Tag Archives: D1

How we built an open-source SEO tool using Workers, D1, and Queues

Post Syndicated from Kristian Freeman original https://blog.cloudflare.com/how-we-built-an-open-source-seo-tool-using-workers-d1-and-queues/

How we built an open-source SEO tool using Workers, D1, and Queues

How we built an open-source SEO tool using Workers, D1, and Queues

Building applications on Cloudflare Workers has always been fun. Workers applications have low latency response times by default, and easy developer ergonomics thanks to Wrangler. It’s no surprise that for years now, developers have been going from idea to production with Workers in just a few minutes.

Internally, we’re no different. When a member of our team has a project idea, we often reach for Workers first, and not just for the MVP stage, but in production, too. Workers have been a secret ingredient to Cloudflare’s innovation for some time now, allowing us to build products like Access, Stream and Workers KV. Even better, when we have new ideas and we can use new Cloudflare products to build them, it’s a great way to give feedback on those products.

We’ve discussed this in the past on the Cloudflare blog – in May last year, I wrote how we rebuilt Cloudflare’s developer documentation using many of the tools that had recently been released in the Workers ecosystem: Cloudflare Pages for hosting, and Bulk Redirects for the redirect rules. In November, we released a new version of our API documentation, which again used Pages for hosting, and Pages functions for intelligent caching and transformation of our API schema.

In this blog post, I’m excited to show off some of the new tools in Cloudflare’s developer arsenal, D1 and Queues, to prototype and ship an internal tool for our SEO experts at Cloudflare. We’ve made this project, which we’re calling Prospector, open-source too – check it out in our cloudflare/templates repo on GitHub. Whether you’re a developer looking to understand how to use multiple parts of Cloudflare’s developer stack together, or an SEO specialist who may want to deploy the tool in production, we’ve made it incredibly easy to get up and running.

How we built an open-source SEO tool using Workers, D1, and Queues

What we’re building

Prospector is a tool that allows Cloudflare’s SEO experts to monitor our blog and marketing site for specific keywords. When a keyword is matched on a page, Prospector will notify an email address. This allows our SEO experts to stay informed of any changes to our website, and take action accordingly.

Using MailChannels’ integration with Workers, we can quickly and easily send emails from our application using a single API call. This allows us to focus on the core functionality of the application, and not worry about the details of sending emails.

Prospector uses Cloudflare Workers as the user-facing API for the application. It uses D1 to store and retrieve data in real-time, and Queues to handle the fetching of all URLs and the notification process. We’ve also included an intuitive user interface for the application, which is built with HTML, CSS, and JavaScript.

How we built an open-source SEO tool using Workers, D1, and Queues

Why we built it

It is widely known in SEO that both internal and external links help Google and other search engines understand what a website is about, which impacts keyword rankings. Not only do these links guide readers to additional helpful information, they also allow web crawlers for search engines to discover and index content on the site.

Acquiring external links is often a time-consuming process and at the discretion of third parties, whereas website owners typically have much more control over internal links. As a result, internal linking is one of the most useful levers available in SEO.

In an ideal world, every piece of content would be fully formed upon publication, replete with helpful internal links throughout the piece. However, this is often not the case. Many times, content is edited after the fact or additional pieces of relevant content come along after initial publication. These situations result in missed opportunities for internal linking.

Like other large organizations, Cloudflare has published thousands of blogs and web pages over the years. We share new content every time a product/technology is introduced and improved. Ultimately, that also means it’s become more challenging to identify opportunities for internal linking in a timely, automated fashion. We needed a tool that would allow us to identify internal linking opportunities as they appear, and speed up the time it takes to identify new internal linking opportunities.

Although we tested several tools that might solve this problem, we found that they were limited in several ways. First, some tools only scanned the first 2,000 characters of a web page. Any opportunities found beyond that limit would not be detected. Next, some tools did not allow us to limit searches to certain areas of the site and resulted in many false positives. Finally, other potential solutions required manual operation, leaving the process at the mercy of human memory.

To solve our problem (and ultimately, improve our SEO), we needed an automated tool that could discover and notify us of new instances of targeted phrases on a specified range of pages.

How it works

Data model

First, let’s explore the data model for Prospector. We have two main tables: notifiers and urls. The notifiers table stores the email address and keyword that we want to monitor. The urls table stores the URL and sitemap that we want to scrape. The notifiers table has a one-to-many relationship with the urls table, meaning that each notifier can have many URLs associated with it.

In addition, we have a sitemaps table that stores the sitemap URLs that we’ve scraped. Many larger websites don’t just have a single sitemap: the Cloudflare blog, for instance, has a primary sitemap that contains four sub-sitemaps. When the application is deployed, a primary sitemap is provided as configuration, and Prospector will parse it to find all of the sub-sitemaps.

Finally, notifier_matches is a table that stores the matches between a notifier and a URL. This allows us to keep track of which URLs have already been matched, and which ones still need to be processed. When a match has been found, the notifier_matches table is updated to reflect that, and “matches” for a keyword are no longer processed. This saves our SEO experts from a crowded inbox, and allows them to focus and act on new matches.

Connecting the pieces with Cloudflare Queues
Cloudflare Queues acts as the work queue for Prospector. When a new notifier is added, a new job is created for it and added to the queue. Behind the scenes, Queues will distribute the work across multiple Workers, allowing us to scale the application as needed. When a job is processed, Prospector will scrape the URL and check for matches. If a match is found, Prospector will send an email to the notifier’s email address.

Using the Cron Triggers functionality in Workers, we can schedule the scraping process to run at a regular interval – by default, once a day. This allows us to keep our data up-to-date, and ensures that we’re always notified of any changes to our website. It also allows the end-user to configure when they receive emails in case they want to receive them more or less frequently, or at the beginning of their workday.

The Module Workers syntax for Workers makes accessing the application bindings – the constants available in the application for querying D1, Queues, and other services – incredibly easy. src/index.ts, the entrypoint for the application, looks like this:

import { DBUrl, Env } from './types'

import {
} from './functions';

import h from './api'

export default {
  async fetch(
	request: Request,
	env: Env,
	ctx: ExecutionContext
  ): Promise<Response> {
	return h.fetch(request, env, ctx)

  async queue(
	batch: MessageBatch<Error>,
	env: Env
  ): Promise<void> {
	for (const message of batch.messages) {
  	const url: DBUrl = JSON.parse(message.body)
  	await handleQueuedUrl(url, env.DB)

  async scheduled(
	env: Env,
  ): Promise<void> {
	await scheduled({
  	authToken: env.AUTH_TOKEN,
  	db: env.DB,
  	queue: env.QUEUE,
  	sitemapUrl: env.SITEMAP_URL,

With this syntax, we can see where the various events incoming to the application – the fetch event, the queue event, and the scheduled event – are handled. The fetch event is the main entrypoint for the application, and is where we handle all of the API routes. The queue event is where we handle the work that’s been added to the queue, and the scheduled event is where we handle the scheduled scraping process.

Central to the application, of course, is Workers – acting as the API gateway and coordinator. We’ve elected to use the popular open-source framework Hono, an Express-style API for Workers, in Prospector. With Hono, we can quickly map out a REST API in just a few lines of code. Here’s an example of a few API routes and how they’re defined with Hono:

const app = new Hono()

app.get("/", (context) => {
  return context.html(index)

app.post("/notifiers", async context => {
  try {
	const { keyword, email } = await context.req.parseBody()
	await context.env.DB.prepare(
  	"insert into notifiers (keyword, email) values (?, ?)"
	).bind(keyword, email).run()
	return context.redirect('/')
  } catch (err) {
	return context.text("Something went wrong")

app.get('/sitemaps', async (context) => {
  const query = await context.env.DB.prepare(
	"select * from sitemaps"
  const sitemaps: Array<DBSitemap> = query.results
  return context.json(sitemaps)

Crucial to the development of Prospector are the improved TypeScript bindings for Workers. As announced in November of last year, TypeScript bindings for Workers are now automatically generated based on our open source runtime, workerd. This means that whenever we use the types provided from the @cloudflare/workers-types package in our application, we can be sure that the types are always up-to-date.

With these bindings, we can define the types for our environment variables, and use them in our application. Here’s an example of the Env type, which defines the environment variables that we use in the application:

export interface Env {
  AUTH_TOKEN: string
  DB: D1Database
  QUEUE: Queue
  SITEMAP_URL: string

Notice the types of the DB and QUEUE bindings – D1Database and Queue, respectively. These types are automatically generated, complete with type signatures for each method inside of the D1 and Queue APIs. This means that we can be sure that we’re using the correct methods, and that we’re passing the correct arguments to them, directly from our text editor – without having to refer to the documentation.

How we built an open-source SEO tool using Workers, D1, and Queues

How to use it

One of my favorite things about Workers is that deploying applications is quick and easy. Using `wrangler.toml` and some simple build scripts, we can deploy a fully-functional application in just a few minutes. Prospector is no different. With just a few commands, we can create the necessary D1 database and Queues instance, and deploy the application to our account.

