Lambda & Serverless
7 articles from official documentation
Automate AWS Lambda Code Integrity with Terraform and Code Signing
Ensure your AWS Lambda functions run only trusted code with automated code signing. Leverage AWS Signer and Terraform to enforce signature validation and enhance security in your deployments.
- →Implement AWS Signer with SHA384-ECDSA for strong cryptographic security.
- →Automate code signing with Terraform to ensure consistent deployments.
Mastering Lambda Function URLs: The Key to Simplified HTTP Access
Lambda function URLs provide a dedicated HTTP(S) endpoint for your Lambda functions, streamlining invocation. With automatic CORS header handling, they simplify cross-origin requests. Dive in to discover how to leverage this powerful feature effectively.
- →Create a function URL using the AWS CLI with the command: `aws lambda create-function-url-config`.
- →Set the authentication type to AWS_IAM or NONE based on your security requirements.
Mastering Lambda Function Scaling and Concurrency
Scaling AWS Lambda functions can be a game-changer for your applications, but understanding concurrency is crucial. Learn how to calculate concurrency based on request rates and durations to optimize performance effectively.
- →Understand concurrency as the number of in-flight requests your Lambda function handles.
- →Calculate concurrency using the formula: Concurrency = (average requests per second) * (average request duration in seconds).
Boosting Lambda Startup Times with SnapStart
Lambda SnapStart can reduce your function's cold start times to sub-second levels by caching the initialized execution environment. This feature is a game changer for performance-sensitive applications. Dive in to learn how it works and what you need to watch out for.
- →Leverage SnapStart to achieve sub-second startup times for your Lambda functions.
- →Understand that SnapStart uses Firecracker microVM snapshots to cache execution environments.
Mastering the Lambda Execution Environment Lifecycle
Understanding the Lambda execution environment lifecycle is crucial for optimizing your serverless applications. The Init phase kicks off with starting extensions and bootstrapping the runtime, which can significantly affect performance. Dive in to learn how this impacts your function invocations.
- →Understand the Init phase: it starts extensions, bootstraps the runtime, and runs static code.
- →Monitor the Invoke phase: it sends events to the runtime and extensions for each invocation.
Unlocking AI/ML Potential: AWS's New Tools for Developers
AWS is rolling out powerful tools to streamline AI and ML development. The Agent Plugin for AWS Serverless simplifies building serverless applications with AI coding assistants. Dive in to discover how these innovations can elevate your projects.
- →Leverage the AWS AI & ML Scholars program to enhance your team's AI skills.
- →Utilize the Agent Plugin for AWS Serverless to streamline serverless application development.
Automate AWS Lambda Runtime Upgrades with AWS Transform Custom
Tired of managing deprecated AWS Lambda runtimes manually? AWS Transform custom automates the migration from outdated versions like Python 3.8 to modern ones like Python 3.13. This tool learns from your code and executes upgrades consistently at scale.
- →Automate migration from deprecated runtimes like Python 3.8 to Python 3.13 using AWS Transform custom.
- →Use the `-t` flag to trust all tool executions, but be cautious of the risks involved.
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