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  1. Terraform v5.9 now available

    Cloudflare Fundamentals Terraform

    Earlier this year, we announced the launch of the new Terraform v5 Provider. We are aware of the high number of issues ↗ reported by the Cloudflare community related to the v5 release. We have committed to releasing improvements on a 2 week cadence to ensure its stability and reliability, including the v5.9 release. We have also pivoted from an issue-to-issue approach to a resource-per-resource approach - we will be focusing on specific resources for every release, stabilizing the release, and closing all associated bugs with that resource before moving onto resolving migration issues.

    Thank you for continuing to raise issues. We triage them weekly and they help make our products stronger.

    This release includes a new resource, cloudflare_snippet, which replaces cloudflare_snippets. cloudflare_snippet is now considered deprecated but can still be used. Please utilize cloudflare_snippet as soon as possible.

    Changes

    • Resources stabilized:
      • cloudflare_zone_setting
      • cloudflare_worker_script
      • cloudflare_worker_route
      • tiered_cache
    • NEW resource cloudflare_snippet which should be used in place of cloudflare_snippets. cloudflare_snippets is now deprecated. This enables the management of Cloudflare's snippet functionality through Terraform.
    • DNS Record Improvements: Enhanced handling of DNS record drift detection
    • Load Balancer Fixes: Resolved created_on field inconsistencies and improved pool configuration handling
    • Bot Management: Enhanced auto-update model state consistency and fight mode configurations
    • Other bug fixes

    For a more detailed look at all of the changes, refer to the changelog ↗ in GitHub.

    Issues Closed

    If you have an unaddressed issue with the provider, we encourage you to check the open issues ↗ and open a new issue if one does not already exist for what you are experiencing.

    Upgrading

    We suggest holding off on migration to v5 while we work on stabilization. This help will you avoid any blocking issues while the Terraform resources are actively being stabilized.

    If you'd like more information on migrating from v4 to v5, please make use of the migration guide ↗. We have provided automated migration scripts using Grit which simplify the transition. These do not support implementations which use Terraform modules, so customers making use of modules need to migrate manually. Please make use of terraform plan to test your changes before applying, and let us know if you encounter any additional issues by reporting to our GitHub repository ↗.

    For more info

  1. Deepgram and Leonardo partner models now available on Workers AI

    Workers AI

    New state-of-the-art models have landed on Workers AI! This time, we're introducing new partner models trained by our friends at Deepgram ↗ and Leonardo ↗, hosted on Workers AI infrastructure.

    As well, we're introuding a new turn detection model that enables you to detect when someone is done speaking — useful for building voice agents!

    Read the blog ↗ for more details and check out some of the new models on our platform:

    You can filter out new partner models with the Partner capability on our Models page.

    As well, we're introducing WebSocket support for some of our audio models, which you can filter though the Realtime capability on our Models page. WebSockets allows you to create a bi-directional connection to our inference server with low latency — perfect for those that are building voice agents.

    An example python snippet on how to use WebSockets with our new Aura model:

    import json
    import os
    import asyncio
    import websockets
    

    uri = f"wss://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/deepgram/aura-1"
    

    input = [
        "Line one, out of three lines that will be provided to the aura model.",
        "Line two, out of three lines that will be provided to the aura model.",
        "Line three, out of three lines that will be provided to the aura model. This is a last line.",
    ]
    

    

    async def text_to_speech():
        async with websockets.connect(uri, additional_headers={"Authorization": os.getenv("CF_TOKEN")}) as websocket:
            print("connection established")
            for line in input:
                print(f"sending `{line}`")
                await websocket.send(json.dumps({"type": "Speak", "text": line}))
    

                print("line was sent, flushing")
                await websocket.send(json.dumps({"type": "Flush"}))
                print("flushed, recving")
                resp = await websocket.recv()
                print(f"response received {resp}")
    

    

    if __name__ == "__main__":
        asyncio.run(text_to_speech())

  1. List all vectors in a Vectorize index with the new list-vectors operation

    Vectorize

    You can now list all vector identifiers in a Vectorize index using the new list-vectors operation. This enables bulk operations, auditing, and data migration workflows through paginated requests that maintain snapshot consistency.

    The operation is available via Wrangler CLI and REST API. Refer to the list-vectors best practices guide for detailed usage guidance.

  1. Manage and deploy your AI provider keys through Bring Your Own Key (BYOK) with AI Gateway, now powered by Cloudflare Secrets Store

    Secrets Store AI Gateway SSL/TLS

    Cloudflare Secrets Store is now integrated with AI Gateway, allowing you to store, manage, and deploy your AI provider keys in a secure and seamless configuration through Bring Your Own Key ↗. Instead of passing your AI provider keys directly in every request header, you can centrally manage each key with Secrets Store and deploy in your gateway configuration using only a reference, rather than passing the value in plain text.

    You can now create a secret directly from your AI Gateway in the dashboard ↗ by navigating into your gateway -> Provider Keys -> Add.

    Import repo or choose template

    You can also create your secret with the newly available ai_gateway scope via wrangler ↗, the Secrets Store dashboard ↗, or the API ↗.