First, you’ll need to clone the repository from our cloudflare/templates repository:

git clone $URL

If you haven’t installed wrangler yet, you can do so by running:

npm install @cloudflare/wrangler -g

With Wrangler installed, you can login to your account by running:

wrangler login

After you’ve done that, you’ll need to create a new D1 database, as well as a Queues instance. You can do this by running the following commands:

wrangler d1 create $DATABASE_NAME
wrangler queues create $QUEUE_NAME

Configure your wrangler.toml with the appropriate bindings (see [the README](URL) for an example):

[[ d1_databases ]]
binding = "DB"
database_name = "keyword-tracker-db"
database_id = "ab4828aa-723b-4a77-a3f2-a2e6a21c4f87"
preview_database_id = "8a77a074-8631-48ca-ba41-a00d0206de32"
  queue = "queue"
  binding = "QUEUE"

  queue = "queue"
  max_batch_size = 10
  max_batch_timeout = 30
  max_retries = 10
  dead_letter_queue = "queue-dlq"

Next, you can run the bin/migrate script to create the tables in your database:


This will create all the needed tables in your database, both in development (locally) and in production. Note that you’ll even see the creation of a honest-to-goodness .sqlite3 file in your project directory – this is the local development database, which you can connect to directly using the same SQLite CLI that you’re used to:

$ sqlite3 .wrangler/state/d1/DB.sqlite3
sqlite> .tables notifier_matches  notifiers     sitemaps       urls

Finally, you can deploy the application to your account:

npm run deploy

With a deployed application, you can visit your Workers URL to see the user interface. From there, you can add new notifiers and URLs, and see the results of your scraping process. When a new keyword match is found, you’ll receive an email with the details of the match instantly:

How we built an open-source SEO tool using Workers, D1, and Queues


For some time, there have been a great deal of applications that were hard to build on Workers without relational data or background task tooling. Now, with D1 and Queues, we can build applications that seamlessly integrate between real-time user interfaces, geographically distributed data, background processing, and more, all using the same developer ergonomics and low latency that Workers is known for.

D1 has been crucial for building this application. On larger sites, the number of URLs that need to be scraped can be quite large. If we were to use Workers KV, our key-value store, for storing this data, we would quickly struggle with how to model, retrieve, and update the data needed for this use-case. With D1, we can build relational data models and quickly query just the data we need for each queued processing task.

Using these tools, developers can build internal tools and applications for their companies that are more powerful and more scalable than ever before. With the integration of Cloudflare’s Zero Trust suite, developers can make these applications secure by default, and deploy them to Cloudflare’s global network. This allows developers to build applications that are fast, secure, and reliable, all without having to worry about the underlying infrastructure.

Prospector is a great example of how easy it is to build applications on Cloudflare Workers. With the recent addition of D1 and Queues, we’ve been able to build fully-functional applications that require real-time data and background processing in just a few hours. We’re excited to share the open-source code for Prospector, and we’d love to hear your feedback on the project.

If you have any questions, feel free to reach out to us on Twitter at @cloudflaredev, or join us in the Cloudflare Workers Discord community, which recently hit 20k members and is a great place to ask questions and get help from other developers.

Welcome to Wildebeest: the Fediverse on Cloudflare

Post Syndicated from Celso Martinho original https://blog.cloudflare.com/welcome-to-wildebeest-the-fediverse-on-cloudflare/

Welcome to Wildebeest: the Fediverse on Cloudflare

Welcome to Wildebeest: the Fediverse on Cloudflare

The Fediverse has been a hot topic of discussion lately, with thousands, if not millions, of new users creating accounts on platforms like Mastodon to either move entirely to “the other side” or experiment and learn about this new social network.

Today we’re introducing Wildebeest, an open-source, easy-to-deploy ActivityPub and Mastodon-compatible server built entirely on top of Cloudflare’s Supercloud. If you want to run your own spot in the Fediverse you can now do it entirely on Cloudflare.

The Fediverse, built on Cloudflare

Today you’re left with two options if you want to join the Mastodon federated network: either you join one of the existing servers (servers are also called communities, and each one has its own infrastructure and rules), or you can run your self-hosted server.

There are a few reasons why you’d want to run your own server:

  • You want to create a new community and attract other users over a common theme and usage rules.
  • You don’t want to have to trust third-party servers or abide by their policies and want your server, under your domain, for your personal account.
  • You want complete control over your data, personal information, and content and visibility over what happens with your instance.

The Mastodon gGmbH non-profit organization provides a server implementation using Ruby, Node.js, PostgreSQL and Redis. Running the official server can be challenging, though. You need to own or rent a server or VPS somewhere; you have to install and configure the software, set up the database and public-facing web server, and configure and protect your network against attacks or abuse. And then you have to maintain all of that and deal with constant updates. It’s a lot of scripting and technical work before you can get it up and running; definitely not something for the less technical enthusiasts.

Wildebeest serves two purposes: you can quickly deploy your Mastodon-compatible server on top of Cloudflare and connect it to the Fediverse in minutes, and you don’t need to worry about maintaining or protecting it from abuse or attacks; Cloudflare will do it for you automatically.

Wildebeest is not a managed service. It’s your instance, data, and code running in our cloud under your Cloudflare account. Furthermore, it’s open-sourced, which means it keeps evolving with more features, and anyone can extend and improve it.

Here’s what we support today:

  • ActivityPub, WebFinger, NodeInfo, WebPush and Mastodon-compatible APIs. Wildebeest can connect to or receive connections from other Fediverse servers.
  • Compatible with the most popular Mastodon web (like Pinafore), desktop, and mobile clients. We also provide a simple read-only web interface to explore the timelines and user profiles.
  • You can publish, edit, boost, or delete posts, sorry, toots. We support text, images, and (soon) video.
  • Anyone can follow you; you can follow anyone.
  • You can search for content.
  • You can register one or multiple accounts under your instance. Authentication can be email-based on or using any Cloudflare Access compatible IdP, like GitHub or Google.
  • You can edit your profile information, avatar, and header image.

How we built it

Our implementation is built entirely on top of our products and APIs. Building Wildebeest was another excellent opportunity to showcase our technology stack’s power and versatility and prove how anyone can also use Cloudflare to build larger applications that involve multiple systems and complex requirements.

Here’s a birds-eye diagram of Wildebeest’s architecture:

Welcome to Wildebeest: the Fediverse on Cloudflare

Let’s get into the details and get technical now.

Cloudflare Pages

At the core, Wildebeest is a Cloudflare Pages project running its code using Pages Functions. Cloudflare Pages provides an excellent foundation for building and deploying your application and serving your bundled assets, Functions gives you full access to the Workers ecosystem, where you can run any code.

Functions has a built-in file-based router. The /functions directory structure, which is uploaded by Wildebeest’s continuous deployment builds, defines your application routes and what files and code will process each HTTP endpoint request. This routing technique is similar to what other frameworks like Next.js use.

Welcome to Wildebeest: the Fediverse on Cloudflare

For example, Mastodon’s /api/v1/timelines/public API endpoint is handled by /functions/api/v1/timelines/public.ts with the onRequest method.

export onRequest = async ({ request, env }) => {
	const { searchParams } = new URL(request.url)
	const domain = new URL(request.url).hostname
	return handleRequest(domain, env.DATABASE, {})

export async function handleRequest(
): Promise<Response> {

Unit testing these endpoints becomes easier too, since we only have to call the handleRequest() function from the testing framework. Check one of our Jest tests, mastodon.spec.ts:

import * as v1_instance from 'wildebeest/functions/api/v1/instance'

describe('Mastodon APIs', () => {
	describe('instance', () => {
		test('return the instance infos v1', async () => {
			const res = await v1_instance.handleRequest(domain, env)
			assert.equal(res.status, 200)

			const data = await res.json<Data>()
			assert.equal(data.rules.length, 0)

As with any other regular Worker, Functions also lets you set up bindings to interact with other Cloudflare products and features like KV, R2, D1, Durable Objects, and more. The list keeps growing.

We use Functions to implement a large portion of the official Mastodon API specification, making Wildebeest compatible with the existing ecosystem of other servers and client applications, and also to run our own read-only web frontend under the same project codebase.

Welcome to Wildebeest: the Fediverse on Cloudflare

Wildebeest’s web frontend uses Qwik, a general-purpose web framework that is optimized for speed, uses modern concepts like the JSX JavaScript syntax extension and supports server-side-rendering (SSR) and static site generation (SSG).

Qwik provides a Cloudflare Pages Adaptor out of the box, so we use that (check our framework guide to know more about how to deploy a Qwik site on Cloudflare Pages). For styling we use the Tailwind CSS framework, which Qwik supports natively.

Our frontend website code and static assets can be found under the /frontend directory. The application is handled by the /functions/[[path]].js dynamic route, which basically catches all the non-API requests, and then invokes Qwik’s own internal router, Qwik City, which takes over everything else after that.

The power and versatility of Pages and Functions routes make it possible to run both the backend APIs and a server-side-rendered dynamic client, effectively a full-stack app, under the same project.

Let’s dig even deeper now, and understand how the server interacts with the other components in our architecture.


Wildebeest uses D1, Cloudflare’s first SQL database for the Workers platform built on top of SQLite, now open to everyone in alpha, to store and query data. Here’s our schema:

Welcome to Wildebeest: the Fediverse on Cloudflare

The schema will probably change in the future, as we add more features. That’s fine, D1 supports migrations which are great when you need to update your database schema without losing your data. With each new Wildebeest version, we can create a new migration file if it requires database schema changes.

