Skip to main content

The Datadog AWS Lambda Library

Project description

datadog-lambda-python

build PyPI PyPI - Python Version Slack License

Datadog Lambda Library for Python (3.6, 3.7, 3.8, and 3.9) enables enhanced Lambda metrics, distributed tracing, and custom metric submission from AWS Lambda functions.

Installation

Follow the installation instructions, and view your function's enhanced metrics, traces and logs in Datadog.

For advanced distributed tracing use cases, check out the official documentation for Datadog APM client.

To connect traces and logs using a custom logger, see connecting logs and traces.

Environment Variables

DD_API_KEY

If you are using the Datadog Lambda Extension, the Datadog API Key must be defined by setting one of the following environment variables:

  • DD_API_KEY - the Datadog API Key in plain-text, NOT recommended
  • DD_KMS_API_KEY - the KMS-encrypted API Key, requires the kms:Decrypt permission
  • DD_API_KEY_SECRET_ARN - the Secret ARN to fetch API Key from the Secrets Manager, requires the secretsmanager:GetSecretValue permission (and kms:Decrypt if using a customer managed CMK)

If you are using the Datadog Forwarder, you must set the Datadog API Key on the Datadog Forwarder instead of your own Lambda function.

DD_SITE

If you are using the Datadog Lambda Extension, you must set DD_SITE on your Lambda function based on your Datadog site. The default is datadoghq.com.

If you are using the Datadog Forwarder, you must set this on the Datadog Forwarder instead of your own Lambda function.

DD_LOGS_INJECTION

Inject Datadog trace id into logs for correlation if you are using a logging.Formatter in the default LambdaLoggerHandler by the Lambda runtime. Defaults to true.

DD_LOG_LEVEL

Set to debug enable debug logs from the Datadog Lambda Library. Defaults to info.

DD_ENHANCED_METRICS

Generate enhanced Datadog Lambda integration metrics, such as, aws.lambda.enhanced.invocations and aws.lambda.enhanced.errors. Defaults to true.

DD_LAMBDA_HANDLER

In order to instrument individual invocations, the Datadog Lambda library needs to wrap around your Lambda handler function. This is usually achieved by setting your function's handler to the Datadog handler function (datadog_lambda.handler.handler) and setting the environment variable DD_LAMBDA_HANDLER with your original handler function to be called by the Datadog handler.

For some advanced use cases, instead of overriding the handler setting and the DD_LAMBDA_HANDLER environment variable, you can apply the Datadog Lambda library wrapper in your function code like below:

from datadog_lambda.wrapper import datadog_lambda_wrapper

@datadog_lambda_wrapper
def my_lambda_handle(event, context):
    # your function code

DD_TRACE_ENABLED

Initialize the Datadog tracer when set to true. Defaults to false.

DD_MERGE_XRAY_TRACES

Set to true to merge the X-Ray trace and the Datadog trace, when using both the X-Ray and Datadog tracing. Defaults to false.

DD_TRACE_MANAGED_SERVICES (experimental)

Inferred Spans are spans that Datadog can create based on incoming event metadata. Set DD_TRACE_MANAGED_SERVICES to true to infer spans based on Lambda events. Inferring upstream spans is only supported if you are using the Datadog Lambda Extension. Defaults to true. Infers spans for:

  • API Gateway REST events
  • API Gateway WebSocket events
  • HTTP API events
  • SQS
  • SNS (SNS messaged delivered via SQS are also supported)
  • Kinesis Streams (if data is a JSON string or base64 encoded JSON string)
  • EventBridge (custom events, where Details is a JSON string)
  • S3
  • DynamoDB

DD_FLUSH_TO_LOG (Deprecated)

When the Datadog Forwarder was launched previously, DD_FLUSH_TO_LOG was introduced to control whether to send custom metrics synchronously from your own Lambda function directly to Datadog with added latency (set DD_FLUSH_TO_LOG to false and you also need to set DD_API_KEY and DD_SITE) or asynchronously through CloudWatch logs (set DD_FLUSH_TO_LOG to true).

Now you should consider adopting the Datadog Lambda Extension for sending custom metrics. When the Datadog Lambda Extension is installed and detected, DD_FLUSH_TO_LOG is ignored. If you wish to Defaults to false. If set to false, you also need to set DD_API_KEY and DD_SITE.

Opening Issues

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.

Contributing

If you find an issue with this package and have a fix, please feel free to open a pull request following the procedures.

Community

For product feedback and questions, join the #serverless channel in the Datadog community on Slack.

License

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.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

datadog_lambda-3.57.0.tar.gz (32.2 kB view hashes)

Uploaded Source

Built Distribution

datadog_lambda-3.57.0-py3-none-any.whl (36.1 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page