    Then, pass the key in the request header using its Secrets Store reference:

    curl -X POST https://gateway.ai.cloudflare.com/v1/<ACCOUNT_ID>/my-gateway/anthropic/v1/messages \
     --header 'cf-aig-authorization: ANTHROPIC_KEY_1 \
     --header 'anthropic-version: 2023-06-01' \
     --header 'Content-Type: application/json' \
     --data  '{"model": "claude-3-opus-20240229", "messages": [{"role": "user", "content": "What is Cloudflare?"}]}'

    Or, using Javascript:

    import Anthropic from '@anthropic-ai/sdk';
    

    

    const anthropic = new Anthropic({
     apiKey: "ANTHROPIC_KEY_1",
     baseURL: "https://gateway.ai.cloudflare.com/v1/<ACCOUNT_ID>/my-gateway/anthropic",
    });
    

    

    const message = await anthropic.messages.create({
     model: 'claude-3-opus-20240229',
     messages: [{role: "user", content: "What is Cloudflare?"}],
     max_tokens: 1024
    });

    For more information, check out the blog ↗!

  1. Content type returned in Workers Assets for Javascript files is now `text/javascript`

    Workers

    JavaScript asset responses have been updated to use the text/javascript Content-Type header instead of application/javascript. While both MIME types are widely supported by browsers, the HTML Living Standard explicitly recommends text/javascript as the preferred type going forward.

    This change improves:

    • Standards alignment: Ensures consistency with the HTML spec and modern web platform guidance.
    • Interoperability: Some developer tools, validators, and proxies expect text/javascript and may warn or behave inconsistently with application/javascript.
    • Future-proofing: By following the spec-preferred MIME type, we reduce the risk of deprecation warnings or unexpected behavior in evolving browser environments.
    • Consistency: Most frameworks, CDNs, and hosting providers now default to text/javascript, so this change matches common ecosystem practice.

    Because all major browsers accept both MIME types, this update is backwards compatible and should not cause breakage.

    Users will see this change on the next deployment of their assets.

  1. Workers KV completes hybrid storage provider rollout for improved performance, fault-tolerance

    KV

    Workers KV has completed rolling out performance improvements across all KV namespaces, providing a significant latency reduction on read operations for all KV users. This is due to architectural changes to KV's underlying storage infrastructure, which introduces a new metadata later and substantially improves redundancy.

    Workers KV latency improvements showing P95 and P99 performance gains in Europe, Asia, Africa and Middle East regions as measured within KV's internal storage gateway worker.

    Performance improvements

    The new hybrid architecture delivers substantial latency reductions throughout Europe, Asia, Middle East, Africa regions. Over the past 2 weeks, we have observed the following:

    • p95 latency: Reduced from ~150ms to ~50ms (67% decrease)
    • p99 latency: Reduced from ~350ms to ~250ms (29% decrease)

  1. Build durable multi-step applications in Python with Workflows (now in beta)

    Workflows Workers

    You can now build Workflows using Python. With Python Workflows, you get automatic retries, state persistence, and the ability to run multi-step operations that can span minutes, hours, or weeks using Python’s familiar syntax and the Python Workers runtime.

    Python Workflows use the same step-based execution model as JavaScript Workflows, but with Python syntax and access to Python’s ecosystem. Python Workflows also enable DAG (Directed Acyclic Graph) workflows, where you can define complex dependencies between steps using the depends parameter.

    Here’s a simple example:

    Python
    from workers import Response, WorkflowEntrypoint
    

    class PythonWorkflowStarter(WorkflowEntrypoint):
        async def run(self, event, step):
            @step.do("my first step")
            async def my_first_step():
                # do some work
                return "Hello Python!"
    

            await my_first_step()
    

            await step.sleep("my-sleep-step", "10 seconds")
    

            @step.do("my second step")
            async def my_second_step():
                # do some more work
                return "Hello again!"
    

            await my_second_step()
    

    class Default(WorkerEntrypoint):
        async def fetch(self, request):
            await self.env.MY_WORKFLOW.create()
            return Response("Hello Workflow creation!")

    Python Workflows support the same core capabilities as JavaScript Workflows, including sleep scheduling, event-driven workflows, and built-in error handling with configurable retry policies.

    To learn more and get started, refer to Python Workflows documentation.

  1. New getByName() API to access Durable Objects

    Durable Objects Workers

    You can now create a client (a Durable Object stub) to a Durable Object with the new getByName method, removing the need to convert Durable Object names to IDs and then create a stub.

    JavaScript
    // Before: (1) translate name to ID then (2) get a client
    const objectId = env.MY_DURABLE_OBJECT.idFromName("foo"); // or .newUniqueId()
    const stub = env.MY_DURABLE_OBJECT.get(objectId);
    

    // Now: retrieve client to Durable Object directly via its name
    const stub = env.MY_DURABLE_OBJECT.getByName("foo");
    

    // Use client to send request to the remote Durable Object
    const rpcResponse = await stub.sayHello();

    Each Durable Object has a globally-unique name, which allows you to send requests to a specific object from anywhere in the world. Thus, a Durable Object can be used to coordinate between multiple clients who need to work together. You can have billions of Durable Objects, providing isolation between application tenants.