-- Migration number: 0001 	 2023-01-16T13:09:04.033Z

CREATE UNIQUE INDEX unique_actor_following ON actor_following (actor_id, target_actor_id);

D1 exposes a powerful client API that developers can use to manipulate and query data from Worker scripts, or in our case, Pages Functions.

Here’s a simplified example of how we interact with D1 when you start following someone on the Fediverse:

export async function addFollowing(db, actor, target, targetAcct): Promise<UUID> {
	const query = `INSERT OR IGNORE INTO actor_following (id, actor_id, target_actor_id, state, target_actor_acct) VALUES (?, ?, ?, ?, ?)`
	const out = await db
		.bind(id, actor.id.toString(), target.id.toString(), STATE_PENDING, targetAcct)
	return id

Cloudflare’s culture of dogfooding and building on top of our own products means that we sometimes experience their shortcomings before our users. We did face a few challenges using D1, which is built on SQLite, to store our data. Here are two examples.

ActivityPub uses UUIDs to identify objects and reference them in URIs extensively. These objects need to be stored in the database. Other databases like PostgreSQL provide built-in functions to generate unique identifiers. SQLite and D1 don’t have that, yet, it’s in our roadmap.

Worry not though, the Workers runtime supports Web Crypto, so we use crypto.randomUUID() to get our unique identifiers. Check the /backend/src/activitypub/actors/inbox.ts:

export async function addObjectInInbox(db, actor, obj) {
	const id = crypto.randomUUID()
	const out = await db
		.prepare('INSERT INTO inbox_objects(id, actor_id, object_id) VALUES(?, ?, ?)')
		.bind(id, actor.id.toString(), obj.id.toString())

Problem solved.

The other example is that we need to store dates with sub-second resolution. Again, databases like PostgreSQL have that:

psql> select now();
2023-02-01 11:45:17.425563+00

However SQLite falls short with:

sqlite> select datetime();
2023-02-01 11:44:02

We worked around this problem with a small hack using strftime():

sqlite> select strftime('%Y-%m-%d %H:%M:%f', 'NOW');
2023-02-01 11:49:35.624

See our initial SQL schema, look for the cdate defaults.


Mastodon content has a lot of rich media. We don’t need to reinvent the wheel and build an image pipeline; Cloudflare Images provides APIs to upload, transform, and serve optimized images from our global CDN, so it’s the perfect fit for Wildebeest’s requirements.

Things like posting content images, the profile avatar, or headers, all use the Images APIs. See /backend/src/media/image.ts to understand how we interface with Images.

async function upload(file: File, config: Config): Promise<UploadResult> {
	const formData = new FormData()
	const url = `https://api.cloudflare.com/client/v4/accounts/${config.accountId}/images/v1`

	formData.set('file', file)

	const res = await fetch(url, {
		method: 'POST',
		body: formData,
		headers: {
			authorization: 'Bearer ' + config.apiToken,

      const data = await res.json()
	return data.result

If you’re curious about Images for your next project, here’s a tutorial on how to integrate Cloudflare Images on your website.

Cloudflare Images is also available from the dashboard. You can use it to browse or manage your catalog quickly.

Welcome to Wildebeest: the Fediverse on Cloudflare


The ActivityPub protocol is chatty by design. Depending on the size of your social graph, there might be a lot of back-and-forth HTTP traffic. We can’t have the clients blocked waiting for hundreds of Fediverse message deliveries every time someone posts something.

We needed a way to work asynchronously and launch background jobs to offload data processing away from the main app and keep the clients snappy. The official Mastodon server has a similar strategy using Sidekiq to do background processing.

Fortunately, we don’t need to worry about any of this complexity either. Cloudflare Queues allows developers to send and receive messages with guaranteed delivery, and offload work from your Workers’ requests, effectively providing you with asynchronous batch job capabilities.

To put it simply, you have a queue topic identifier, which is basically a buffered list that scales automatically, then you have one or more producers that, well, produce structured messages, JSON objects in our case, and put them in the queue (you define their schema), and finally you have one or more consumers that subscribes that queue, receive its messages and process them, at their own speed.

Welcome to Wildebeest: the Fediverse on Cloudflare

Here’s the How Queues works page for more information.

In our case, the main application produces queue jobs whenever any incoming API call requires long, expensive operations. For example, when someone posts, sorry, toots something, we need to broadcast that to their followers’ inboxes, potentially triggering many requests to remote servers. Here we are queueing a job for that, thus freeing the APIs to keep responding:

export async function deliverFollowers(
	db: D1Database,
	from: Actor,
	activity: Activity,
	queue: Queue
) {
	const followers = await getFollowers(db, from)

	const messages = followers.map((id) => {
		const body = {
			activity: JSON.parse(JSON.stringify(activity)),
			actorId: from.id.toString(),
			toActorId: id,
		return { body }

	await queue.sendBatch(messages)

Similarly, we don’t want to stop the main APIs when remote servers deliver messages to our instance inboxes. Here’s Wildebeest creating asynchronous jobs when it receives messages in the inbox:

export async function handleRequest(
	domain: string,
	db: D1Database,
	id: string,
	activity: Activity,
	queue: Queue,
): Promise<Response> {
	const handle = parseHandle(id)

	const actorId = actorURL(domain, handle.localPart)
const actor = await actors.getPersonById(db, actorId)

      // creates job
	await queue.send({
		type: MessageType.Inbox,
		actorId: actor.id.toString(),

	// frees the API
	return new Response('', { status: 200 })

And the final piece of the puzzle, our queue consumer runs in a separate Worker, independently from the Pages project. The consumer listens for new messages and processes them sequentially, at its rhythm, freeing everyone else from blocking. When things get busy, the queue grows its buffer. Still, things keep running, and the jobs will eventually get dispatched, freeing the main APIs for the critical stuff: responding to remote servers and clients as quickly as possible.

export default {
	async queue(batch, env, ctx) {
		for (const message of batch.messages) {

			switch (message.body.type) {
				case MessageType.Inbox: {
					await handleInboxMessage(...)
				case MessageType.Deliver: {
					await handleDeliverMessage(...)

If you want to get your hands dirty with Queues, here’s a simple example on Using Queues to store data in R2.

Caching and Durable Objects

Caching repetitive operations is yet another strategy for improving performance in complex applications that require data processing. A famous Netscape developer, Phil Karlton, once said: “There are only two hard things in Computer Science: cache invalidation and naming things.”

Cloudflare obviously knows a lot about caching since it’s a core feature of our global CDN. We also provide Workers KV to our customers, a global, low-latency, key-value data store that anyone can use to cache data objects in our data centers and build fast websites and applications.

However, KV achieves its performance by being eventually consistent. While this is fine for many applications and use cases, it’s not ideal for others.

The ActivityPub protocol is highly transactional and can’t afford eventual consistency. Here’s an example: generating complete timelines is expensive, so we cache that operation. However, when you post something, we need to invalidate that cache before we reply to the client. Otherwise, the new post won’t be in the timeline and the client can fail with an error because it doesn’t see it. This actually happened to us with one of the most popular clients.

Welcome to Wildebeest: the Fediverse on Cloudflare

We needed to get clever. The team discussed a few options. Fortunately, our API catalog has plenty of options. Meet Durable Objects.

Durable Objects are single-instance Workers that provide a transactional storage API. They’re ideal when you need central coordination, strong consistency, and state persistence. You can use Durable Objects in cases like handling the state of multiple WebSocket connections, coordinating and routing messages in a chatroom, or even running a multiplayer game like Doom.

You know where this is going now. Yes, we implemented our key-value caching subsystem for Wildebeest on top of a Durable Object. By taking advantage of the DO’s native transactional storage API, we can have strong guarantees that whenever we create or change a key, the next read will always return the latest version.

The idea is so simple and effective that it took us literally a few lines of code to implement a key-value cache with two primitives: HTTP PUT and GET.

export class WildebeestCache {
	async fetch(request: Request) {
		if (request.method === 'GET') {
			const { pathname } = new URL(request.url)
			const key = pathname.slice(1)
			const value = await this.storage.get(key)
			return new Response(JSON.stringify(value))

		if (request.method === 'PUT') {
			const { key, value } = await request.json()
			await this.storage.put(key, value)
			return new Response('', { status: 201 })

Strong consistency it is. Lets move to user registration and authentication now.

Zero Trust Access

The official Mastodon server handles user registrations, typically using email, before you can choose your local user name and start using the service. Handling user registration and authentication can be daunting and time-consuming if we were to build it from scratch though.

Furthermore, people don’t want to create new credentials for every new service they want to use and instead want more convenient OAuth-like authorization and authentication methods so that they can reuse their existing Apple, Google, or GitHub accounts.

We wanted to simplify things using Cloudflare’s built-in features. Needless to say, we have a product that handles user onboarding, authentication, and access policies to any application behind Cloudflare; it’s called Zero Trust. So we put Wildebeest behind it.

Zero Trust Access can either do one-time PIN (OTP) authentication using email or single-sign-on (SSO) with many identity providers (examples: Google, Facebook, GitHub, Linkedin), including any generic one supporting SAML 2.0.

