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⚡️ Sentry/Raven SDK Integration For AWS Lambda (python) and Serverless

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This library simplifies integration of Sentry's raven-python library with AWS Lambda. The only supported platforms are Python 2.7 and Python 3.6.

What is Raven and Sentry?

It's a bit confusing, but Raven is the official name of the error reporting SDK that will forward errors, exceptions and messages to the Sentry server. For more details of what Raven and Sentry actually is, refer to the official Sentry documentation:


  • Easy to use.
  • Integrates with Serverless Framework for AWS Lambda (though use of the framework is not required).
  • Wraps your Python code with Sentry error capturing.
  • Forwards any errors returned by your AWS Lambda function to Sentry.
  • Warn if your code is about to hit the execution timeout limit.
  • Warn if your Lambda function is low on memory.
  • Catches and reports unhandled exceptions.
  • Serverless, Sentry and as well as this library are all Open Source. Yay! 🎉


  • Install the raven-python-lambda module from pip:
    pip install raven-python-lambda
  • or install the raven-python-lambda locally:
    pip install -e .
  • Check out the examples below how to integrate it with your project by updating serverless.yml as well as your Lambda handler code.

Use as Standalone Library

If you don't want to add another plugin to Serverless, you can use this library standalone without additional dependencies (besides raven itself).

You will need to extend your serverless.yml to include additional environment variables. The only required environment variable is SENTRY_DSN to set the DSN url for your reporting. A full list of available environment variables is available below.

service: my-serverless-project
  # ...
    SENTRY_ENVIRONMENT: ${opt:stage, self:provider.stage} # recommended
    SENTRY_DSN: # URL provided by Sentry

Use Together With the Serverless Sentry Plugin

The Serverless Sentry Plugin allows configuration of the library through the serverless.yml. This is the recommended way of using the serverless-sentry-lib library.

Instead of manually setting environment variables the plugin determines and sets them automatically. In the serverless.yml simply load the plugin and set the dsn configuration option as follows:

service: my-serverless-project
  # ...
    dsn: # URL provided by Sentry

You can still manually set environment variables on a per-function level to overwrite the plugin's ones.

Environment Variables

Logging tags can be controlled through the following environment variables. You can set them manually in your serverless.yml or let them be configured automatically using the Serverless Sentry Plugin during deployment.

Environment Variable Description
SENTRY_ENVIRONMENT Environment (optional, e.g. "dev" or "prod")
SENTRY_RELEASE Release number of your project (optional)
SENTRY_AUTO_BREADCRUMBS Automatically create breadcrumbs (see Sentry Raven docs, default to true)
SENTRY_FILTER_LOCAL Don't report errors from local environments (defaults to true)
SENTRY_CAPTURE_ERRORS Enable capture Lambda errors (defaults to true)
SENTRY_CAPTURE_UNHANDLED Enable capture unhandled exceptions (defaults to true)
SENTRY_CAPTURE_MEMORY Enable monitoring memory usage (defaults to true)
SENTRY_CAPTURE_TIMEOUTS Enable monitoring execution timeouts (defaults to true)
SENTRY_CAPTURE_LOGS Enable capture log messages (defaults to true)
SENTRY_LOG_LEVEL Capture logs in sentry starting at this level (defaults to logging.WARNING)
SENTRY_TIMEOUT_THRESHOLD Set the percent threshold to trigger timeout warning (defaults to 0.50)
SENTRY_MEMORY_THRESHOLD Set the percent threshold to trigger memory usage warning (defaults to 0.75)

In addition the library checks for the following optional variables and adds them as custom tags automatically:

Environment Variable Sentry Tag Description
SERVERLESS_SERVICE service_name Serveless service name
SERVERLESS_STAGE stage Serverless stage
SERVERLESS_ALIAS alias Serverless alias, see Serverless AWS Alias Plugin
SERVERLESS_REGION region Serverless region name


For maximum flexibility this library is implemented as a decorated around your original AWS Lambda handler code (your def handler() or similar). The RavenLambdaWrapper adds error and exception handling, and takes care of configuring the Raven client automatically.

The RavenLambdaWrapper is pre-configured to reasonable defaults and doesn't need much setup. Simply pass in your configuration. Passing in your own Raven client is necessary to ensure that the wrapper uses the same environment as the rest of your code. In the rare circumstances that this isn't desired, you can pass in null instead.

Original Lambda Handler Code Before Adding RavenLambdaWrapper:

def handler(event, context):
    print("Go Serverless! Your function executed successfully")

New Lambda Handler Code With RavenLambdaWrapper For Sentry Reporting

from raven import Client # Offical `raven` module
from raven_python_lambda import RavenLambdaWrapper

def handler(event, context):
    print("Go Serverless! Your function executed successfully")

Once your Lambda handler code is wrapped in the RavenLambdaWrapper, it will be extended it with automatic error reporting. Whenever your Lambda handler sets an error response, the error is forwarded to Sentry with additional context information.

