Optimizing Observability: A Deep Dive into AWS Lambda Metrics

Authors

  • Balasubrahmanya Balakrishna Senior Lead Software Engineer, Richmond, VA, USA.  Author

DOI:

https://doi.org/10.47363/JAICC/2022(1)160

Keywords:

AWS Lambda, CloudWatch, CloudWatch Metrics, AWS Powertools for Lamda

Abstract

The importance of observability in AWS Lambda systems is examined in this technical article, which focuses on using Python and the AWS Lambda
Powertools to improve monitoring capabilities. With serverless computing, AWS Lambda has emerged as a critical service that lets developers concentrate on writing code rather than maintaining infrastructure. Nonetheless, troubleshooting, performance improvement, and guaranteeing the dependability of serverless apps depend on effective observability. Using specially designed Python Serverless Restful API and AWS Lambda Powertools, this article thoroughly analyzes important AWS Lambda metrics, their interpretation, and techniques to improve observability while running serverless applications in the AWS Lambda environment.


The author will use Python with the AWS Lambda Powertools, implemented as a Lambda layer, to facilitate seamless integration for custom metrics and
advanced observability features.

Author Biography

  • Balasubrahmanya Balakrishna, Senior Lead Software Engineer, Richmond, VA, USA. 

    Balasubrahmanya Balakrishna, Senior Lead Software Engineer, Richmond, VA, USA. 

Downloads

Published

2022-11-25

How to Cite

Optimizing Observability: A Deep Dive into AWS Lambda Metrics. (2022). Journal of Artificial Intelligence & Cloud Computing, 1(4), 1-4. https://doi.org/10.47363/JAICC/2022(1)160

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