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www/src/content/blog/2024-12-03-cf-service-bindings.mdx
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--- | ||
title: "Introducing Tracing for Cloudflare Service Bindings with Fiberplane" | ||
description: "Learn how Fiberplane's instrumentation client now supports tracing Cloudflare Service Bindings" | ||
slug: introducing-tracing-for-cloudflare-service-bindings-with-fiberplane | ||
date: 2024-12-03 | ||
author: Nele Uhlemann | ||
tags: | ||
- cloudflare | ||
- typescript | ||
- launch week | ||
- services architecture | ||
--- | ||
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import { Aside, LinkCard } from "@astrojs/starlight/components"; | ||
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Today, we are excited to announce a new feature in [Fiberplane's instrumentation client](https://fiberplane.com/docs/components/client-library/): support for tracing [Cloudflare Service Bindings](https://developers.cloudflare.com/workers/runtime-apis/bindings/service-bindings/). | ||
Service bindings allow for Worker-to-Worker communication, and tracing them enables better visibility and debugging for distributed systems built on Cloudflare. | ||
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## Cloudflare Service Bindings | ||
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Cloudflare Workers can invoke other Cloudflare Workers in the same network, facilitating the creation of distributed architectures on Cloudflare. | ||
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Workers Service Bindings allow for multiple Workers to utilize another Worker's functionality, like authenticating requests or sending emails. | ||
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Decomposing your logic into multiple Workers can therefore reduce code duplication, simplify maintenance, and streamline updates to core parts of your system. | ||
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Additionally, when you rely on Service Bindings, certain Workers can remain completely unexposed to the public internet, which gives your application an nice added layer of security. | ||
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### Simple example use case | ||
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Imagine you want to organize a marathon event. To allow athletes to register, you provide a sign-up form on your website. | ||
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When an athlete submits the form, their data is stored in a database. An email is then sent to confirm their registration. | ||
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Separately, and not as part of the registration process, you offer a newsletter subscription. | ||
When an athlete subscribes to the newsletter, their email address is stored in a different database, and they receive a welcome email. | ||
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In this scenario, you could have three workers: one for handling the sign-up form, another for managing the newsletter subscription, and then a _shared_ email worker to send emails. | ||
![Example Workers architecture](@/assets/blog/2024-12-03-workers-example-architecture.png) | ||
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### How it works | ||
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When one Cloudflare Worker invokes another, the calls remain within the same execution thread. | ||
This design ensures that breaking down service logic into multiple Workers does not introduce network latency, making the architecture both flexible and high-performance. | ||
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There are two primary ways Workers can communicate using Service Bindings: | ||
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- RPC | ||
- HTTP | ||
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Bindings are configured in the `wrangler.toml` file. If you want to learn more about setting up Service Bindings, check out the [Cloudflare documentation](https://developers.cloudflare.com/workers/runtime-apis/bindings/service-bindings/). | ||
Since the calls occur in the same thread, it’s important to handle them asynchronously. | ||
Otherwise, Worker A might terminate the thread before Worker B has completed its operation. Here is a simple example using rpc: | ||
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```typescript | ||
await c.env.WORKER_EMAIL.send(email, firstName); | ||
``` | ||
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If the Service Binding is defined in the `wrangler.toml` file, the Worker can invoke another Worker’s function by using the binding name and the appropriate function from the other Worker. | ||
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## Developing with multiple Workers | ||
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As service distribution increases, so does the complexity of observing and debugging a system. | ||
Tracing the full call chain of a request becomes critical to understanding performance and error handling. | ||
This is particularly important when dealing with asynchronous background tasks executed by other Workers. | ||
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Observing and measuring response times is already an important aspect of local development. | ||
It helps you understand your application’s performance and identify bottlenecks. | ||
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## Example with Fiberplane | ||
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Let’s explore how Fiberplane’s instrumentation client can help trace requests between Cloudflare Workers. | ||
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In this example, we use Fiberplane's client to instrument the sign-up Worker, which stores user data in a database and invokes the email Worker to send a confirmation email. | ||
With Fiberplane, you can visualize the entire call chain of this request. | ||
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![Sequential Trace](@/assets/blog/2024-12-03-workers-binding-sequential.png) | ||
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In the trace above, we see a sequential execution model where the sign-up Worker first performs database operations and then invokes the email Worker. | ||
The total execution time depends on the entire call chain, as shown below. | ||
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We can improve the response time by using parallel execution with `waitUntil()`. | ||
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```typescript | ||
app.post("/api/marathon-wait-until", async (c) => { | ||
const { firstName, lastName, email, address, distance } = await c.req.json(); | ||
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//using waitUntil() and invoke email worker via rpc | ||
c.executionCtx.waitUntil(c.env.WORKER_EMAIL.send(email, firstName)); | ||
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await insertData( | ||
firstName, | ||
lastName, | ||
email, | ||
address, | ||
distance, | ||
c.env.DATABASE_URL | ||
); | ||
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return c.text("Thanks for registering for our Marathon", 200); | ||
}); | ||
``` | ||
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Using Fiberplane, we can also visualize the improved execution model: | ||
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![WaitUntil() Trace](@/assets/blog/2024-12-03-workers-binding-waituntil.png) | ||
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By adopting `waitUntil()` for parallel execution, you can reduce user-facing latency while ensuring that background operations are completed efficiently. | ||
Tracing across multiple Workers is therefore important to understand dependencies and visualize the total lifecycle of the thread. | ||
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Additionally, Fiberplane's studio provides detailed information about the Service Binding: | ||
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![Binding information](@/assets/blog/2024-12-03-workers-binding-information.png) | ||
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This new feature in Fiberplane's instrumentation client simplifies tracing between Cloudflare Workers, offering developers better visibility and control over distributed architectures. | ||
Explore the [example code](https://github.com/Nlea/cloudflare-handling-asynchronous-tasks-/tree/seperate-workers/seperate-workers) and start tracing your Cloudflare Workers today! |
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