    To learn more, visit the Durable Objects API Documentation or the getting started guide.

  1. Subscribe to events from Cloudflare services with Queues

    Queues

    You can now subscribe to events from other Cloudflare services (for example, Workers KV, Workers AI, Workers) and consume those events via Queues, allowing you to build custom workflows, integrations, and logic in response to account activity.

    Event subscriptions architecture

    Event subscriptions allow you to receive messages when events occur across your Cloudflare account. Cloudflare products can publish structured events to a queue, which you can then consume with Workers or pull via HTTP from anywhere.

    To create a subscription, use the dashboard or Wrangler:

    Terminal window
    npx wrangler queues subscription create my-queue --source r2 --events bucket.created

    An event is a structured record of something happening in your Cloudflare account – like a Workers AI batch request being queued, a Worker build completing, or an R2 bucket being created. Events follow a consistent structure:

    Example R2 bucket created event
    {
      "type": "cf.r2.bucket.created",
      "source": {
        "type": "r2"
      },
      "payload": {
        "name": "my-bucket",
        "location": "WNAM"
      },
      "metadata": {
        "accountId": "f9f79265f388666de8122cfb508d7776",
        "eventTimestamp": "2025-07-28T10:30:00Z"
      }
    }

    Current event sources include R2, Workers KV, Workers AI, Workers Builds, Vectorize, Super Slurper, and Workflows. More sources and events are on the way.

    For more information on event subscriptions, available events, and how to get started, refer to our documentation.

  1. Easier debugging in Workers with improved Wrangler error screen

    Workers

    Wrangler's error screen has received several improvements to enhance your debugging experience!

    The error screen now features a refreshed design thanks to youch ↗, with support for both light and dark themes, improved source map resolution logic that handles missing source files more reliably, and better error cause display.

    BeforeAfter (Light)After (Dark)
    Old error screenNew light theme error screenNew dark theme error screen

    Try it out now with npx wrangler@latest dev in your Workers project.

  1. Terraform v5.8.4 now available

    Cloudflare Fundamentals Terraform

    Earlier this year, we announced the launch of the new Terraform v5 Provider. We are aware of the high number of issues ↗ reported by the Cloudflare Community related to the v5 release. We have committed to releasing improvements on a two week cadence to ensure stability and reliability.

    One key change we adopted in recent weeks is a pivot to more comprehensive, test-driven development. We are still evaluating individual issues, but are also investing in much deeper testing to drive our stabilization efforts. We will subsequently be investing in comprehensive migration scripts. As a result, you will see several of the highest traffic APIs have been stabilized in the most recent release, and are supported by comprehensive acceptance tests.

    Thank you for continuing to raise issues. We triage them weekly and they help make our products stronger.

    Changes

    • Resources stabilized:
      • cloudflare_argo_smart_routing
      • cloudflare_bot_management
      • cloudflare_list
      • cloudflare_list_item
      • cloudflare_load_balancer
      • cloudflare_load_balancer_monitor
      • cloudflare_load_balancer_pool
      • cloudflare_spectrum_application
      • cloudflare_managed_transforms
      • cloudflare_url_normalization_settings
      • cloudflare_snippet
      • cloudflare_snippet_rules
      • cloudflare_zero_trust_access_application
      • cloudflare_zero_trust_access_group
      • cloudflare_zero_trust_access_identity_provider
      • cloudflare_zero_trust_access_mtls_certificate
      • cloudflare_zero_trust_access_mtls_hostname_settings
      • cloudflare_zero_trust_access_policy
      • cloudflare_zone
    • Multipart handling restored for cloudflare_snippet
    • cloudflare_bot_management diff issues resolves when running terraform plan and terraform apply
    • Other bug fixes

    For a more detailed look at all of the changes, refer to the changelog ↗ in GitHub.

    Issues Closed

    If you have an unaddressed issue with the provider, we encourage you to check the open issues ↗ and open a new one if one does not already exist for what you are experiencing.

    Upgrading

    We suggest holding off on migration to v5 while we work on stabilization. This will help you avoid any blocking issues while the Terraform resources are actively being stabilized.

    If you'd like more information on migrating to v5, please make use of the migration guide ↗. We have provided automated migration scripts using Grit which simplify the transition. These migration scripts do not support implementations which use Terraform modules, so customers making use of modules need to migrate manually. Please make use of terraform plan to test your changes before applying, and let us know if you encounter any additional issues by reporting to our GitHub repository ↗.

    For more info

  1. The Node.js and Web File System APIs in Workers

    Workers

    Implementations of the node:fs module ↗ and the Web File System API ↗ are now available in Workers.

    Using the node:fs module

    The node:fs module provides access to a virtual file system in Workers. You can use it to read and write files, create directories, and perform other file system operations.

    The virtual file system is ephemeral with each individual request havig its own isolated temporary file space. Files written to the file system will not persist across requests and will not be shared across requests or across different Workers.

