process.env.AWS_LAMBDA_FUNCTION_MEMORY_SIZE
                },
                {
                    'Name': 'LambdaProcessor',
                    'Value': process.env.lambda_fn_arch
                }
            ],
            'Unit': 'Milliseconds',
            'Value': value
        }, ],
        'Namespace': 'LambdaProcessMetrics'
    }).promise()
Enter fullscreen mode Exit fullscreen mode

arm64 architecture duration of several Lambda function invocations
Duration
arm64 architecture average duration of several Lambda function invocations
Average duration
Duration graph
Duration graph

x86_64 architecture duration of several Lambda function invocations
Duration
x86_64 architecture average duration of several Lambda function invocations
Average duration
Duration graph

Duration graph

All query operations with x86_64 and arm64 with 128MB and 256MB Memory
Average All query operations with x86_64 and arm64 with 128MB and 256MB Memory

Minimum All query operations with x86_64 and arm64 with 128MB and 256MB Memory
Maximum All query operations with x86_64 and arm64 with 128MB and 256MB Memory

All scan operations with x86_64 and arm64 with 128MB and 256MB Memory
Average All scan operations with x86_64 and arm64 with 128MB and 256MB Memory
Minimum All scan operations with x86_64 and arm64 with 128MB and 256MB Memory
Maximum All scan operations with x86_64 and arm64 with 128MB and 256MB Memory

All operations
Average All operations
Minimum All operations
Maximum All operations

Pricing

Lambda function with arm64 architecture is cheaper than the x86_64 architecture.

And also both the architectures are included under the 1M free requests per month and 400,000 GB-seconds of compute time per month, usable for functions powered by both x86, and Graviton2 processors, in aggregate.

image
You can know more about Lambda pricing with different architectures.
For this demo, the complete execution cycle is part of the Free Tier limit inclusive of all StepFunction executions and Lambda function executions.

Conclusion

The operational and execution time with x86_64 and arm has significant difference, the DynamoDB operations Scan and Query have different variations of execution time but the Lambda function as a whole, the time of duration is dropped which in-turn affects the billed execution time thus making the cost of Lambda function of arm64 significantly lower than x86_64.

Discussion (2)

Collapse
sabir_mustafa profile image
صابر مصطفی

Great addition. It will help us to write effective code with low price.

Collapse
zachjonesnoel profile image
Jones Zachariah Noel Author

Absolutely! Who doesn't love optimized and efficient code with low cost.