aws-lambda-power-tuning

AWS Lambda Power Tuning is an open-source tool that can help you visualize and fine-tune the memory/power configuration of Lambda functions. It runs in your own AWS account - powered by AWS Step Functions - and it supports three optimization strategies: cost, speed, and balanced. (by alexcasalboni)

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aws-lambda-power-tuning reviews and mentions

Posts with mentions or reviews of aws-lambda-power-tuning. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-15.
  • Optimizing Costs in the Cloud: Embracing a FinOps Mindset
    1 project | dev.to | 2 Apr 2024
    Sometimes, changing services, like opting for HTTP over REST API Gateway, leveraging tools like Lambda Powertuning to optimize functions, or reducing a CloudWatch log retention and changing log level, can lead to significant savings.
  • AWS SnapStart - Part 13 Measuring warm starts with Java 21 using different Lambda memory settings
    4 projects | dev.to | 15 Jan 2024
    In case of not enabling SnapStart for the Lambda function we observed that increasing memory reduces the warm execution time for our use case especially for p>90. As adding more memory to the Lambda function is also a cost factor, the sweet spot between cold and warm start time and cost is somewhere between 768 and 1204 MB memory setting for the Lambda function for our use case. You can use AWS Lambda Power Tuning for very nice visualisations.
  • How to enhance your Lambda function performance with memory configuration?
    1 project | dev.to | 21 Aug 2023
    The aws lambda power tuning tool helps optimise the Lambda performance and cost in a data-driven manner. Let's try it out:
  • Controlling Cloud Costs: Strategies for keeping on top of your AWS cloud spend
    1 project | dev.to | 21 Jun 2023
    For Lambda, a very useful tool to help optimise is the AWS Lambda Power Tuning tool, released by Alex Casalboni, Developer Advocate at AWS: https://github.com/alexcasalboni/aws-lambda-power-tuning
  • Best way to decrease latency (API <-> Lambda <-> Dynamodb)
    1 project | /r/aws | 4 Jun 2023
    Lambda memory affects not only the CPU performance and and host execution priority, but also network performance. Be wary though as the price scales linearly. You can use a tool like Lambda Power Tuning to find the sweet spot for your application. https://github.com/alexcasalboni/aws-lambda-power-tuning
  • How to optimize your lambda functions with AWS Lambda power tuning
    2 projects | dev.to | 13 Apr 2023
    This tool, which is open source and available here, takes the form of a Step Function that is deployed on your AWS account. The purpose of this Step Function is to run your lambda with different memory configurations several times and output a comparison in the form of a graph (or JSON) to try to find the optimal balance between cost and execution time. There are three possible optimization modes: cost, execution time, or a "balanced" mode where it tries to find a balance between the two.
  • Developers Journey to AWS Lambda
    4 projects | dev.to | 9 Apr 2023
    The AWS Documentation's Memory and Computing Power page is a good starting point. To avoid configuring it manually, it's worth checking out AWS Lambda Power Tuning, which will help you find the sweet spot.
  • Guide to Serverless & Lambda Testing — Part 2 — Testing Pyramid
    6 projects | dev.to | 13 Mar 2023
    Utilizing tools such as AWS X-Ray, AWS Lambda Power Tuning, and AWS Lambda Powertools tracer utility is recommended. Read more about it here.
  • Tunea tus funciones Lambda
    2 projects | dev.to | 10 Mar 2023
    Install the AWS SAM CLI in your local environment. Configure your AWS credentials (requires AWS CLI installed): $ aws configure Clone this git repository: $ git clone https://github.com/alexcasalboni/aws-lambda-power-tuning.git Build the Lambda layer and any other dependencies (Docker is required): $ cd ./aws-lambda-power-tuning $ sam build -u sam build -u will run SAM build using a Docker container image that provides an environment similar to that which your function would run in. SAM build in-turn looks at your AWS SAM template file for information about Lambda functions and layers in this project. Once the build has completed you should see output that states Build Succeeded. If not there will be error messages providing guidance on what went wrong. Deploy the application using the SAM deploy "guided" mode: $ sam deploy -g
  • AWS Serverless Production Readiness Checklist
    2 projects | dev.to | 21 Jan 2023
    Use AWS Lambda Power Tuning to balance cost and performance.
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