    Workers running with the nodejs_compat compatibility flag will have access to the node:fs module by default when the compatibility date is set to 2025-09-01 or later. Support for the API can also be enabled using the enable_nodejs_fs_module compatibility flag together with the nodejs_compat flag. The node:fs module can be disabled using the disable_nodejs_fs_module compatibility flag.

    JavaScript
    import fs from "node:fs";
    

    const config = JSON.parse(fs.readFileSync("/bundle/config.json", "utf-8"));
    

    export default {
      async fetch(request) {
        return new Response(`Config value: ${config.value}`);
      },
    };

    There are a number of initial limitations to the node:fs implementation:

    • The glob APIs (e.g. fs.globSync(...)) are not implemented.
    • The file watching APIs (e.g. fs.watch(...)) are not implemented.
    • The file timestamps (modified time, access time, etc) are only partially supported. For now, these will always return the Unix epoch.

    Refer to the Node.js documentation ↗ for more information on the node:fs module and its APIs.

    The Web File System API

    The Web File System API provides access to the same virtual file system as the node:fs module, but with a different API surface. The Web File System API is only available in Workers running with the enable_web_file_system compatibility flag. The nodejs_compat compatibility flag is not required to use the Web File System API.

    JavaScript
    const root = navigator.storage.getDirectory();
    

    export default {
      async fetch(request) {
        const tmp = await root.getDirectoryHandle("/tmp");
        const file = await tmp.getFileHandle("data.txt", { create: true });
        const writable = await file.createWritable();
        const writer = writable.getWriter();
        await writer.write("Hello, World!");
        await writer.close();
    

        return new Response("File written successfully!");
      },
    };

    As there are still some parts of the Web File System API that are not fully standardized, there may be some differences between the Workers implementation and the implementations in browsers.

  1. Workers Static Assets: Corrected handling of double slashes in redirect rule paths

    Workers

    Static Assets: Fixed a bug in how redirect rules ↗ defined in your Worker's _redirects file are processed.

    If you're serving Static Assets with a _redirects file containing a rule like /ja/* /:splat, paths with double slashes were previously misinterpreted as external URLs. For example, visiting /ja//example.com would incorrectly redirect to https://example.com instead of /example.com on your domain. This has been fixed and double slashes now correctly resolve as local paths. Note: Cloudflare Pages was not affected by this issue.

  1. Workers per-branch preview URLs now support long branch names

    Workers

    We've updated preview URLs for Cloudflare Workers to support long branch names.

    Previously, branch and Worker names exceeding the 63-character DNS limit would cause alias generation to fail, leaving pull requests without aliased preview URLs. This particularly impacted teams relying on descriptive branch naming.

    Now, Cloudflare automatically truncates long branch names and appends a unique hash, ensuring every pull request gets a working preview link.

    How it works

    • 63 characters or less: <branch-name>-<worker-name> → Uses actual branch name as is
    • 64 characters or more: <truncated-branch-name>--<hash>-<worker-name> → Uses truncated name with 4-character hash
    • Hash generation: The hash is derived from the full branch name to ensure uniqueness
    • Stable URLs: The same branch always generates the same hash across all commits

    Requirements and compatibility

    • Wrangler 4.30.0 or later: This feature requires updating to wrangler@4.30.0+
    • No configuration needed: Works automatically with existing preview URL setups

  1. Python Workers handlers now live in an entrypoint class

    Workers

    We are changing how Python Workers are structured by default. Previously, handlers were defined at the top-level of a module as on_fetch, on_scheduled, etc. methods, but now they live in an entrypoint class.

    Here's an example of how to now define a Worker with a fetch handler:

    Python
    from workers import Response, WorkerEntrypoint
    

    class Default(WorkerEntrypoint):
        async def fetch(self, request):
            return Response("Hello World!")

    To keep using the old-style handlers, you can specify the disable_python_no_global_handlers compatibility flag in your wrangler file:

    JSONC
    {
      "compatibility_flags": [
        "disable_python_no_global_handlers"
      ]
    }

    Consult the Python Workers documentation for more details.

  1. Terraform provider improvements — Python Workers support, smaller plan diffs, and API SDK fixes

    Workers

    The recent Cloudflare Terraform Provider ↗ and SDK releases (such as cloudflare-typescript ↗) bring significant improvements to the Workers developer experience. These updates focus on reliability, performance, and adding Python Workers support.

    Terraform Improvements

    Fixed Unwarranted Plan Diffs

    Resolved several issues with the cloudflare_workers_script resource that resulted in unwarranted plan diffs, including:

    • Using Durable Objects migrations
    • Using some bindings such as secret_text
    • Using smart placement

    A resource should never show a plan diff if there isn't an actual change. This fix reduces unnecessary noise in your Terraform plan and is available in Cloudflare Terraform Provider 5.8.0.

