Cloudflare Quick Start for Flue

Install

Choose the features you want to configure, and this guide will show you how:

Install the Sentry Cloudflare SDK:

npm install @sentry/cloudflare@^11.0.0

npm install @sentry/cloudflare@^11.0.0

yarn add @sentry/cloudflare@^11.0.0

pnpm add @sentry/cloudflare@^11.0.0

Configure

Add the Sentry Vite plugin to your Vite config, after Flue's:

import { cloudflare } from "@cloudflare/vite-plugin";
import { flue, flueWorkerConfig } from "@flue/vite";
import { sentryCloudflareVitePlugin } from "@sentry/cloudflare/vite";
import { defineConfig } from "vite";

export default defineConfig({
  plugins: [
    flue(),
    cloudflare({ config: flueWorkerConfig() }),
    sentryCloudflareVitePlugin(),
  ],
});

import { cloudflare } from "@cloudflare/vite-plugin";
import { flue, flueWorkerConfig } from "@flue/vite";
import { sentryCloudflareVitePlugin } from "@sentry/cloudflare/vite";
import { defineConfig } from "vite";

export default defineConfig({
  plugins: [
    flue(),
    cloudflare({ config: flueWorkerConfig() }),
    sentryCloudflareVitePlugin(),
  ],
});

The plugin registers the Flue instrumentation for you at build time, so you don't write an instrument() call as you do on Node.js. It instruments the other libraries your tools call at the same point, so their spans land in the agent's trace.

Each Flue agent runs in its own Durable Object, which is a separate isolate from your Worker entry. Sentry.init() has to run inside it, so create a module that wraps the generated agent Durable Object:

import { extend } from "@flue/runtime/cloudflare";
import * as Sentry from "@sentry/cloudflare";

export const cloudflare = extend({
  wrap: (Final) =>
    Sentry.instrumentDurableObjectWithSentry(
      (env: Env) => ({
        dsn: "___PUBLIC_DSN___",
        // ___PRODUCT_OPTION_START___ performance

        // Set tracesSampleRate to 1.0 to capture 100%
        // of spans for tracing.
        // We recommend adjusting this value in production.
        tracesSampleRate: 1.0,
        // ___PRODUCT_OPTION_END___ performance
      }),
      Final,
    ),
});

import { extend } from "@flue/runtime/cloudflare";
import * as Sentry from "@sentry/cloudflare";

export const cloudflare = extend({
  wrap: (Final) =>
    Sentry.instrumentDurableObjectWithSentry(
      (env: Env) => ({
        dsn: "___PUBLIC_DSN___",
        // ___PRODUCT_OPTION_START___ performance

        // Set tracesSampleRate to 1.0 to capture 100%
        // of spans for tracing.
        // We recommend adjusting this value in production.
        tracesSampleRate: 1.0,
        // ___PRODUCT_OPTION_END___ performance
      }),
      Final,
    ),
});

Re-export it as cloudflare from each agent module. This is how Flue applies the wrapper — defining it anywhere else has no effect:

export { cloudflare } from "../sentry.ts";

export { cloudflare } from "../sentry.ts";

Enable Node.js compatibility in your Wrangler config so the SDK can run on Workers:

{
  "compatibility_flags": ["nodejs_compat"]
}

{
  "compatibility_flags": ["nodejs_compat"]
}

With this setup, Sentry captures errors thrown by your agents and tools, and AI spans for every run (agent turns, model calls, tool executions, token usage, and latency). Manual spans you start inside a tool nest under that tool's span.

To review what's captured and turn recording of prompts and responses off, see Privacy Controls below.

Privacy Controls

The SDK will record generative AI inputs and outputs (the prompts your agent sends and the model responses it receives) by default. To turn recording off, set genAI.inputs and genAI.outputs to false in dataCollection:

Sentry.instrumentDurableObjectWithSentry(
  (env: Env) => ({
    dsn: "___PUBLIC_DSN___",
    dataCollection: {
      genAI: { inputs: false, outputs: false },
    },
  }),
  Final,
);

Sentry.instrumentDurableObjectWithSentry(
  (env: Env) => ({
    dsn: "___PUBLIC_DSN___",
    dataCollection: {
      genAI: { inputs: false, outputs: false },
    },
  }),
  Final,
);

See dataCollection documentation for details on privacy control options.

Link Conversations

Sentry groups a multi-turn chat into a single Conversation automatically — there's no Sentry-specific setup. Flue already tracks a conversation id per conversation, and the SDK maps it to gen_ai.conversation.id on the agent, model, and tool spans of every turn.

The agent span also carries gen_ai.agent.name, so you can tell a lead agent's runs from its subagents'.

Verify

Send a message to one of your agents, then open Explore → Agents in Sentry. Select the conversation to open its detail. The timeline shows the agent turn, model calls, tool executions, token usage, latency, and any errors your tools threw.

If no data appears, confirm that:

• The dsn belongs to the Sentry project you're viewing.
• tracesSampleRate is greater than 0.
• Your agent completed at least one turn after you added the setup.