Mutexes are often a source of contention that can result in performance issues or deadlocks. It’s no different in Go, and locating the root cause is often challenging. In obvious deadlock situations where all goroutines are waiting, the runtime may be able to detect or predict mutex-related issues and panic. Generally, the problems will manifest themselves at the application logic level.

Let’s look at this simple example:

lock := &sync.Mutex{}
// goroutine1
go func() {
lock.Lock()

// here we make other goroutine1 wait
time.Sleep(500 * time.Millisecond)

fmt.Printf(“%v: goroutine1 releasing…\n”, time.Now().UnixNano())
lock.Unlock()
}()

// goroutine2
go func() {
fmt.Printf(“%v: goroutine2 acquiring…\n”, time.Now().UnixNano())
lock.Lock()
fmt.Printf(“%v: goroutine2 done\n”, time.Now().UnixNano())
}()

time.Sleep(1 * time.Second)

The lock is obtained in the first goroutine, and the second goroutine has to wait for it.

Problems like this will most likely not be detected in the development phase, when there is no concurrent use of an application, and they will result in a performance issue only in the production environment. As a side note, it’s always a good idea to have automated performance regression testing in place, which will simulate concurrent live traffic.

Utilizing pprof

Go has a built-in block profiling and tracing toolset for such situations: pprof. Basically, an application has to expose the profilers on an HTTP port by importing the net/http/pprof package. Afterward, different profiles can be requested by running go tool pprof http://localhost:6060/debug/pprof/block.

Although pprof’s block profiler or tracer can be extremely helpful in identifying contention issues, there are a few obstacles in using pprof against production environment:

• The profiler’s HTTP handler, which accepts profiling requests, needs to attach itself to the application’s HTTP server or have one running, which means extra security measures should be taken to protect the listening port.
• Locating and accessing the application node’s host to run the go tool pprof against may be tricky in container environments like Kubernetes.
• If the application has a deadlock or cannot respond to pprof requests, no profiling or tracing is possible. Profiles recorded before the problem was detected would be very helpful in cases like this.

For production and development environments, the IBM Instana^™ platform provides automatic blocking call profiling. It reports regularly and profiles to the dashboard, which are accessible in the Hot spots/Time section.

Getting started with the IBM Instana platform

The IBM Instana platform is a powerful tool that can help developers quickly and efficiently detect lock contention issues in Go applications. With its automated profiling capabilities, the platform can easily identify the sections of code where multiple goroutines are competing for the same lock, allowing developers to pinpoint and resolve contention issues.

Using the platform, developers can help ensure that their applications perform optimally and deliver the best possible user experience. So, if you’re developing Go applications and looking for an effective way to detect lock contention, consider using the IBM Instana platform to streamline your debugging process and improve your application’s overall performance.

If you’re not already an IBM Instana user, you can sign up for a free two-week trial.