Setting Custom Configuration Options

As shown above you can use environment variables to control the Sentry integration. In some scenarios in which environment variables are not desired or in which custom logic needs to be executed, you can also pass in configuration options to the RavenLambdaWrapper directly:

  • raven_client - Your Raven client. Don't forget to set this if you send your own custom messages and exceptions to Sentry later in your code.
  • auto_breadcrumbs - Automatically create breadcrumbs (see Sentry Raven docs, defaults to true)
  • filter_local - don't report errors from local environments (defaults to true)
  • capture_errors - capture Lambda errors (defaults to true)
  • capture_unhandled_rejections - capture unhandled exceptions (defaults to true)
  • capture_memory_warnings - monitor memory usage (defaults to true)
  • capture_timeout_warnings - monitor execution timeouts (defaults to true)
from raven import Client # Offical `raven` module
from raven_python_lambda import RavenLambdaWrapper

raven_config = {
  'capture_errors': False,
  'capture_unhandled_rejections': True,
  'capture_memory_warnings': True,
  'capture_timeout_warnings': True,
  'raven_client': client

def handler(event, context):
    print("Go Serverless! Your function executed successfully")

Accessing the Raven Client for Capturing Custom Messages and Exceptions

If you want to capture a message or exception from anywhere in your code, simply use the Raven client as usual. It is a singleton instance and doesn't need to be configured again:

from raven import Client # Offical `raven` module
client.captureMessage("Hello from Lambda!", level="info ")

For further documentation on how to use it to capture your own messages refer to

Capturing Unhandled Exceptions

Typically, if your Lambda code throws an unhandled exception somewhere in the code, the invocation is immediately aborted and the function exits with a "Process exited before completing request". The plugin captures these unhandled exceptions, forwards them to Sentry and returns the exception like any regular error generated by your function.

Local Development

By default the library will not forward errors is if either the IS_OFFLINE or IS_LOCAL environment variable is set. If you want to change this behavior set the filter_local config option to False.

Detecting Slow Running Code

It's a good practice to specify the function timeout in serverless.yml to be at last twice as large as the expected maximum execution time. If you specify a timeout of 6 seconds (the default), this plugin will warn you if the function runs for 3 or more seconds. That means it's time to either review your code for possible performance improvements or increase the timeout value slightly.

Low Memory Warnings

The plugin will automatically generate a warning if the memory consumption of your Lambda function crosses 75% of the allocated memory limit. The plugin samples the amount of memory used by Python every 500 milliseconds (using psutil.Process(os.getpid()).memory_info().rss ), independently of any garbage collection.

Only one low memory warning will be generated per function invocation. You might want to increase the memory limit step by step until your code runs without warnings.

Turn Sentry Reporting On/Off

Obviously Sentry reporting is only enabled if you wrap your code using the RavenLambdaWrapper as shown in the examples above. In addition, error reporting is only active if the SENTRY_DSN environment variable is set. This is an easy way to enable or disable reporting as a whole or for specific functions.

In some cases it might be desirable to disable only error reporting itself but keep the advanced features such as timeout and low memory warnings in place. This can be achieved via setting the respective options in the environment variables or the RavenLambdaWrapper during initialization:

from raven import Client # Offical `raven` module
from raven_python_lambda import RavenLambdaWrapper

raven_config = {
  'capture_errors': False,  # Don't log error responses from the Lambda ...
  'capture_unhandled_rejections': True,  # keep unhandled exception logging
  'capture_memory_warnings': True,  # memory warnings
  'capture_timeout_warnings': True,  # timeout warnings
  'raven_client': client

def handler(event, context):
    print("Go Serverless! Your function executed successfully")

SQS Proxying

This also supports the ability to forward all Sentry messages to an SQS queue. This is meant to be used in conjunction with the raven-sqs-proxy (polls SQS and then passes the message on to Sentry).

Why is this useful? If you don't have the ability of running AWS Lambda functions within a VPC, then then this plugin is necessary.

Some reasons for why you would not want or need to run a lambda function within VPC are:

  • An AWS account doesn't have a useful VPC (special purpose accounts)
  • An AWS account doesn't have a VPC that is peered to a VPC where Sentry is running
  • Cross-region use cases where Sentry lives in an internal VPC without external connectivity
  • ENI Exhaustion Concerns: It is possible to exhaust the ENIs within a VPC if you have many, many lambdas running. This can break new deployments within a VPC.

What is required for SQS

For this to work, you will need:

  1. An SQS queue
  2. A lambda function launched with an IAM role with the following permissions to the SQS queue:
  3. A DSN that with the following parameters to the URL:
    sqs_region - The AWS region name for where the SQS queue resides
    sqs_account - This is the 12 digit AWS account number
    sqs_name - The name of the SQS queue
    • An example: https://user:pass@some-sentry-server?sqs_region=us-west-2&sqs_account=111111111111sqs_name=sentry-queue
  4. The proxying service enabled and running. Please review the documentation on the raven-sqs-proxy page for details.


Big thanks to arabold and as they were the inspiration for this work.

Version History


Sentry/Raven SDK Integration For AWS Lambda (python) and Serverless





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