    Improved File Management

    You can now specify content_file and content_sha256 instead of content. This prevents the Workers script content from being stored in the state file which greatly reduces plan diff size and noise. If your workflow synced plans remotely, this should now happen much faster since there is less data to sync. This is available in Cloudflare Terraform Provider 5.7.0.

    resource "cloudflare_workers_script" "my_worker" {
      account_id      = "123456789"
      script_name     = "my_worker"
      main_module     = "worker.mjs"
      content_file    = "worker.mjs"
      content_sha256  = filesha256("worker.mjs")
    }

    Assets Headers and Redirects Support

    Fixed the cloudflare_workers_script resource to properly support headers and redirects for Assets:

    resource "cloudflare_workers_script" "my_worker" {
      account_id      = "123456789"
      script_name     = "my_worker"
      main_module     = "worker.mjs"
      content_file    = "worker.mjs"
      content_sha256  = filesha256("worker.mjs")
      assets = {
        config = {
          headers = file("_headers")
          redirects = file("_redirects")
        }
        # Completion jwt from:
        # https://developers.cloudflare.com/api/resources/workers/subresources/assets/subresources/upload/
        jwt = "jwt"
      }
    }

    Available in Cloudflare Terraform Provider 5.8.0.

    Python Workers Support

    Added support for uploading Python Workers (beta) in Terraform. You can now deploy Python Workers with:

    resource "cloudflare_workers_script" "my_worker" {
      account_id       = "123456789"
      script_name      = "my_worker"
      content_file     = "worker.py"
      content_sha256   = filesha256("worker.py")
      content_type     = "text/x-python"
    }

    Available in Cloudflare Terraform Provider 5.8.0.

    SDK Enhancements

    Improved File Upload API

    Fixed an issue where Workers script versions in the SDK did not allow uploading files. This now works, and also has an improved files upload interface:

    JavaScript
    const scriptContent = `
      export default {
        async fetch(request, env, ctx) {
          return new Response('Hello World!', { status: 200 });
        }
      };
    `;
    

    client.workers.scripts.versions.create('my-worker', {
      account_id: '123456789',
      metadata: {
        main_module: 'my-worker.mjs',
      },
      files: [
        await toFile(
          Buffer.from(scriptContent),
          'my-worker.mjs',
          {
            type: "application/javascript+module",
          }
        )
      ]
    });

    Will be available in cloudflare-typescript 4.6.0. A similar change will be available in cloudflare-python 4.4.0.

    Fixed updating KV values

    Previously when creating a KV value like this:

    JavaScript
    await cf.kv.namespaces.values.update("my-kv-namespace", "key1", {
      account_id: "123456789",
      metadata: "my metadata",
      value: JSON.stringify({
        hello: "world"
      })
    });

    ...and recalling it in your Worker like this:

    TypeScript
    const value = await c.env.KV.get<{hello: string}>("key1", "json");

    You'd get back this: {metadata:'my metadata', value:"{'hello':'world'}"} instead of the correct value of {hello: 'world'}

    This is fixed in cloudflare-typescript 4.5.0 and will be fixed in cloudflare-python 4.4.0.

  1. MessageChannel and MessagePort

    Workers

    A minimal implementation of the MessageChannel API ↗ is now available in Workers. This means that you can use MessageChannel to send messages between different parts of your Worker, but not across different Workers.

    The MessageChannel and MessagePort APIs will be available by default at the global scope with any worker using a compatibility date of 2025-08-15 or later. It is also available using the expose_global_message_channel compatibility flag, or can be explicitly disabled using the no_expose_global_message_channel compatibility flag.

    JavaScript
    const { port1, port2 } = new MessageChannel();
    

    port2.onmessage = (event) => {
      console.log('Received message:', event.data);
    };
    

    port2.postMessage('Hello from port2!');

    Any value that can be used with the structuredClone(...) API can be sent over the port.

    Differences

    There are a number of key limitations to the MessageChannel API in Workers:

    • Transfer lists are currently not supported. This means that you will not be able to transfer ownership of objects like ArrayBuffer or MessagePort between ports.
    • The MessagePort is not yet serializable. This means that you cannot send a MessagePort object through the postMessage method or via JSRPC calls.
    • The 'messageerror' event is only partially supported. If the 'onmessage' handler throws an error, the 'messageerror' event will be triggered, however, it will not be triggered when there are errors serializing or deserializing the message data. Instead, the error will be thrown when the postMessage method is called on the sending port.
    • The 'close' event will be emitted on both ports when one of the ports is closed, however it will not be emitted when the Worker is terminated or when one of the ports is garbage collected.

  1. Wrangler and the Cloudflare Vite plugin support `.env` files in local development

    Workers

    Now, you can use .env files to provide secrets and override environment variables on the env object during local development with Wrangler and the Cloudflare Vite plugin.

    Previously in local development, if you wanted to provide secrets or environment variables during local development, you had to use .dev.vars files. This is still supported, but you can now also use .env files, which are more familiar to many developers.

