Serverless Error and Performance Monitoring

Using Sentry for Serverless makes debugging as painless as possible, so you can keep everything up and running.

Getting Started is Simple

Add @sentry/serverless as a dependency:

npm install --save @sentry/aws-serverless

Then set up the AWS Lambda integration:

const Sentry = require("@sentry/aws-serverless");

Sentry.init({
  dsn: 'https://<key>@sentry.io/<project>',
  tracesSampleRate: 1.0,
});

exports.handler = Sentry.wrapHandler(async (event, context) => {
  // Your handler code
});

Install our Python SDK using pip:

pip install --upgrade sentry-sdk

Then use the AWS Lambda integration for the Python SDK like this:

import sentry_sdk

sentry_sdk.init(
    dsn="https://<key>@sentry.io/<project>",
    integrations=[AwsLambdaIntegration()],
    traces_sample_rate=1.0, # adjust the sample rate in production as needed
)

def my_function(event, context):
    # ...

Add @sentry/serverless as a dependency to package.json:

"@sentry/serverless": "*"

Then set up Sentry error logging for a GCP Cloud Function:

const Sentry = require("@sentry/serverless");

Sentry.GCPFunction.init({
  dsn: "https://<key>@sentry.io/<project>",
  tracesSampleRate: 1.0,
});

exports.helloHttp = Sentry.GCPFunction.wrapHttpFunction((req, res) => {
  throw new Error('oh, hello there!');
});

Add the Sentry SDK to your requirements.txt:

pip install sentry-sdk

Then use the GCP Functions integration for the Python SDK like this:

import sentry_sdk
from sentry_sdk.integrations.gcp import GcpIntegration

sentry_sdk.init(
    dsn="https://<key>@sentry.io/<project>",
    integrations=[GcpIntegration()],
    traces_sample_rate=1.0, # adjust the sample rate in production as needed
)

def http_function_entrypoint(request):
    # ...

Add @sentry/node as a dependency:

npm install --save @sentry/node

Then set up Sentry error logging for an Azure Function:

"use strict";

const Sentry = require("@sentry/node");

Sentry.init({
  dsn: "https://<key>@sentry.io/<project>",
});

module.exports = async function(context, req) {
  try {
    await notExistFunction();
  } catch (e) {
    Sentry.captureException(e);
    await Sentry.flush(2000);
  }

  context.res = {
    status: 200,
    body: "Hello from Azure Cloud Function!",
  };
};

Add @sentry/cloudflare as a dependency:

npm install --save @sentry/cloudflare

Configure the nodejs_compat compatibility flag in your wrangler.json:

{
  "compatibility_flags": [
    "nodejs_compat"
  ],
  "compatibility_date": "2024-01-01"
}

Then add the Sentry middleware to your Cloudflare Pages functions:

import * as Sentry from "@sentry/cloudflare";

export const onRequest = [
  // Make sure Sentry is the first middleware
  Sentry.sentryPagesPlugin((context) => ({
    dsn: 'https://<key>@sentry.io/<project>',
    tracesSampleRate: 1.0,
  })),
  // Add more middlewares here
];

Add @sentry/cloudflare as a dependency:

npm install --save @sentry/cloudflare

Configure the nodejs_compat compatibility flag in your wrangler.json:

{
  "compatibility_flags": [
    "nodejs_compat"
  ],
  "compatibility_date": "2024-01-01"
}

Then wrap your handler with the withSentry function:

import * as Sentry from "@sentry/cloudflare";

export default Sentry.withSentry(
  (env) => ({
    dsn: 'https://<key>@sentry.io/<project>',
    tracesSampleRate: 1.0,
    enableLogs: true,
  }),
  {
    async fetch(request, env, ctx) {
      return new Response('Hello World!');
    },
  }
);

Add @sentry/node as a dependency:

npm install --save @sentry/node

Create an initialization file (e.g., init.ts) that runs before your functions:

import * as Sentry from '@sentry/node';

Sentry.init({
  dsn: 'https://<key>@sentry.io/<project>',
  tracesSampleRate: 1.0,
});

Import the initialization file at the top of your functions entry point:

import './init'; // Import Sentry initialization first

import { onRequest } from 'firebase-functions/https';
import { onDocumentCreated } from 'firebase-functions/firestore';
import * as admin from 'firebase-admin';

admin.initializeApp();
const db = admin.firestore();

// HTTP function - automatically instrumented
export const helloWorld = onRequest(async (request, response) => {
  response.send('Hello from Firebase!');
});

// Firestore trigger - automatically instrumented
export const onUserCreated = onDocumentCreated('users/{userId}', async (event) => {
  const userId = event.params.userId;
  // Your logic here
});

Check our documentation for the latest instructions.

See All Platforms

More than 150K Organizations Trust Sentry with Their Application Monitoring

Code-Level Visibility

View stack traces on issues, user-agent information, and all the metadata around an issue for all the context needed to resolve the issue.

Quickly Identify Function Latencies

Trace those ten-second page loads to poor-performing API calls and slow database queries. The event detail waterfall visually highlights what calls are giving your customers a poor experience.

Fill in the Gaps

See what happened leading up to the issue. Get function execution details including function metadata, execution time, Amazon Resource Name, and function identity.

FAQs

Sentry uses run-time instrumentation to capture errors. This allows users to get to the root of the problems using stack traces, breadcrumbs, function context and environment context.

CloudWatch/Stackdriver logs and metrics are hard to use to debug issues. The information is limited to some log statements and usually don't have the context needed to debug issues.

Sentry uses run-time instrumentation to get real time visibility into execution environment and report all relevant info to be able to quickly debug issues. For example source code visibility when issues occur.

CloudWatch or Stackdriver log forwarding requires parsing through logs and usually are limited to details that already exist in logs.

Sentry supports distributed tracing in addition to error monitoring for serverless functions.

You can get started for free. Pricing depends on the number of monthly events, transactions, and attachments that you send Sentry. For more details, visit our pricing page.

Supporting Resources

The Sentry Blog

Sentry Documentation

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