The Datadog AWS Lambda Library
Datadog Lambda Library for Python (3.8, 3.9, 3.10, 3.11, and 3.12) enables enhanced Lambda metrics, distributed tracing, and custom metric submission from AWS Lambda functions.
Follow the installation instructions, and view your function's enhanced metrics, traces and logs in Datadog.
Follow the configuration instructions to tag your telemetry, capture request/response payloads, filter or scrub sensitive information from logs or traces, and more.
For additional tracing configuration options, check out the official documentation for Datadog trace client.
Besides the environment variables supported by dd-trace-py, the datadog-lambda-python library added following environment variables.
Environment Variables | Description | Default Value |
---|---|---|
DD_ENCODE_AUTHORIZER_CONTEXT | When set to true for Lambda authorizers, the tracing context will be encoded into the response for propagation. Supported for NodeJS and Python. |
true |
DD_DECODE_AUTHORIZER_CONTEXT | When set to true for Lambdas that are authorized via Lambda authorizers, it will parse and use the encoded tracing context (if found). Supported for NodeJS and Python. |
true |
DD_COLD_START_TRACING | Set to false to disable Cold Start Tracing. Used in NodeJS and Python. |
true |
DD_MIN_COLD_START_DURATION | Sets the minimum duration (in milliseconds) for a module load event to be traced via Cold Start Tracing. Number. | 3 |
DD_COLD_START_TRACE_SKIP_LIB | optionally skip creating Cold Start Spans for a comma-separated list of libraries. Useful to limit depth or skip known libraries. | ddtrace.internal.compat,ddtrace.filters |
DD_CAPTURE_LAMBDA_PAYLOAD | Captures incoming and outgoing AWS Lambda payloads in the Datadog APM spans for Lambda invocations. | false |
DD_CAPTURE_LAMBDA_PAYLOAD_MAX_DEPTH | Determines the level of detail captured from AWS Lambda payloads, which are then assigned as tags for the aws.lambda span. It specifies the nesting depth of the JSON payload structure to process. Once the specified maximum depth is reached, the tag's value is set to the stringified value of any nested elements beyond this level. For example, given the input payload: {If the depth is set to 2 , the resulting tag's key is set to function.request.lv1.lv2 and the value is {\"lv3\": \"val\"} . If the depth is set to 0 , the resulting tag's key is set to function.request and value is {\"lv1\":{\"lv2\":{\"lv3\": \"val\"}}} |
10 |
If you encounter a bug with this package, we want to hear about it. Before opening a new issue, search the existing issues to avoid duplicates.
When opening an issue, include the Datadog Lambda Library version, Python version, and stack trace if available. In addition, include the steps to reproduce when appropriate.
You can also open an issue for a feature request.
Datadog's Continuous Profiler is now available in beta for Python in version 4.62.0 and layer version 62 and above. This optional feature is enabled by setting the DD_PROFILING_ENABLED
environment variable to true
. During the beta period, profiling is available at no additional cost.
The Continuous Profiler works by spawning a thread which periodically wakes up and takes a snapshot of the CPU and Heap of all running python code. This can include the profiler itself. If you want the Profiler to ignore itself, set DD_PROFILING_IGNORE_PROFILER
to true
.
dd-trace
upgraded from 0.61 to 1.4, full release notes are available here
get_correlation_ids()
has been changed to get_log_correlation_context()
, which now returns a dictionary containing the active span_id
, trace_id
, as well as service
and env
.If you find an issue with this package and have a fix, please feel free to open a pull request following the procedures.
For product feedback and questions, join the #serverless
channel in the Datadog community on Slack.
Unless explicitly stated otherwise all files in this repository are licensed under the Apache License Version 2.0.
This product includes software developed at Datadog (https://www.datadoghq.com/). Copyright 2019 Datadog, Inc.