Category: Advanced (300)

In this post, we explore using AWS Step Function state machine with asynchronous AWS services, look at some scenarios where the processing time can be unpredictable, explain when traditional solutions such as polling (periodically check) fall short, and demonstrate how to implement a generalized callback pattern to handle asynchronous operations into a more manageable synchronous flow.

This post examines the benefits of transitioning Lambda functions to IPv6, provides practical guidance for implementing dual-stack support in your Lambda environment, and considerations for maintaining compatibility with existing systems during migration.

In this post, you’ll learn how to use AWS Step Functions Distributed Map to process Amazon Athena data manifest and Parquet files through a step-by-step demonstration.

In this post, we explore how to optimize processing array data embedded within complex JSON structures using AWS Step Functions Distributed Map. You’ll learn how to use ItemsPointer to reduce the complexity of your state machine definitions, create more flexible workflow designs, and streamline your data processing pipelines—all without writing additional transformation code or AWS Lambda functions.

In this post, you’ll learn how to process Amazon S3 objects at scale with the new AWS Step Functions Distributed Map S3 prefix and transformation capabilities.

In this post, you learn how to implement blue/green deployments by using Amazon API Gateway for your APIs. For this post, we use AWS Lambda functions on the backend. However, you can follow the same strategy for other backend implementations of the APIs. All the required infrastructure is deployed by using AWS Serverless Application Model (AWS SAM).

When migrating Amazon EC2 instances with encrypted Amazon EBS volumes across AWS Regions with in the same account or a different account, you face a particular challenge: AWS KMS keys are AWS Region-specific and cannot be shared across AWS Regions. This post provides a step-by-step approach to successfully migrate your encrypted EC2 instances without compromising your security posture by sharing your KMS keys.

Users usually package their function code as container images when using machine learning (ML) models that are larger than 250 MB, which is the Lambda deployment package size limit for zip files. In this post, we demonstrate an approach that downloads ML models directly from Amazon S3 into your function’s memory so that you can continue packaging your function code using zip files.

In this post, we show how to use Step Functions Distributed Map to process Amazon S3 objects and export results to Amazon S3 Tables, creating a scalable and maintainable data processing pipeline.

This post demonstrates how you can connect CloudFront with a Private REST API in Amazon REST API Gateway using a VPC origin.