AWS Certified Developer Associate DVA-C02 Practice Question
You are tasked with augmenting the observability of a serverless function to ensure granular tracking of its execution time when processing streaming data. How would you enable systematic tracking of the function's processing duration to aid in swift identification and remediation of performance bottlenecks?
Configure an alert based on a heuristic evaluation of the serverless platform's function execution duration.
Manually record log entries for execution times, and later process them with an external application to transform into structured metrics.
Utilize the embedded metric format for custom metrics creation within your serverless application logic.
Depend exclusively on the standard metrics offered by the serverless platform for average processing times without modifications.
Implementing the CloudWatch embedded metric format (EMF) within your serverless function code allows you to generate custom metrics with rich detail regarding function execution. This method provides a higher resolution of data with minimal operational impact, as it eliminates the need for additional utilities to parse extensive log files or the insufficient granularity that may come from relying solely on automatic monitoring services.
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What is the CloudWatch Embedded Metric Format (EMF)?
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AWS Certified Developer Associate DVA-C02
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