![]() For example, if a function errors because of a downstream system being overwhelmed, you can use AsyncEventAge and Concurrency metrics. It is best practice to alert on function errors using the error metric and use the metrics to get better insights into retry behavior, such as interval between retries. Invoke the function: aws lambda invoke \.Build and deploy: sam build & sam deploy –region $REGION.Raise Exception(“Lambda function throwing exception”) Edit the function code in hello_world/app.py to raise an exception: def handler(event, context):.To simulate a function error, throw an exception from the Lambda handler: Lambda drops the event from its internal queue if the retries are exhausted. Lambda retries processing the asynchronous invocation event for a maximum of two times, in case of function error or exception. Scenario 1: Troubleshooting delays due to function error These scenarios show how you can use the three new metrics. After waiting a few seconds, refresh if you don’t see the metric immediately. Under “Graphed metrics”, change the statistic to sum and “Period” to 1 minute. Choose Lambda > By Function Name and choose AsyncEventsReceived for the function you created.Choose All Metrics under Metrics in the left-hand panel in the CloudWatch console and search for “async”:.Invoke the function using AWS CLI: aws lambda invoke \.Save the name of the function in an environment variable: FUNCTION_NAME=$(aws cloudformation describe-stacks \.Keep everything else as default values: sam build Provide lambda-async-metric as the stack name when prompted. Clone the GitHub repository: git clone.To test the following scenarios, you must install: You can deploy a sample Lambda function to show how to use the new metrics for troubleshooting. This flowchart shows the way that you can combine the new metrics with existing metrics to troubleshoot problems with asynchronous processing: The AsyncEventsDropped metric is a measure of the number of events dropped because of processing failure. Customers can set alarms on this metric to alert on SLA breaches. An increasing value shows retries because of error or throttles. With retries, Lambda emits this metric every time it attempts to invoke the function with the event. The AsyncEventAge metric is a measure of the difference between the time that an event is first enqueued in the internal queue and the time the Lambda service invokes the function. Lambda does not emit this metric for retried events. ![]() This is possible because of transient networking issues. In case this metric is lower than the number of events that you expect, it shows that the source did not emit events or events did not arrive at the Lambda service. You can track events from the client using custom CloudWatch metrics or extract it from logs using Embedded Metric Format (EMF). The AsyncEventsReceived metric is a measure of the number of events enqueued in Lambda’s internal queue. Set maximum age of event on function between 60 seconds to 6 hours Set retry attempt on function between 0-2 Visit the asynchronous Lambda invocations documentation to learn more: Causeįunction errors (returned from code or runtime, such as timeouts) This table summarizes the retry behavior. However, the event once discarded from the event queue goes to the destination or DLQ, if configured. A separate process reads events from the queue and sends them to the function.īy default, Lambda discards events from its event queue if the retry policy has exceeded the number of configured retries or the event reached its maximum age. ![]() Lambda uses an internal queue to store events. OverviewĪWS services such as Amazon S3, Amazon SNS, and Amazon EventBridge invoke Lambda functions asynchronously. This blog and the sample application provide examples that highlight the usage of the new metrics. ![]() These issues include throttling, concurrency limit, function errors, processing latency because of retries, missing events, and taking corrective action. With these new metrics for asynchronous function invocations, you can identify the root cause of processing issues. Previously, customers found it challenging to monitor the processing of asynchronous invocations. These metrics provide visibility for asynchronous Lambda function invocations. Today, AWS is announcing three new Amazon CloudWatch metrics for asynchronous AWS Lambda function invocations: AsyncEventsReceived, AsyncEventAge, and AsyncEventsDropped. This post is written by Arthi Jaganathan, Principal SA, Serverless and Dhiraj Mahapatro, Principal SA, Serverless.
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