    Using .env files in local development

    You can create a .env file in your project root to define environment variables that will be used when running wrangler dev or vite dev. The .env file should be formatted like a dotenv file, such as KEY="VALUE":

    .env
    TITLE="My Worker"
    API_TOKEN="dev-token"

    When you run wrangler dev or vite dev, the environment variables defined in the .env file will be available in your Worker code via the env object:

    JavaScript
    export default {
      async fetch(request, env) {
        const title = env.TITLE; // "My Worker"
        const apiToken = env.API_TOKEN; // "dev-token"
        const response = await fetch(
          `https://api.example.com/data?token=${apiToken}`,
        );
        return new Response(`Title: ${title} - ` + (await response.text()));
      },
    };

    Multiple environments with .env files

    If your Worker defines multiple environments, you can set different variables for each environment (ex: production or staging) by creating files named .env.<environment-name>.

    When you use wrangler <command> --env <environment-name> or CLOUDFLARE_ENV=<environment-name> vite dev, the corresponding environment-specific file will also be loaded and merged with the .env file.

    For example, if you want to set different environment variables for the staging environment, you can create a file named .env.staging:

    .env.staging
    API_TOKEN="staging-token"

    When you run wrangler dev --env staging or CLOUDFLARE_ENV=staging vite dev, the environment variables from .env.staging will be merged onto those from .env.

    JavaScript
    export default {
      async fetch(request, env) {
        const title = env.TITLE; // "My Worker" (from `.env`)
        const apiToken = env.API_TOKEN; // "staging-token" (from `.env.staging`, overriding the value from `.env`)
        const response = await fetch(
          `https://api.example.com/data?token=${apiToken}`,
        );
        return new Response(`Title: ${title} - ` + (await response.text()));
      },
    };

    Find out more

    For more information on how to use .env files with Wrangler and the Cloudflare Vite plugin, see the following documentation:

  1. Introducing observability and metrics for Stream Live Inputs

    Stream

    New information about broadcast metrics and events is now available in Cloudflare Stream in the Live Input details of the Dashboard.

    Live Input details showing metrics

    You can now easily understand broadcast-side health and performance with new observability, which can help when troubleshooting common issues, particularly for new customers who are just getting started, and platform customers who may have limited visibility into how their end-users configure their encoders.

    To get started, start a live stream (just getting started?), then visit the Live Input details page in Dash.

    See our new live Troubleshooting guide to learn what these metrics mean and how to use them to address common broadcast issues.

  1. Directly import `waitUntil` in Workers for easily spawning background tasks

    Workers

    You can now import waitUntil from cloudflare:workers to extend your Worker's execution beyond the request lifecycle from anywhere in your code.

    Previously, waitUntil could only be accessed through the execution context (ctx) parameter passed to your Worker's handler functions. This meant that if you needed to schedule background tasks from deeply nested functions or utility modules, you had to pass the ctx object through multiple function calls to access waitUntil.

    Now, you can import waitUntil directly and use it anywhere in your Worker without needing to pass ctx as a parameter:

    JavaScript
    import { waitUntil } from "cloudflare:workers";
    

    export function trackAnalytics(eventData) {
      const analyticsPromise = fetch("https://analytics.example.com/track", {
        method: "POST",
        body: JSON.stringify(eventData),
      });
    

      // Extend execution to ensure analytics tracking completes
      waitUntil(analyticsPromise);
    }

    This is particularly useful when you want to:

    • Schedule background tasks from utility functions or modules
    • Extend execution for analytics, logging, or cleanup operations
    • Avoid passing the execution context through multiple layers of function calls
    JavaScript
    import { waitUntil } from "cloudflare:workers";
    

    export default {
      async fetch(request, env, ctx) {
        // Background task that should complete even after response is sent
        cleanupTempData(env.KV_NAMESPACE);
        return new Response("Hello, World!");
      }
    };
    

    function cleanupTempData(kvNamespace) {
      // This function can now use waitUntil without needing ctx
      const deletePromise = kvNamespace.delete("temp-key");
      waitUntil(deletePromise);
    }

    For more information, see the waitUntil documentation.

  1. Requests made from Cloudflare Workers can now force a revalidation of their cache with the origin

    Workers

    By setting the value of the cache property to no-cache, you can force Cloudflare's cache to revalidate its contents with the origin when making subrequests from Cloudflare Workers.

    index.js
    export default {
      async fetch(req, env, ctx) {
        const request = new Request("https://cloudflare.com", {
          cache: "no-cache",
        });
        const response = await fetch(request);
        return response;
      },
    };

    When no-cache is set, the Worker request will first look for a match in Cloudflare's cache, then:

    • If there is a match, a conditional request is sent to the origin, regardless of whether or not the match is fresh or stale. If the resource has not changed, the cached version is returned. If the resource has changed, it will be downloaded from the origin, updated in the cache, and returned.
    • If there is no match, Workers will make a standard request to the origin and cache the response.

    This increases compatibility with NPM packages and JavaScript frameworks that rely on setting the cache property, which is a cross-platform standard part of the Request interface. Previously, if you set the cache property on Request to 'no-cache', the Workers runtime threw an exception.

  1. Agents SDK adds MCP Elicitation support, http-streamable support, task queues, email integration and more

    Agents Workers

    The latest releases of @cloudflare/agents ↗ brings major improvements to MCP transport protocols support and agents connectivity. Key updates include:

    MCP elicitation support

    MCP servers can now request user input during tool execution, enabling interactive workflows like confirmations, forms, and multi-step processes. This feature uses durable storage to preserve elicitation state even during agent hibernation, ensuring seamless user interactions across agent lifecycle events.