When you start using Wildebeest with a client, you don’t need to register at all. Instead, you go straight to log in, which will redirect you to the Access page and handle the authentication according to the policy that you, the owner of your instance, configured.

The policy defines who can authenticate, and how.

Welcome to Wildebeest: the Fediverse on Cloudflare

When authenticated, Access will redirect you back to Wildebeest. The first time this happens, we will detect that we don’t have information about the user and ask for your Username and Display Name. This will be asked only once and is what will be to create your public Mastodon profile.

Welcome to Wildebeest: the Fediverse on Cloudflare

Technically, Wildebeest implements the OAuth 2 specification. Zero Trust protects the /oauth/authorize endpoint and issues a valid JWT token in the request headers when the user is authenticated. Wildebeest then reads and verifies the JWT and returns an authorization code in the URL redirect.

Once the client has an authorization code, it can use the /oauth/token endpoint to obtain an API access token. Subsequent API calls inject a bearer token in the Authorization header:

Authorization: Bearer access_token

Deployment and Continuous Integration

We didn’t want to run a managed service for Mastodon as it would somewhat diminish the concepts of federation and data ownership. Also, we recognize that ActivityPub and Mastodon are emerging, fast-paced technologies that will evolve quickly and in ways that are difficult to predict just yet.

For these reasons, we thought the best way to help the ecosystem right now would be to provide an open-source software package that anyone could use, customize, improve, and deploy on top of our cloud. Cloudflare will obviously keep improving Wildebeest and support the community, but we want to give our Fediverse maintainers complete control and ownership of their instances and data.

The remaining question was, how do we distribute the Wildebeest bundle and make it easy to deploy into someone’s account when it requires configuring so many Cloudflare features, and how do we facilitate updating the software over time?

The solution ended up being a clever mix of using GitHub with GitHub Actions, Deploy with Workers, and Terraform.

Welcome to Wildebeest: the Fediverse on Cloudflare

The Deploy with Workers button is a specially crafted link that auto-generates a workflow page where the user gets asked some questions, and Cloudflare handles authorizing GitHub to deploy to Workers, automatically forks the Wildebeest repository into the user’s account, and then configures and deploys the project using a GitHub Actions workflow.

Welcome to Wildebeest: the Fediverse on Cloudflare

A GitHub Actions workflow is a YAML file that declares what to do in every step. Here’s the Wildebeest workflow (simplified):

name: Deploy
      - main
    runs-on: ubuntu-latest
    timeout-minutes: 60
      - name: Ensure CF_DEPLOY_DOMAIN and CF_ZONE_ID are defined
      - name: Create D1 database
        uses: cloudflare/[email protected]
          command: d1 create wildebeest-${{ env.OWNER_LOWER }}
      - name: retrieve Zero Trust organization
      - name: retrieve Terraform state KV namespace
      - name: download VAPID keys
      - name: Publish DO
      - name: Configure
        run: terraform plan && terraform apply -auto-approve
      - name: Create Queue
      - name: Publish consumer
      - name: Publish
        uses: cloudflare/[email protected]
          command: pages publish --project-name=wildebeest-${{ env.OWNER_LOWER }} .

Updating Wildebeest

This workflow runs automatically every time the main branch changes, so updating the Wildebeest is as easy as synchronizing the upstream official repository with the fork. You don’t even need to use git commands for that; GitHub provides a convenient Sync button in the UI that you can simply click.

Welcome to Wildebeest: the Fediverse on Cloudflare

What’s more? Updates are incremental and non-destructive. When the GitHub Actions workflow redeploys Wildebeest, we only make the necessary changes to your configuration and nothing else. You don’t lose your data; we don’t need to delete your existing configurations. Here’s how we achieved this:

We use Terraform, a declarative configuration language and tool that interacts with our APIs and can query and configure your Cloudflare features. Here’s the trick, whenever we apply a new configuration, we keep a copy of the Terraform state for Wildebeest in a Cloudflare KV key. When a new deployment is triggered, we get that state from the KV copy, calculate the differences, then change only what’s necessary.

Data loss is not a problem either because, as you read above, D1 supports migrations. If we need to add a new column to a table or a new table, we don’t need to destroy the database and create it again; we just apply the necessary SQL to that change.

Welcome to Wildebeest: the Fediverse on Cloudflare

Protection, optimization and observability, naturally

Once Wildebeest is up and running, you can protect it from bad traffic and malicious actors. Cloudflare offers you DDoS, WAF, and Bot Management protection out of the box at a click’s distance.

Likewise, you’ll get instant network and content delivery optimizations from our products and analytics on how your Wildebeest instance is performing and being used.

Welcome to Wildebeest: the Fediverse on Cloudflare

ActivityPub, WebFinger, NodeInfo and Mastodon APIs

Mastodon popularized the Fediverse concept, but many of the underlying technologies used have been around for quite a while. This is one of those rare moments when everything finally comes together to create a working platform that answers an actual use case for Internet users. Let’s quickly go through the protocols that Wildebeest had to implement:


ActivityPub is a decentralized social networking protocol and has been around as a W3C recommendation since at least 2018. It defines client APIs for creating and manipulating content and server-to-server APIs for content exchange and notifications, also known as federation. ActivityPub uses ActivityStreams, an even older W3C protocol, for its vocabulary.

The concepts of Actors (profiles), messages or Objects (the toots), inbox (where you receive toots from people you follow), and outbox (where you send your toots to the people you follow), to name a few of many other actions and activities, are all defined on the ActivityPub specification.

Here’s our folder with the ActivityPub implementation.

import type { APObject } from 'wildebeest/backend/src/activitypub/objects'
import type { Actor } from 'wildebeest/backend/src/activitypub/actors'

export async function addObjectInInbox(db, actor, obj) {
	const id = crypto.randomUUID()
	const out = await db
		.prepare('INSERT INTO inbox_objects(id, actor_id, object_id) VALUES(?, ?, ?)')
		.bind(id, actor.id.toString(), obj.id.toString())


WebFinger is a simple HTTP protocol used to discover information about any entity, like a profile, a server, or a specific feature. It resolves URIs to resource objects.

Mastodon uses WebFinger lookups to discover information about remote users. For example, say you want to interact with @[email protected] Your local server would request https://example.com/.well-known/webfinger?resource=acct:[email protected] (using the acct scheme) and get something like this:

    "subject": "acct:[email protected]",
    "aliases": [
    "links": [
            "rel": "self",
            "type": "application/activity+json",
            "href": "https://example.com/ap/users/user"

Now we know how to interact with @[email protected], using the https://example.com/ap/users/user endpoint.

Here’s our WebFinger response:

export async function handleRequest(request, db): Promise<Response> {
	const jsonLink = /* … link to actor */

	const res: WebFingerResponse = {
		subject: `acct:...`,
		aliases: [jsonLink],
		links: [
				rel: 'self',
				type: 'application/activity+json',
				href: jsonLink,
	return new Response(JSON.stringify(res), { headers })

Mastodon API

Finally, things like setting your server information, profile information, generating timelines, notifications, and searches, are all Mastodon-specific APIs. The Mastodon open-source project defines a catalog of REST APIs, and you can find all the documentation for them on their website.

Our Mastodon API implementation can be found here (REST endpoints) and here (backend primitives). Here’s an example of Mastodon’s server information /api/v2/instance implemented by Wildebeest:

export async function handleRequest(domain, db, env) {

	const res: InstanceConfigV2 = {
		title: env.INSTANCE_TITLE,
		version: getVersion(),
		source_url: 'https://github.com/cloudflare/wildebeest',
		description: env.INSTANCE_DESCR,
		thumbnail: {
		languages: ['en'],
		registrations: {
			enabled: false,
		contact: {
			email: env.ADMIN_EMAIL,
		rules: [],

	return new Response(JSON.stringify(res), { headers })

Wildebeest also implements WebPush for client notifications and NodeInfo for server information.

Other Mastodon-compatible servers had to implement all these protocols too; Wildebeest is one of them. The community is very active in discussing future enhancements; we will keep improving our compatibility and adding support to more features over time, ensuring that Wildebeest plays well with the Fediverse ecosystem of servers and clients emerging.

Get started now

Enough about technology; let’s get you into the Fediverse. We tried to detail all the steps to deploy your server. To start using Wildebeest, head to the public GitHub repository and check our Get Started tutorial.

Most of Wildebeest’s dependencies offer a generous free plan that allows you to try them for personal or hobby projects that aren’t business-critical, however you will need to subscribe an Images plan (the lowest tier should be enough for most needs) and, depending on your server load, Workers Unbound (again, the minimum cost should be plenty for most use cases).

Following our dogfooding mantra, Cloudflare is also officially joining the Fediverse today. You can start following our Mastodon accounts and get the same experience of having regular updates from Cloudflare as you get from us on other social platforms, using your favorite Mastodon apps. These accounts are entirely running on top of a Wildebeest server:

Welcome to Wildebeest: the Fediverse on Cloudflare

Wildebeest is compatible with most client apps; we are confirmed to work with the official Mastodon Android and iOS apps, Pinafore, Mammoth, and tooot, and looking into others like Ivory. If your favorite isn’t working, please submit an issue here, we’ll do our best to help support it.

