12/16/2023 0 Comments Serverless sqs queue![]() ![]() We will use AWS Lambda Powertools’ batch utility in combination with tenacity for retries and safe handling. Now that we understand the theory let’s write the improved Lambda function code with the hybrid approach. However, momentarily network issues, bugs, and service downtime are dynamic in nature, and a retry strategy might be able resolve the processing issue. Keep in mind that once new items are added to the SQS, the failed batch items will be part of the latest batch that the function receives but keep in mind that messages have retention time so that they won’t remain forever on the queue.īe aware that errors such as invalid input validation or verification (security-wise) should not be retried, as they will fail again and again. (3) If the Lambda marked items as failed to process, the SQS will invoke the function again with a batch containing only the failed items once the SQS’s visibility timeout has passed. If all items are successfully processed, the function marks that zero items failed to process. (2) The function marks to the SQS what items failed processing (after failed retry attempts) or ends with an exception if the entire batch has failed. The Lambda function iterates over the batch and handles each batch item and retries its processing (1a in the diagram, if required) with ‘tenacity’. (1) SQS triggers a function with a batch. A hybrid approach - use options 1 and 2 together, which we will implement as the preferred method in this post.A function marks the partially failed messages. A function raises an exception at the end of its execution, thus returning the entire batch to the queue.ī. An automatic retry can be triggered in two use cases:Ī. However, since with SQS, we deal with batches of records, and not just one, we need to be aware of the total runtime of the function and leave enough time for the rest of the batch and its potential retries, which can be a bit tricky, resulting in a potential function timeout. Run a retry during the Lambda function’s runtime, i.e., use the tenacity library (or any other retry library) to decorate any inner logic function with automatic retry. There are three options to handle failures: So, let’s review possible methods to handle failures while remaining resilient and self-healing. However, what happens if one item fails processing due to momentarily network issues, external services bugs, or other random issues, and how do we recover? The Lambda function will iterate each item, process it and continue to the next item. SQS triggers our Lambda function with an SQS event containing batch items. Note that this article builds on the code examples from the first article. However, we didn’t focus on processing failures. We implemented the AWS CDK infrastructure and Lambda function handler codes. In the first article, in my SQS best practices, we defined the SQS to Lambda function pattern. This blog post was originally published on my website, “Ran The Builder.” In the third part of the series, you will learn about dead letter queue best practices and how to handle failures correctly. The first article will teach you how to efficiently handle Amazon SQS batches with AWS Lambda Powertools for Python and AWS CDK code examples. This article will teach you how to handle Amazon SQS batch processing failures and master automatic retries with AWS Lambda Powertools for Python and AWS CDK code examples. This is the second article in three part series about SQS best practices. However, on the Lambda function side, handling this input can get tricky, especially when errors and retries come into mind. SQS can trigger a Lambda function as its target and send the batch items as input. It strongly integrates with AWS Lambda, its native partner, as a target destination. Amazon Simple Queue Service (SQS) is a powerful service designed to manage the messaging needs of robust, decoupled microservices. ![]()
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