    TypeScript
    // Request user confirmation via elicitation
    const confirmation = await this.elicitInput({
      message: `Are you sure you want to increment the counter by ${amount}?`,
      requestedSchema: {
        type: "object",
        properties: {
          confirmed: {
            type: "boolean",
            title: "Confirm increment",
            description: "Check to confirm the increment",
          },
        },
        required: ["confirmed"],
      },
    });

    Check out our demo ↗ to see elicitation in action.

    HTTP streamable transport for MCP

    MCP now supports HTTP streamable transport which is recommended over SSE. This transport type offers:

    • Better performance: More efficient data streaming and reduced overhead
    • Improved reliability: Enhanced connection stability and error recover- Automatic fallback: If streamable transport is not available, it gracefully falls back to SSE
    TypeScript
    export default MyMCP.serve("/mcp", {
      binding: "MyMCP",
    });

    The SDK automatically selects the best available transport method, gracefully falling back from streamable-http to SSE when needed.

    Enhanced MCP connectivity

    Significant improvements to MCP server connections and transport reliability:

    • Auto transport selection: Automatically determines the best transport method, falling back from streamable-http to SSE as needed
    • Improved error handling: Better connection state management and error reporting for MCP servers
    • Reliable prop updates: Centralized agent property updates ensure consistency across different contexts

    Lightweight .queue for fast task deferral

    You can use .queue() to enqueue background work — ideal for tasks like processing user messages, sending notifications etc.

    TypeScript
    class MyAgent extends Agent {
      doSomethingExpensive(payload) {
        // a long running process that you want to run in the background
      }
    

      queueSomething() {
        await this.queue("doSomethingExpensive", somePayload); // this will NOT block further execution, and runs in the background
        await this.queue("doSomethingExpensive", someOtherPayload); // the callback will NOT run until the previous callback is complete
        // ... call as many times as you want
      }
    }

    Want to try it yourself? Just define a method like processMessage in your agent, and you’re ready to scale.

    New email adapter

    Want to build an AI agent that can receive and respond to emails automatically? With the new email adapter and onEmail lifecycle method, now you can.

    TypeScript
    export class EmailAgent extends Agent {
      async onEmail(email: AgentEmail) {
        const raw = await email.getRaw();
        const parsed = await PostalMime.parse(raw);
    

        // create a response based on the email contents
        // and then send a reply
    

        await this.replyToEmail(email, {
          fromName: "Email Agent",
          body: `Thanks for your email! You've sent us "${parsed.subject}". We'll process it shortly.`,
        });
      }
    }

    You route incoming mail like this:

    TypeScript
    export default {
      async email(email, env) {
        await routeAgentEmail(email, env, {
          resolver: createAddressBasedEmailResolver("EmailAgent"),
        });
      },
    };

    You can find a full example here ↗.

    Automatic context wrapping for custom methods

    Custom methods are now automatically wrapped with the agent's context, so calling getCurrentAgent() should work regardless of where in an agent's lifecycle it's called. Previously this would not work on RPC calls, but now just works out of the box.

    TypeScript
    export class MyAgent extends Agent {
      async suggestReply(message) {
        // getCurrentAgent() now correctly works, even when called inside an RPC method
        const { agent } = getCurrentAgent()!;
        return generateText({
          prompt: `Suggest a reply to: "${message}" from "${agent.name}"`,
          tools: [replyWithEmoji],
        });
      }
    }

    Try it out and tell us what you build!

  1. Cloudflare Sandbox SDK adds streaming, code interpreter, Git support, process control and more

    Agents Workers

    We’ve shipped a major release for the @cloudflare/sandbox ↗ SDK, turning it into a full-featured, container-based execution platform that runs securely on Cloudflare Workers.

    This update adds live streaming of output, persistent Python and JavaScript code interpreters with rich output support (charts, tables, HTML, JSON), file system access, Git operations, full background process control, and the ability to expose running services via public URLs.

    This makes it ideal for building AI agents, CI runners, cloud REPLs, data analysis pipelines, or full developer tools — all without managing infrastructure.

    Code interpreter (Python, JS, TS)

    Create persistent code contexts with support for rich visual + structured outputs.

    createCodeContext(options)

    Creates a new code execution context with persistent state.

    TypeScript
    // Create a Python context
    const pythonCtx = await sandbox.createCodeContext({ language: "python" });
    

    // Create a JavaScript context
    const jsCtx = await sandbox.createCodeContext({ language: "javascript" });

    Options:

    • language: Programming language ('python' | 'javascript' | 'typescript')
    • cwd: Working directory (default: /workspace)
    • envVars: Environment variables for the context

    runCode(code, options)

    Executes code with optional streaming callbacks.