Final words

Wildebeest was built entirely on top of our Supercloud stack. It was one of the most complete and complex projects we have created that uses various Cloudflare products and features.

We hope this write-up inspires you to not only try deploying Wildebeest and joining the Fediverse, but also building your next application, however demanding it is, on top of Cloudflare.

Wildebeest is a minimally viable Mastodon-compatible server right now, but we will keep improving it with more features and supporting it over time; after all, we’re using it for our official accounts. It is also open-sourced, meaning you are more than welcome to contribute with pull requests or feedback.

In the meantime, we opened a Wildebeest room on our Developers Discord Server and are keeping an eye open on the GitHub repo issues tab. Feel free to engage with us; the team is eager to know how you use Wildebeest and answer your questions.

PS: The code snippets in this blog were simplified to benefit readability and space (the TypeScript types and error handling code were removed, for example). Please refer to the GitHub repo links for the complete versions.

ICYMI: Developer Week 2022 announcements

Post Syndicated from Dawn Parzych original https://blog.cloudflare.com/icymi-developer-week-2022-announcements/

ICYMI: Developer Week 2022 announcements

ICYMI: Developer Week 2022 announcements

Developer Week 2022 has come to a close. Over the last week we’ve shared with you 31 posts on what you can build on Cloudflare and our vision and roadmap on where we’re headed. We shared product announcements, customer and partner stories, and provided technical deep dives. In case you missed any of the posts here’s a handy recap.

Product and feature announcements

Announcement Summary
Welcome to the Supercloud (and Developer Week 2022) Our vision of the cloud — a model of cloud computing that promises to make developers highly productive at scaling from one to Internet-scale in the most flexible, efficient, and economical way.
Build applications of any size on Cloudflare with the Queues open beta Build performant and resilient distributed applications with Queues. Available to all developers with a paid Workers plan.
Migrate from S3 easily with the R2 Super Slurper A tool to easily and efficiently move objects from your existing storage provider to R2.
Get started with Cloudflare Workers with ready-made templates See what’s possible with Workers and get building faster with these starter templates.
Reduce origin load, save on cloud egress fees, and maximize cache hits with Cache Reserve Cache Reserve is graduating to open beta – users can now test and integrate it into their content delivery strategy without any additional waiting.
Store and process your Cloudflare Logs… with Cloudflare Query Cloudflare logs stored on R2.
UPDATE Supercloud SET status = ‘open alpha’ WHERE product = ‘D1’ D1, our first global relational database, is in open alpha. Start building and share your feedback with us.
Automate an isolated browser instance with just a few lines of code The Browser Rendering API is an out of the box solution to run browser automation tasks with Puppeteer in Workers.
Bringing authentication and identification to Workers through Mutual TLS Send outbound requests with Workers through a mutually authenticated channel.
Spice up your sites on Cloudflare Pages with Pages Functions General Availability Easily add dynamic content to your Pages projects with Functions.
Announcing the first Workers Launchpad cohort and growth of the program to $2 billion We were blown away by the interest in the Workers Launchpad Funding Program and are proud to introduce the first cohort.
The most programmable Supercloud with Cloudflare Snippets Modify traffic routed through the Cloudflare CDN without having to write a Worker.
Keep track of Workers’ code and configuration changes with Deployments Track your changes to a Worker configuration, binding, and code.
Send Cloudflare Workers logs to a destination of your choice with Workers Trace Events Logpush Gain visibility into your Workers when logs are sent to your analytics platform or object storage. Available to all users on a Workers paid plan.
Improved Workers TypeScript support Based on feedback from users we’ve improved our types and are open-sourcing the automatic generation scripts.

Technical deep dives

Announcement Summary
The road to a more standards-compliant Workers API An update on the work the WinterCG is doing on the creation of common API standards in JavaScript runtimes and how Workers is implementing them.
Indexing millions of HTTP requests using Durable Objects
Indexing and querying millions of logs stored in R2 using Workers, Durable Objects, and the Streams API.
Iteration isn’t just for code: here are our latest API docs We’ve revamped our API reference documentation to standardize our API content and improve the overall developer experience when using the Cloudflare APIs.
Making static sites dynamic with D1 A template to build a D1-based comments APi.
The Cloudflare API now uses OpenAPI schemas OpenAPI schemas are now available for the Cloudflare API.
Server-side render full stack applications with Pages Functions Run server-side rendering in a Function using a variety of frameworks including Qwik, Astro, and SolidStart.
Incremental adoption of micro-frontends with Cloudflare Workers How to replace selected elements of a legacy client-side rendered application with server-side rendered fragments using Workers.
How we built it: the technology behind Cloudflare Radar 2.0 Details on how we rebuilt Radar using Pages, Remix, Workers, and R2.
How Cloudflare uses Terraform to manage Cloudflare How we made it easier for our developers to make changes with the Cloudflare Terraform provider.
Network performance Update: Developer Week 2022 See how fast Cloudflare Workers are compared to other solutions.
How Cloudflare instruments services using Workers Analytics Engine Instrumentation with Analytics Engine provides data to find bugs and helps us prioritize new features.
Doubling down on local development with Workers:Miniflare meets workerd Improving local development using Miniflare3, now powered by workerd.

Customer and partner stories

Announcement Summary
Cloudflare Workers scale too well and broke our infrastructure, so we are rebuilding it on Workers How DevCycle re-architected their feature management tool using Workers.
Easy Postgres integration with Workers and Neon.tech Neon.tech solves the challenges of connecting to Postgres from Workers
Xata Workers: client-side database access without client-side secrets Xata uses Workers for Platform to reduce security risks of running untrusted code.
Twilio Segment Edge SDK powered by Cloudflare Workers The Segment Edge SDK, built on Workers, helps applications collect and track events from the client, and get access to realtime user state to personalize experiences.


And that’s it for Developer Week 2022. But you can keep the conversation going by joining our Discord Community.

Making static sites dynamic with Cloudflare D1

Post Syndicated from Kristian Freeman original https://blog.cloudflare.com/making-static-sites-dynamic-with-cloudflare-d1/

Making static sites dynamic with Cloudflare D1


Making static sites dynamic with Cloudflare D1

There are many ways to store data in your applications. For example, in Cloudflare Workers applications, we have Workers KV for key-value storage and Durable Objects for real-time, coordinated storage without compromising on consistency. Outside the Cloudflare ecosystem, you can also plug in other tools like NoSQL and graph databases.

But sometimes, you want SQL. Indexes allow us to retrieve data quickly. Joins enable us to describe complex relationships between different tables. SQL declaratively describes how our application’s data is validated, created, and performantly queried.

D1 was released today in open alpha, and to celebrate, I want to share my experience building apps with D1: specifically, how to get started, and why I’m excited about D1 joining the long list of tools you can use to build apps on Cloudflare.

Making static sites dynamic with Cloudflare D1

D1 is remarkable because it’s an instant value-add to applications without needing new tools or stepping out of the Cloudflare ecosystem. Using wrangler, we can do local development on our Workers applications, and with the addition of D1 in wrangler, we can now develop proper stateful applications locally as well. Then, when it’s time to deploy the application, wrangler allows us to both access and execute commands to your D1 database, as well as your API itself.

What we’re building

In this blog post, I’ll show you how to use D1 to add comments to a static blog site. To do this, we’ll construct a new D1 database and build a simple JSON API that allows the creation and retrieval of comments.

As I mentioned, separating D1 from the app itself – an API and database that remains separate from the static site – allows us to abstract the static and dynamic pieces of our website from each other. It also makes it easier to deploy our application: we will deploy the frontend to Cloudflare Pages, and the D1-powered API to Cloudflare Workers.

Building a new application

First, we’ll add a basic API in Workers. Create a new directory and in it a new wrangler project inside it:

$ mkdir d1-example && d1-example
$ wrangler init

In this example, we’ll use Hono, an Express.js-style framework, to rapidly build our API. To use Hono in this project, install it using NPM:

$ npm install hono

Then, in src/index.ts, we’ll initialize a new Hono app, and define a few endpoints – GET /API/posts/:slug/comments, and POST /get/api/:slug/comments.

import { Hono } from 'hono'
import { cors } from 'hono/cors'

const app = new Hono()

app.get('/api/posts/:slug/comments', async c => {
  // do something

app.post('/api/posts/:slug/comments', async c => {
  // do something

export default app

Now we’ll create a D1 database. In Wrangler 2, there is support for the wrangler d1 subcommand, which allows you to create and query your D1 databases directly from the command line. So, for example, we can create a new database with a single command:

$ wrangler d1 create d1-example

With our created database, we can take the database name ID and associate it with a binding inside of wrangler.toml, wrangler’s configuration file. Bindings allow us to access Cloudflare resources, like D1 databases, KV namespaces, and R2 buckets, using a simple variable name in our code. Below, we’ll create the binding DB and use it to represent our new database:

[[ d1_databases ]]
binding = "DB" # i.e. available in your Worker on env.DB
database_name = "d1-example"
database_id = "4e1c28a9-90e4-41da-8b4b-6cf36e5abb29"

Note that this directive, the [[d1_databases]] field, currently requires a beta version of wrangler. You can install this for your project using the command npm install -D wrangler/beta.

