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.
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: https://docs.sentry.io/.
- 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.
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
provider:
# ...
environment:
SENTRY_ENVIRONMENT: ${opt:stage, self:provider.stage} # recommended
SENTRY_DSN: https://xxxx:[email protected]/zzzz # URL provided by Sentry
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
provider:
# ...
plugins:
serverless-sentry
custom:
sentry:
dsn: https://xxxx:[email protected]/zzzz # URL provided by Sentry
You can still manually set environment variables on a per-function level to overwrite the plugin's ones.
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_DSN |
Sentry DSN Url |
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
@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.
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 totrue
)filter_local
- don't report errors from local environments (defaults totrue
)capture_errors
- capture Lambda errors (defaults totrue
)capture_unhandled_rejections
- capture unhandled exceptions (defaults totrue
)capture_memory_warnings
- monitor memory usage (defaults totrue
)capture_timeout_warnings
- monitor execution timeouts (defaults totrue
)
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
}
@RavenLambdaWrapper(raven_config)
def handler(event, context):
print("Go Serverless! Your function executed successfully")
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 docs.getsentry.com.
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.
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
.
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.
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.
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
}
@RavenLambdaWrapper(raven_config)
def handler(event, context):
print("Go Serverless! Your function executed successfully")
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.
For this to work, you will need:
- An SQS queue
- A lambda function launched with an IAM role with the following permissions to the SQS queue:
sqs:GetQueueUrl sqs:SendMessage
- 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
- An example:
- The proxying service enabled and running. Please review the documentation on the raven-sqs-proxy page for details.
Big thanks to arabold and https://github.com/arabold/serverless-sentry-plugin as they were the inspiration for this work.