    TypeScript
    // Simple execution
    const execution = await sandbox.runCode('print("Hello World")', {
      context: pythonCtx,
    });
    

    // With streaming callbacks
    await sandbox.runCode(
      `
    for i in range(5):
        print(f"Step {i}")
        time.sleep(1)
    `,
      {
        context: pythonCtx,
        onStdout: (output) => console.log("Real-time:", output.text),
        onResult: (result) => console.log("Result:", result),
      },
    );

    Options:

    • language: Programming language ('python' | 'javascript' | 'typescript')
    • cwd: Working directory (default: /workspace)
    • envVars: Environment variables for the context

    Real-time streaming output

    Returns a streaming response for real-time processing.

    TypeScript
    const stream = await sandbox.runCodeStream(
      "import time; [print(i) for i in range(10)]",
    );
    // Process the stream as needed

    Rich output handling

    Interpreter outputs are auto-formatted and returned in multiple formats:

    • text
    • html (e.g., Pandas tables)
    • png, svg (e.g., Matplotlib charts)
    • json (structured data)
    • chart (parsed visualizations)
    TypeScript
    const result = await sandbox.runCode(
      `
    import seaborn as sns
    import matplotlib.pyplot as plt
    

    data = sns.load_dataset("flights")
    pivot = data.pivot("month", "year", "passengers")
    sns.heatmap(pivot, annot=True, fmt="d")
    plt.title("Flight Passengers")
    plt.show()
    

    pivot.to_dict()
    `,
      { context: pythonCtx },
    );
    

    if (result.png) {
      console.log("Chart output:", result.png);
    }

    Preview URLs from Exposed Ports

    Start background processes and expose them with live URLs.

    TypeScript
    await sandbox.startProcess("python -m http.server 8000");
    const preview = await sandbox.exposePort(8000);
    

    console.log("Live preview at:", preview.url);

    Full process lifecycle control

    Start, inspect, and terminate long-running background processes.

    TypeScript
    const process = await sandbox.startProcess("node server.js");
    console.log(`Started process ${process.id} with PID ${process.pid}`);
    

    // Monitor the process
    const logStream = await sandbox.streamProcessLogs(process.id);
    for await (const log of parseSSEStream<LogEvent>(logStream)) {
      console.log(`Server: ${log.data}`);
    }
    • listProcesses() - List all running processes
    • getProcess(id) - Get detailed process status
    • killProcess(id, signal) - Terminate specific processes
    • killAllProcesses() - Kill all processes
    • streamProcessLogs(id, options) - Stream logs from running processes
    • getProcessLogs(id) - Get accumulated process output

    Git integration

    Clone Git repositories directly into the sandbox.

    TypeScript
    await sandbox.gitCheckout("https://github.com/user/repo", {
      branch: "main",
      targetDir: "my-project",
    });

    Sandboxes are still experimental. We're using them to explore how isolated, container-like workloads might scale on Cloudflare — and to help define the developer experience around them.

  1. OpenAI open models now available on Workers AI

    Agents Workers AI

    We're thrilled to be a Day 0 partner with OpenAI ↗ to bring their latest open models ↗ to Workers AI, including support for Responses API, Code Interpreter, and Web Search (coming soon).

    Get started with the new models at @cf/openai/gpt-oss-120b and @cf/openai/gpt-oss-20b. Check out the blog ↗ for more details about the new models, and the gpt-oss-120b and gpt-oss-20b model pages for more information about pricing and context windows.

    Responses API

    If you call the model through:

    • Workers Binding, it will accept/return Responses API – env.AI.run(“@cf/openai/gpt-oss-120b”)
    • REST API on /run endpoint, it will accept/return Responses API – https://api.cloudflare.com/client/v4/accounts/<account_id>/ai/run/@cf/openai/gpt-oss-120b
    • REST API on new /responses endpoint, it will accept/return Responses API – https://api.cloudflare.com/client/v4/accounts/<account_id>/ai/v1/responses
    • REST API for OpenAI Compatible endpoint, it will return Chat Completions (coming soon) – https://api.cloudflare.com/client/v4/accounts/<account_id>/ai/v1/chat/completions
    curl https://api.cloudflare.com/client/v4/accounts/<account_id>/ai/v1/responses \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer $CLOUDFLARE_API_KEY" \
      -d '{
        "model": "@cf/openai/gpt-oss-120b",
        "reasoning": {"effort": "medium"},
        "input": [
          {
            "role": "user",
            "content": "What are the benefits of open-source models?"
          }
        ]
      }'

    Code Interpreter

    The model is natively trained to support stateful code execution, and we've implemented support for this feature using our Sandbox SDK ↗ and Containers ↗. Cloudflare's Developer Platform is uniquely positioned to support this feature, so we're very excited to bring our products together to support this new use case.

    Web Search (coming soon)

    We are working to implement Web Search for the model, where users can bring their own Exa API Key so the model can browse the Internet.

  1. Increased disk space for Workers Builds

    Workers

    As part of the ongoing open beta for Workers Builds, we’ve increased the available disk space for builds from 8 GB to 20 GB for both Free and Paid plans.

    This provides more space for larger projects, dependencies, and build artifacts while improving overall build reliability.

    MetricFree PlanPaid Plans
    Disk Space20 GB20 GB

    All other build limits — including CPU, memory, build minutes, and timeout remain unchanged.