With the database configured in our wrangler.toml, we can start interacting with it from the command line and inside our Workers function.

First, you can issue direct SQL commands using wrangler d1 execute:

$ wrangler d1 execute d1-example --command "SELECT name FROM sqlite_schema WHERE type ='table'"
Executing on d1-example:
│ name │
│ sqlite_sequence │

You can also pass a SQL file – perfect for initial data seeding in a single command. Create src/schema.sql, which will create a new comments table for our project:

drop table if exists comments;
create table comments (
  id integer primary key autoincrement,
  author text not null,
  body text not null,
  post_slug text not null
create index idx_comments_post_id on comments (post_slug);

-- Optionally, uncomment the below query to create data

-- insert into comments (author, body, post_slug)
-- values ("Kristian", "Great post!", "hello-world");

With the file created, execute the schema file against the D1 database by passing it with the flag --file:

$ wrangler d1 execute d1-example --file src/schema.sql

We’ve created a SQL database with just a few commands and seeded it with initial data. Now we can add a route to our Workers function to retrieve data from that database. Based on our wrangler.toml config, the D1 database is now accessible via the DB binding. In our code, we can use the binding to prepare SQL statements and execute them, for instance, to retrieve comments:

app.get('/api/posts/:slug/comments', async c => {
  const { slug } = c.req.param()
  const { results } = await c.env.DB.prepare(`
    select * from comments where post_slug = ?
  return c.json(results)

In this function, we accept a slug URL query parameter and set up a new SQL statement where we select all comments with a matching post_slug value to our query parameter. We can then return it as a simple JSON response.

So far, we’ve built read-only access to our data. But “inserting” values to SQL is, of course, possible as well. So let’s define another function that allows POST-ing to an endpoint to create a new comment:

app.post('/API/posts/:slug/comments', async c => {
  const { slug } = c.req.param()
  const { author, body } = await c.req.json<Comment>()

  if (!author) return c.text("Missing author value for new comment")
  if (!body) return c.text("Missing body value for new comment")

  const { success } = await c.env.DB.prepare(`
    insert into comments (author, body, post_slug) values (?, ?, ?)
  `).bind(author, body, slug).run()

  if (success) {
    return c.text("Created")
  } else {
    return c.text("Something went wrong")

In this example, we built a comments API for powering a blog. To see the source for this D1-powered comments API, you can visit cloudflare/templates/worker-d1-api.

Making static sites dynamic with Cloudflare D1


One of the things most exciting about D1 is the opportunity to augment existing applications or websites with dynamic, relational data. As a former Ruby on Rails developer, one of the things I miss most about that framework in the world of JavaScript and serverless development tools is the ability to rapidly spin up full data-driven applications without needing to be an expert in managing database infrastructure. With D1 and its easy onramp to SQL-based data, we can build true data-driven applications without compromising on performance or developer experience.

This shift corresponds nicely with the advent of static sites in the last few years, using tools like Hugo or Gatsby. A blog built with a static site generator like Hugo is incredibly performant – it will build in seconds with small asset sizes.

But by trading a tool like WordPress for a static site generator, you lose the opportunity to add dynamic information to your site. Many developers have patched over this problem by adding more complexity to their build processes: fetching and retrieving data and generating pages using that data as part of the build.

This addition of complexity in the build process attempts to fix the lack of dynamism in applications, but it still isn’t genuinely dynamic. Instead of being able to retrieve and display new data as it’s created, the application rebuilds and redeploys whenever data changes so that it appears to be a live, dynamic representation of data. Your application can remain static, and the dynamic data will live geographically close to the users of your site, accessible via a queryable and expressive API.

D1: our quest to simplify databases

Post Syndicated from Nevi Shah original https://blog.cloudflare.com/whats-new-with-d1/

D1: our quest to simplify databases

D1: our quest to simplify databases

When we announced D1 in May of this year, we knew it would be the start of something new – our first SQL database with Cloudflare Workers. Prior to D1 we’ve announced storage options like KV (key-value store), Durable Objects (single location, strongly consistent data storage) and R2 (blob storage). But the question always remained “How can I store and query relational data without latency concerns and an easy API?”

The long awaited “Cloudflare Database” was the true missing piece to build your application entirely on Cloudflare’s global network, going from a blank canvas in VSCode to a full stack application in seconds. Compatible with the popular SQLite API, D1 empowers developers to build out their databases without getting bogged down by complexity and having to manage every underlying layer.

Since our launch announcement in May and private beta in June, we’ve made great strides in building out our vision of a serverless database. With D1 still in private beta but an open beta on the horizon, we’re excited to show and tell our journey of building D1 and what’s to come.

The D1 Experience

We knew from Cloudflare Workers feedback that using Wrangler as the mechanism to create and deploy applications is loved and preferred by many. That’s why when Wrangler 2.0 was announced this past May alongside D1, we took advantage of the new and improved CLI for every part of the experience from data creation to every update and iteration. Let’s take a quick look on how to get set up in a few easy steps.

Create your database

With the latest version of Wrangler installed, you can create an initialized empty database with a quick

npx wrangler d1 create my_database_name

To get your database up and running! Now it’s time to add your data.

Bootstrap it

It wouldn’t be the “Cloudflare way” if you had to sit through an agonizingly long process to get set up. So we made it easy and painless to bring your existing data from an old database and bootstrap your new D1 database.  You can run

wrangler d1 execute my_database-name --file ./filename.sql

and pass through an existing SQLite .sql file of your choice. Your database is now ready for action.

Develop & Test Locally

With all the improvements we’ve made to Wrangler since version 2 launched a few months ago, we’re pleased to report that D1 has full remote & local wrangler dev support:

D1: our quest to simplify databases

When running wrangler dev -–local -–persist, an SQLite file will be created inside .wrangler/state. You can then use a local GUI program for managing it, like SQLiteFlow (https://www.sqliteflow.com/) or Beekeeper (https://www.beekeeperstudio.io/).

Or you can simply use SQLite directly with the SQLite command line by running sqlite3 .wrangler/state/d1/DB.sqlite3:

D1: our quest to simplify databases

Automatic backups & one-click restore

No matter how much you test your changes, sometimes things don’t always go according to plan. But with Wrangler you can create a backup of your data, view your list of backups or restore your database from an existing backup. In fact, during the beta, we’re taking backups of your data every hour automatically and storing them in R2, so you will have the option to rollback if needed.

D1: our quest to simplify databases

And the best part – if you want to use a production snapshot for local development or to reproduce a bug, simply copy it into the .wrangler/state directory and wrangler dev –-local –-persist will pick it up!

Let’s download a D1 backup to our local disk. It’s SQLite compatible.

D1: our quest to simplify databases

Now let’s run our D1 worker locally, from the backup.

D1: our quest to simplify databases

Create and Manage from the dashboard

However, we realize that CLIs are not everyone’s jam. In fact, we believe databases should be accessible to every kind of developer – even those without much database experience! D1 is available right from the Cloudflare dashboard giving you near total command parity with Wrangler in just a few clicks. Bootstrapping your database, creating tables, updating your database, viewing tables and triggering backups are all accessible right at your fingertips.

D1: our quest to simplify databases

Changes made in the UI are instantly available to your Worker — no deploy required!

We’ve told you about some of the improvements we’ve landed since we first announced D1, but as always, we also wanted to give you a small taste (with some technical details) of what’s ahead. One really important functionality of a database is transactions — something D1 wouldn’t be complete without.

Sneak peek: how we’re bringing JavaScript transactions to D1

With D1, we strive to present a dramatically simplified interface to creating and querying relational data, which for the most part is a good thing. But simplification occasionally introduces drawbacks, where a use-case is no longer easily supported without introducing some new concepts. D1 transactions are one example.

Transactions are a unique challenge

You don’t need to specify where a Cloudflare Worker or a D1 database run—they simply run everywhere they need to. For Workers, that is as close as possible to the users that are hitting your site right this second. For D1 today, we don’t try to run a copy in every location worldwide, but dynamically manage the number and location of read-only replicas based on how many queries your database is getting, and from where. However, for queries that make changes to a database (which we generally call “writes” for short), they all have to travel back to the single Primary D1 instance to do their work, to ensure consistency.

But what if you need to do a series of updates at once? While you can send multiple SQL queries with .batch() (which does in fact use database transactions under the hood), it’s likely that, at some point, you’ll want to interleave database queries & JS code in a single unit of work.

This is exactly what database transactions were invented for, but if you try running BEGIN TRANSACTION in D1 you’ll get an error. Let’s talk about why that is.

Why native transactions don’t work
The problem arises from SQL statements and JavaScript code running in dramatically different places—your SQL executes inside your D1 database (primary for writes, nearest replica for reads), but your Worker is running near the user, which might be on the other side of the world. And because D1 is built on SQLite, only one write transaction can be open at once. Meaning that, if we permitted BEGIN TRANSACTION, any one Worker request, anywhere in the world, could effectively block your whole database! This is a quite dangerous thing to allow:

  • A Worker could start a transaction then crash due to a software bug, without calling ROLLBACK. The primary would be blocked, waiting for more commands from a Worker that would never come (until, probably, some timeout).
  • Even without bugs or crashes, transactions that require multiple round-trips between JavaScript and SQL could end up blocking your whole system for multiple seconds, dramatically limiting how high an application built with Workers & D1 could scale.

