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Improving Worker Tail scalability


4 min read

Being able to get real-time information from applications in production is extremely important. Many times software passes local testing and automation, but then users report that something isn’t working correctly. Being able to quickly see what is happening, and how often, is critical to debugging.

This is why we originally developed the Workers Tail feature - to allow developers the ability to view requests, exceptions, and information for their Workers and to provide a window into what’s happening in real time. When we developed it, we also took the opportunity to build it on top of our own Workers technology using products like Trace Workers and Durable Objects. Over the last couple of years, we’ve continued to iterate on this feature - allowing users to quickly access logs from the Dashboard and via Wrangler CLI.

Today, we’re excited to announce that tail can now be enabled for Workers at any size and scale! In addition to telling you about the new and improved scalability, we wanted to share how we built it, and the changes we made to enable it to scale better.

Why Tail was limited

Tail leverages Durable Objects to handle coordination between the Worker producing messages and consumers like wrangler and the Cloudflare dashboard, and Durable Objects are a great choice for handling real-time communication like this. However, when a single Durable Object instance starts to receive a very high volume of traffic - like the kind that can come with tailing live Workers - it can see some performance issues.

As a result, Workers with a high volume of traffic could not be supported by the original Tail infrastructure. Tail had to be limited to Workers receiving 100 requests/second (RPS) or less. This was a significant limitation that resulted in many users with large, high-traffic Workers having to turn to their own tooling to get proper observability in production.

Believing that every feature we provide should scale with users during their development journey, we set out to improve Tail's performance at high loads.

Updating the way filters work

The first improvement was to the existing filtering feature. When starting a Tail with wrangler tail (and now with the Cloudflare dashboard) users have the ability to filter out messages based on information in the requests or logs.
Previously, this filtering was handled within the Durable Object, which meant that even if a user was filtering out the majority of their traffic, the Durable Object would still have to handle every message. Often users with high traffic Tails were using many filters to better interpret their logs, but wouldn’t be able to start a Tail due to the 100 RPS limit.

We moved filtering out of the Durable Object and into the Tail message producer, preventing any filtered messages from reaching the Tail Durable Object, and thereby reducing the load on the Tail Durable Object. Moving the filtering out of the Durable Object was the first step in improving Tail’s performance at scale.

Sampling logs to keep Tails within Durable Object limits

After moving log filtering outside of the Durable Object, there was still the issue of determining when Tails could be started since there was no way to determine to what degree filters would reduce traffic for a given Tail, and simply starting a Durable Object back up would mean that it more than likely hit the 100 RPS limit immediately.

The solution for this was to add a safety mechanism for the Durable Object while the Tail was running.

We created a simple controller to track the RPS hitting a Durable Object and sample messages until the desired volume of 100 RPS is reached. As shown below, sampling keeps the Tail Durable Object RPS below the target of 100.

When messages are sampled, the following message appears every five seconds to let the user know that they are in sampling mode:

This message goes away once the Tail is stopped or filters are applied that drop the RPS below 100.

A final failsafe

Finally as a last resort a failsafe mechanism was added in the case the Durable Object gets fully overloaded. Since RPS tracking is done within the Durable Object, if the Durable Object is overloaded due to an extremely large amount of traffic, the sampling mechanism will fail.

In the case that an overload is detected, all messages forwarded to the Durable Object are stopped periodically to prevent any issues with Workers infrastructure.

Here we can see a user who had a large amount of traffic that started to become sampled. As the traffic increased, the number of sampled messages grew. Since the traffic was too fast for the sampling mechanism to handle, the Durable Object got overloaded. However, soon excess messages were blocked and the overload stopped.

Try it out

These new improvements are in place currently and available to all users 🎉

To Tail Workers via the Dashboard, log in, navigate to your Worker, and click on the Logs tab. You can then start a log stream via the default view.

If you’re using the Wrangler CLI, you can start a new Tail by running wrangler tail.

Beyond Worker tail

While we're excited for tail to be able to reach new limits and scale, we also recognize users may want to go beyond the live logs provided by Tail.

For example, if you’d like to push log events to additional destinations for a historical view of your application’s performance, we offer Logpush. If you’d like more insight into and control over log messages and events themselves, we offer Tail Workers.

These products, and others, can be read about in our Logs documentation. All of them are available for use today.

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Adam Murray|@admah

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