Azure Functions
Learn how to manually set up Sentry in your Azure Functions and capture your first errors.
You need:
Choose the features you want to configure, and this guide will show you how:
Run the command for your preferred package manager to add @sentry/node as a runtime dependency to your application:
npm install @sentry/node --save
npm install @sentry/node @sentry/profiling-node --save
Make sure to initialize Sentry at the top of your function file before importing any other modules:
const Sentry = require("@sentry/node");
// ___PRODUCT_OPTION_START___ profiling
const { nodeProfilingIntegration } = require("@sentry/profiling-node");
// ___PRODUCT_OPTION_END___ profiling
Sentry.init({
dsn: "___PUBLIC_DSN___",
// Adds request headers and IP for users, for more info visit:
// https://docs.sentry.io/platforms/javascript/guides/azure-functions/configuration/options/#sendDefaultPii
sendDefaultPii: true,
// ___PRODUCT_OPTION_START___ profiling
integrations: [nodeProfilingIntegration()],
// ___PRODUCT_OPTION_END___ profiling
// ___PRODUCT_OPTION_START___ performance
// Add Performance Monitoring by setting tracesSampleRate
// Set tracesSampleRate to 1.0 to capture 100% of transactions
// We recommend adjusting this value in production
// Learn more at
// https://docs.sentry.io/platforms/javascript/configuration/options/#traces-sample-rate
tracesSampleRate: 1.0,
// ___PRODUCT_OPTION_END___ performance
// ___PRODUCT_OPTION_START___ profiling
// Enable profiling for a percentage of sessions
// Learn more at
// https://docs.sentry.io/platforms/javascript/configuration/options/#profileSessionSampleRate
profileSessionSampleRate: 1.0,
// ___PRODUCT_OPTION_END___ profiling
// ___PRODUCT_OPTION_START___ logs
// Enable logs to be sent to Sentry
enableLogs: true,
// ___PRODUCT_OPTION_END___ logs
});
// your function code
Because Azure Functions are short-lived, you have to explicitly flush Sentry events after calling captureException, or they may be lost before being sent to Sentry.
const Sentry = require("@sentry/node");
// your Sentry init code
module.exports = async function (context, req) {
try {
// Your function code
} catch (e) {
// use Sentry.withScope to enrich the event with request data
Sentry.withScope((scope) => {
// Attach request context (requires sendDefaultPii: true)
scope.setSDKProcessingMetadata({ request: req });
Sentry.captureException(e);
});
await Sentry.flush(2000);
}
// ...
};
The stack traces in your Sentry errors probably won't look like your actual code without unminifying them. To fix this, upload your source maps to Sentry. The easiest way to do this is by using the Sentry Wizard:
npx @sentry/wizard@latest -i sourcemaps
Let's test your setup and confirm that Sentry is working correctly and sending data to your Sentry project.
First, let's verify that Sentry captures errors and creates issues in your Sentry project. Add an intentional error in your function:
const Sentry = require("@sentry/node");
module.exports = async function (context, req) {
try {
// This function does not exist, triggering an error
await notExistFunction();
} catch (e) {
Sentry.withScope((scope) => {
scope.setSDKProcessingMetadata({ request: req });
Sentry.captureException(e);
});
}
// Wait for the event to be sent before the function execution ends
await Sentry.flush(2000);
context.res = {
status: 500,
body: "Test error sent to Sentry.",
};
};
Deploy and trigger your function to throw an error.
To test tracing, update your function to include a custom span:
const Sentry = require("@sentry/node");
module.exports = async function (context, req) {
await Sentry.startSpan(
{ name: "My Custom Span", op: "task" },
async () => {
// Simulate some work
await new Promise((resolve) => setTimeout(resolve, 100));
},
);
// Wait for the event to be sent before the function execution ends
await Sentry.flush(2000);
context.res = {
status: 200,
body: "Hello world!",
};
};
Deploy and trigger your function to start a child span.
Now, head over to your project on Sentry.io to view the collected data (it takes a couple of moments for the data to appear).
At this point, you should have integrated Sentry into your Azure Function and should already be sending data to your Sentry project.
Now's a good time to customize your setup and look into more advanced topics. Our next recommended steps for you are:
- Explore practical guides on what to monitor, log, track, and investigate after setup
- Continue to customize your configuration
- Learn how to manually capture errors
- Get familiar with Sentry's product features like tracing, insights, and alerts
Our documentation is open source and available on GitHub. Your contributions are welcome, whether fixing a typo (drat!) or suggesting an update ("yeah, this would be better").