But allowing a developer to define transactions that mix both SQL and JavaScript makes building applications with Workers & D1 so much more flexible and powerful. We need a new solution (or, in our case, a new version of an old solution).

A way forward: stored procedures
Stored procedures are snippets of code that are uploaded to the database, to be executed directly next to the data. Which, at first blush, sounds exactly like what we want.

However, in practice, stored procedures in traditional databases are notoriously frustrating to work with, as anyone who’s developed a system making heavy use of them will tell you:

  • They’re often written in a different language to the rest of your application. They’re usually written in (a specific dialect of) SQL or an embedded language like Tcl/Perl/Python. And while it’s technically possible to write them in JavaScript (using an embedded V8 engine), they run in such a different environment to your application code it still requires significant context-switching to maintain them.
  • Having both application code and in-database code affects every part of the development lifecycle, from authoring, testing, deployment, rollbacks and debugging. But because stored procedures are usually introduced to solve a specific problem, not as a general purpose application layer, they’re often managed completely manually. You can end up with them being written once, added to the database, then never changed for fear of breaking something.

With D1, we can do better.

The point of a stored procedure was to execute directly next to the data—uploading the code and executing it inside the database was simply a means to that end. But we’re using Workers, a global JavaScript execution platform, can we use them to solve this problem?

It turns out, absolutely! But here we have a few options of exactly how to make it work, and we’re working with our private beta users to find the right API. In this section, I’d like to share with you our current leading proposal, and invite you all to give us your feedback.

When you connect a Worker project to a D1 database, you add the section like the following to your wrangler.toml:

[[ d1_databases ]]
# What binding name to use (e.g. env.DB):
binding = "DB"
# The name of the DB (used for wrangler d1 commands):
database_name = "my-d1-database"
# The D1's ID for deployment:
database_id = "48a4224e-...3b09"
# Which D1 to use for `wrangler dev`:
# (can be the same as the previous line)
preview_database_id = "48a4224e-...3b09"

# NEW: adding "procedures", pointing to a new JS file:
procedures = "./src/db/procedures.js"

That D1 Procedures file would contain the following (note the new db.transaction() API, that is only available within a file like this):

export default class Procedures {
  constructor(db, env, ctx) {
    this.db = db

  // any methods you define here are available on env.DB.Procedures
  // inside your Worker
  async Checkout(cartId: number) {
    // Inside a Procedure, we have a new db.transaction() API
    const result = await this.db.transaction(async (txn) => {
      // Transaction has begun: we know the user can't add anything to
      // their cart while these actions are in progress.
      const [cart, user] = Helpers.loadCartAndUser(cartId)

      // We can update the DB first, knowing that if any of the later steps
      // fail, all these changes will be undone.
      await this.db
        .prepare(`UPDATE cart SET status = ?1 WHERE cart_id = ?2`)
        .bind('purchased', cartId)
      const newBalance = user.balance - cart.total_cost
      await this.db
        .prepare(`UPDATE user SET balance = ?1 WHERE user_id = ?2`)
        // Note: the DB may have a CHECK to guarantee 'user.balance' can not
        // be negative. In that case, this statement may fail, an exception
        // will be thrown, and the transaction will be rolled back.
        .bind(newBalance, cart.user_id)

      // Once all the DB changes have been applied, attempt the payment:
      const { ok, details } = await PaymentAPI.processPayment(
      if (!ok) {
        // If we throw an Exception, the transaction will be rolled back
        // and result.error will be populated:
        // throw new PaymentFailedError(details)
        // Alternatively, we can do both of those steps explicitly
        await txn.rollback()
        // The transaction is rolled back, our DB is now as it was when we
        // started. We can either move on and try something new, or just exit.
        return { error: new PaymentFailedError(details) }

      // This is implicitly called when the .transaction() block finishes,
      // but you can explicitly call it too (potentially committing multiple
      // times in a single db.transaction() block).
      await txn.commit()

      // Anything we return here will be returned by the 
      // db.transaction() block
      return {
        amount_charged: cart.total_cost,
        remaining_balance: newBalance,

    if (result.error) {
      // Our db.transaction block returned an error or threw an exception.

    // We're still in the Procedure, but the Transaction is complete and
    // the DB is available for other writes. We can either do more work
    // here (start another transaction?) or return a response to our Worker.
    return result

And in your Worker, your DB binding now has a “Procedures” property with your function names available:

const { error, amount_charged, remaining_balance } =
  await env.DB.Procedures.Checkout(params.cartId)

if (error) {
  // Something went wrong, `error` has details
} else {
  // Display `amount_charged` and `remaining_balance` to the user.

Multiple Procedures can be triggered at one time, but only one db.transaction() function can be active at once: any other write queries or other transaction blocks will be queued, but all read queries will continue to hit local replicas and run as normal. This API gives you the ability to ensure consistency when it’s essential but with the minimal impact on total overall performance worldwide.

Request for feedback

As with all our products, feedback from our users drives the roadmap and development. While the D1 API is in beta testing today, we’re still seeking feedback on the specifics. However, we’re pleased that it solves both the problems with transactions that are specific to D1 and the problems with stored procedures described earlier:

  • Code is executing as close as possible to the database, removing network latency while a transaction is open.
  • Any exceptions or cancellations of a transaction cause an instant rollback—there is no way to accidentally leave one open and block the whole D1 instance.
  • The code is in the same language as the rest of your Worker code, in the exact same dialect (e.g. same TypeScript config as it’s part of the same build).
  • It’s deployed seamlessly as part of your Worker. If two Workers bind to the same D1 instance but define different procedures, they’ll only see their own code. If you want to share code between projects or databases, extract a library as you would with any other shared code.
  • In local development and test, the procedure works just like it does in production, but without the network call, allowing seamless testing and debugging as if it was a local function.
  • Because procedures and the Worker that define them are treated as a single unit, rolling back to an earlier version never causes a skew between the code in the database and the code in the Worker.

The D1 ecosystem: contributions from the community

We’ve told you about what we’ve been up to and what’s ahead, but one of the unique things about this project is all the contributions from our users. One of our favorite parts of private betas is not only getting feedback and feature requests, but also seeing what ideas and projects come to fruition. While sometimes this means personal projects, with D1, we’re seeing some incredible contributions to the D1 ecosystem. Needless to say, the work on D1 hasn’t just been coming from within the D1 team, but also from the wider community and other developers at Cloudflare. Users have been showing off their D1 additions within our Discord private beta channel and giving others the opportunity to use them as well. We wanted to take a moment to highlight them.


Dealing with raw SQL syntax is powerful (and using the D1 .bind() API, safe against SQL injections) but it can be a little clumsy. On the other hand, most existing query builders assume direct access to the underlying DB, and so aren’t suitable to use with D1. So Cloudflare developer Gabriel Massadas designed a small, zero-dependency query builder called workers-qb:

import { D1QB } from 'workers-qb'
const qb = new D1QB(env.DB)

const fetched = await qb.fetchOne({
    tableName: "employees",
    fields: "count(*) as count",
    where: {
      conditions: "active = ?1",
      params: [true]

Check out the project homepage for more information: https://workers-qb.massadas.com/.

D1 console

While you can interact with D1 through both Wrangler and the dashboard, Cloudflare Community champion, Isaac McFadyen created the very first D1 console where you can quickly execute a series of queries right through your terminal. With the D1 console, you don’t need to spend time writing the various Wrangler commands we’ve created – just execute your queries.

This includes all bells and whistles you would expect from a modern database console including multiline input, command history, validation for things D1 may not yet support, and ability to save your Cloudflare credentials for later use.

Check out the full project on GitHub or NPM for more information.

Miniflare test Integration

The Miniflare project, which powers Wrangler’s local development experience, also provides fully-fledged test environments for popular JavaScript test runners, Jest and Vitest. With this comes the concept of Isolated Storage, allowing each test to run independently, so that changes made in one don’t affect the others. Brendan Coll, creator of Miniflare, guided the D1 test implementation to give the same benefits:

import Worker from ‘../src/index.ts’
const { DB } = getMiniflareBindings();

beforeAll(async () => {
  // Your D1 starts completely empty, so first you must create tables
  // or restore from a schema.sql file.
  await DB.exec(`CREATE TABLE entries (id INTEGER PRIMARY KEY, value TEXT)`);

// Each describe block & each test gets its own view of the data.
describe(‘with an empty DB’, () => {
  it(‘should report 0 entries’, async () => {
    await Worker.fetch(...)
  it(‘should allow new entries’, async () => {
    await Worker.fetch(...)

// Use beforeAll & beforeEach inside describe blocks to set up particular DB states for a set of tests
describe(‘with two entries in the DB’, () => {
  beforeEach(async () => {
    await DB.prepare(`INSERT INTO entries (value) VALUES (?), (?)`)
            .bind(‘aaa’, ‘bbb’)
  // Now, all tests will run with a DB with those two values
  it(‘should report 2 entries’, async () => {
    await Worker.fetch(...)
  it(‘should not allow duplicate entries’, async () => {
    await Worker.fetch(...)

