Step by step approach for integrating Datadog with AWS Lambda
AWS Lambda metrics :
There are 3 ways to get metrics from AWS Lambda:
- You can get Cloudwatch Lambda metrics from the Datadog AWS integration
- You can get enhanced metrics by installing Serverless Monitoring for AWS Lambda through the Datadog Lambda Extension.
- You can submit custom metrics to Datadog from your Lambda functions.
The Datadog Lambda Extension
The Lambda Extension is installed as an AWS Lambda layer for your functions. Lambda layers are an AWS feature that allow you to separate your function code from its dependencies. A layer is a .zip file archive that contains supplementary code or data, such as library dependencies, custom runtimes, or configuration files.
Once installed, the Lambda Extension collects and sends data from your Lambda function to Datadog, including:
- Logs
- Traces
- Functional-level metrics
The Datadog Lambda Library
The Datadog Lambda Library can help us to to capture distributed traces and enrich your Lambda data.
- Implementation of the Lambda Library varies by runtime. For example, for .NET and Java, the Lambda Library is built into the tracer, while Node.js, Python, and Go use separate libraries. You can find detailed instructions for your runtime in the documentation.
Step by Step Approach for AWS Lambda Python integration with data dog
https://dev.to/aws-builders/aws-lambda-in-python-with-datadog-integration-4675
Step by Step Approach for AWS Lambda C#.Net integration with data dog
https://dev.to/srinivasuluparanduru/aws-lambda-in-c-with-datadog-integration-5egb
References :
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Added Step by Step Approach for AWS Lambda Python integration with data dog blog link to my main blog
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