Kevin Oliver

@kevino

Posted September 1, 2016

Finagle Block Party

💔 SPOILER ALERT: you do not want to go to this party 💔

Blocking Finagle’s event loop via calls to Await.result or Await.ready will cause your application to experience unexpected slowness, a decrease in throughput, and potentially deadlocks. Find out if our new tools that identify the calls that cause service sadness are right for you.

Why is blocking bad?

Finagle uses Netty which is a network library built on an event loop. When an event loop thread blocks, that thread can no longer do its other asynchronous work. As such, blocking has effects that span beyond the line of code that is doing the blocking. Removing blocking code should help your service with throughput and latency.

How do I find out if my service is blocking?

Blocking can happen in two ways, explicitly and implicitly. Explicit blocking is when code synchronously waits on a Future from an event loop thread. In Finagle, this is done by making calls to Await.result or Await.ready.

If your service is running Finagle 6.37, there is now a gauge exported as scheduler/blocking_ms which can be used to identify how much time is being spent. You can verify that your service continues to operate correctly by checking the new lint rule added to TwitterServer’s /admin/lint admin endpoint.

Implicit blocking happens when your code runs a potentially expensive operation, for example making network calls on the event loop thread using a synchronous API. Unfortunately, these calls are difficult to track down and we do not yet have any tooling to help on this front.

Bummer, it is blocking. How do I find out what’s blocking?

You can do a deploy with an extra system property set that will log the stacktraces for a fraction of the blocking calls. Given that the code is about to block, the extra overhead of logging the stacktrace shouldn’t be a significant overhead. However, if your service has a large amount of blocking, you may want to limit this fraction to avoid filling up your logs. You can set it via -Dcom.twitter.concurrent.schedulerSampleBlockingFraction=$fraction where $fraction must be between 0.0 and 1.0, inclusive.

This will output a log that should point you to the code doing the blocking. For example in the stacktrace below, HttpServer.scala would be the cause:

I 0812 21:39:31.743 THREAD18 TraceId:a2c1d94ae0029777: Scheduler blocked for 5004957 micros via the following stacktrace
com.twitter.concurrent.LocalScheduler$BlockingHere
  at com.twitter.concurrent.LocalScheduler$Activation.blocking(Scheduler.scala:216)
  at com.twitter.concurrent.LocalScheduler.blocking(Scheduler.scala:285)
  at com.twitter.concurrent.Scheduler$.blocking(Scheduler.scala:115)
  at com.twitter.util.Await$.result(Awaitable.scala:151)
  at com.twitter.util.Await$.result(Awaitable.scala:140)
  at com.twitter.example.HttpServer$$anonfun$4.apply(HttpServer.scala:28)
  at com.twitter.example.HttpServer$$anonfun$4.apply(HttpServer.scala:24)
  ...

How can I fix the blocking code?

We recommend that applications use the Future combinators such as flatMap, onSuccess, transform, and so on. Sometimes this type of change may not be feasible and in those cases you can use a FuturePool to shift the blocking off of the event loop and onto a thread pool that your application controls.

Please let us know if you have any questions, either by getting in touch through @finagle, the Finaglers mailing list, or chat.

Thanks for reading and we sincerely hope you don’t RSVP.