All the databases for tests are run in-memory, so these are lightning fast. And fast, reliable testing is a big part of building maintainable real-world apps, so we’re thrilled to extend that to D1.

Want access to the private beta?

Feeling inspired?

We love to see what our beta users build or want to build especially when our products are at an early stage. As we march toward an open beta, we’ll be looking specifically for your feedback. We are slowly letting more folks into the beta, but if you haven’t received your “golden ticket” yet with access, sign up here! Once you’ve been invited in, you’ll receive an official welcome email.

As always, happy building!

Going originless with Cloudflare Workers – Building a Todo app – Part 1: The API

Post Syndicated from Kabir Sikand original https://blog.cloudflare.com/workers-todo-part-1/

Going originless with Cloudflare Workers – Building a Todo app – Part 1: The API

Going originless with Cloudflare Workers – Building a Todo app – Part 1: The API

A few months ago we launched Custom Domains into an open beta. Custom Domains allow you to hook up your Workers to the Internet, without having to deal with DNS records or certificates – just enter a valid hostname and Cloudflare will do the rest! The beta’s over, and Custom Domains are now GA.

Custom Domains aren’t just about a seamless developer experience; they also allow you to build a globally distributed instantly scalable application on Cloudflare’s Developer Platform. That’s because Workers leveraging Custom Domains have no concept of an ‘Origin Server’. There’s no ‘home’ to phone to – and that also means your application can use the power of Cloudflare’s global network to run your application, well, everywhere. It’s truly serverless.

Let’s build “Todo”, but without the servers

Today we’ll start a series of posts outlining a simple todo list application. We’ll start with an API and hook it up to the Internet using Custom Domains.

With Custom Domains, you’re treating the whole network as the application server. Any time a request comes into a Cloudflare data center, Workers are triggered in that data center and connect to resources across the network as needed. Our developers don’t need to think about regions, or replication, or spinning up the right number of instances to handle unforeseen load. Instead, just deploy your Workers and Cloudflare will handle the rest.

For our todo application, we begin by building an API Gateway to perform routing, any authorization checks, and drop invalid requests. We then fan out to each individual use case in a separate Worker, so our teams can independently make updates or add features to each endpoint without a full redeploy of the whole application. Finally, each Worker has a D1 binding to be able to create, read, update, and delete records from the database. All of this happens on Cloudflare’s global network, so your API is truly available everywhere. The architecture will look something like this:

Going originless with Cloudflare Workers – Building a Todo app – Part 1: The API

Bootstrap the D1 Database

First off, we’re going to need a D1 database set up, with a schema for our todo application to run on. If you’re not familiar with D1, it’s Cloudflare’s serverless database offering – explained in more detail here. To get started, we use the wrangler d1 command to create a new database:

npx wrangler d1 create <todo | custom-database-name>

After executing this command, you will be asked to add a snippet of code to your wrangler.toml file that looks something like this:

[[ d1_databases ]]
binding = "db" # i.e. available in your Worker on env.db
database_name = "<todo | custom-database-name>"
database_id = "<UUID>"

Let’s save that for now, and we’ll put these into each of our private microservices in a few moments. Next, we’re going to create our database schema. It’s a simple todo application, so it’ll look something like this, with some seeded data:


CREATE TABLE todos (id INTEGER PRIMARY KEY, todo TEXT, todoStatus BOOLEAN NOT NULL CHECK (todoStatus IN (0, 1)));
INSERT INTO todos (todo, todoStatus) VALUES ("Fold my laundry", 0),("Get flowers for mum’s birthday", 0),("Find Nemo", 0),("Water the monstera", 1);

You can bootstrap your new D1 database by running:

npx wrangler d1 execute <todo | custom-database-name> --file=./schema.sql

Then validate your new data by running a query through Wrangler using the following command:

npx wrangler d1 execute <todo | custom-database-name> --command='SELECT * FROM todos';

Great! We’ve now got a database running entirely on Cloudflare’s global network.

Build the endpoint Workers

To talk to your database, we’ll spin up a series of private microservices for each endpoint in our application. We want to be able to create, read, update, delete, and list our todos. The full source code for each is available here. Below is code from a Worker that lists all our todos from D1.


export default {
   async fetch(request, env) {
     const { results } = await env.db.prepare(
       "SELECT * FROM todos"
     return Response.json(results);

The Worker ‘todo-list’ needs to be able to access D1 from the environment variable db. To do this, we’ll define the D1 binding in our wrangler.toml file. We also specify that workers_dev is false, preventing a preview from being generated via workers.dev (we want this to be a private microservice).


name = "todo-list"
main = "src/list.js"
compatibility_date = "2022-09-07"
workers_dev = false
usage_model = "unbound"

[[ d1_databases ]]
binding = "db" # i.e. available in your Worker on env.db
database_name = "<todo | custom-database-name>"
database_id = "UUID"

Finally, use wrangler publish to deploy this microservice.

todo/list on ∞main [!] 
› wrangler publish
 ⛅️ wrangler 0.0.0-893830aa
Retrieving cached values for account from ../../../node_modules/.cache/wrangler
Your worker has access to the following bindings:
- D1 Databases:
  - db: todo (UUID)
Total Upload: 4.71 KiB / gzip: 1.60 KiB
Uploaded todo-list (0.96 sec)
No publish targets for todo-list (0.00 sec)

Notice that wrangler mentions there are no ‘publish targets’ for todo-list. That’s because we haven’t hooked todo-list up to any HTTP endpoints. That’s fine! We’re going to use Service Bindings to route requests through a gateway worker, as described in the architecture diagram above.

Next, reuse these steps to create similar microservices for each of our create, read, update, and delete endpoints. The source code is available to follow along.

Tying it all together with an API Gateway

Each of our Workers are able to talk to the D1 database, but how can our application talk to our API? We’ll build out a simple API gateway to route incoming requests to the appropriate microservice. For the purposes of our application, we’re using a combination of URL pathname and request method to detect which endpoint is appropriate.


export default {
 async fetch(request, env) {
     const url = new URL(request.url)
     const idPattern = new URLPattern({ pathname: '/:id' })
     if (idPattern.test(request.url)) {
       switch (request.method){
         case 'GET':
           return await env.get.fetch(request.clone())
         case 'PATCH':
           return await env.update.fetch(request.clone())
         case 'DELETE':
           return await env.delete.fetch(request.clone())
           return new Response("Unsupported method for endpoint /:id", {status: 405})
     } else if (url.pathname == '/') {
       switch (request.method){
         case 'GET':
           return await env.list.fetch(request.clone())
         case 'POST':
           return await env.create.fetch(request.clone())
           return new Response("Unsupported method for endpoint /", {status: 405})
     return new Response("Not found. Supported endpoints are /:id and /", {status: 404})
   } catch(e) {
     return new Response(e, {status: 500})

With our API gateway all set, we just need to expose our application to the Internet using a Custom Domain, and hook up our Service Bindings, so the gateway Worker can access each appropriate microservice. We’ll set this up in a wrangler.toml.


name = "todo-gateway"
main = "src/gateway.js"
compatibility_date = "2022-09-07"
workers_dev = false
usage_model = "unbound"
routes =  [
   {pattern="todos.radiobox.tv", custom_domain=true, zone_name="radiobox.tv"}
services = [
   {binding = "get",service = "todo-get"},
   {binding = "delete",service = "todo-delete"},
   {binding = "create",service = "todo-create"},
   {binding = "update",service = "todo-update"},
   {binding = "list",service = "todo-list"}

Next, use wrangler publish to deploy your application to the Cloudflare network. Seconds later, you’ll have a simple, functioning todo API built entirely on Cloudflare’s Developer Platform!

› wrangler publish
 ⛅️ wrangler 0.0.0-893830aa
Retrieving cached values for account from ../../../node_modules/.cache/wrangler
Your worker has access to the following bindings:
- Services:
  - get: todo-get
  - delete: todo-delete
  - create: todo-create
  - update: todo-update
  - list: todo-list
Total Upload: 1.21 KiB / gzip: 0.42 KiB
Uploaded todo-gateway (0.62 sec)
Published todo-gateway (0.51 sec)
  todos.radiobox.tv (custom domain - zone name: radiobox.tv)

Natively Global

Since it’s built natively on Cloudflare, you can also include Cloudflare’s security suite in front of the application. If we want to prevent SQL Injection attacks for this endpoint, we can enable the appropriate Managed WAF rules on our todos API endpoint. Alternatively, if we wanted to prevent global access to our API (only allowing privileged clients to access the application), we can simply put Cloudflare Access in front, with custom Access Rules.

Going originless with Cloudflare Workers – Building a Todo app – Part 1: The API

With Custom Domains on Workers, you’re able to easily create applications that are native to Cloudflare’s global network, instantly. Best of all, your developers don’t need to worry about maintaining DNS records or certificate renewal – Cloudflare handles it all on their behalf. We’d like to give a huge shout out to the 5,000+ developers who used Custom Domains during the open beta period, and those that gave feedback along the way to make this possible. Can’t wait to see what you build next! As always, if you have any questions or would like to get involved, please join us on Discord.

Tune in next time to see how we can build a frontend for our application. In the meantime, you can play around with the todos API we built today at todos.radiobox.tv.