Goroutine Leak Profiles

Go’s concurrency features are powerful and easy to use, but that same ease can sometimes lead even seasoned developers to make mistakes. Fortunately, the Go ecosystem comes equipped with useful tools for debugging, e.g., the race detector, but even existing tools may miss some concurrency bugs, such as the topic of this article, the goroutine leak.

Goroutines synchronize or exchange information via shared concurrency primitives, e.g., channels, locks, and wait groups. While communicating, goroutines often block on these primitives, as in, wait until some condition is met; ubiquitous examples include waiting to acquire a held mutex, or receive a message over a channel. Goroutines can also block on operating system operations, like reading from a network socket or a file.

We may consider a goroutine leaked if it is blocked, but the conditions needed to unblock it can never be met. Over time, an accumulation of leaked goroutines degrades performance through excessive memory usage (by the leaked goroutines themselves or the memory they reference), as well as CPU usage from the garbage collector, especially if GOMEMLIMIT is in use.

Goroutine leaks can be notoriously difficult to detect. In unit testing, the most significant breakthroughs include the open-source library goleak, which can instrument individual tests to signal any un-terminated goroutines after the test wraps up as suspicious. Similarly, Go 1.25 introduced the synctest package to the standard library; it can significantly improve the quality of unit tests in concurrent code by giving Go developers more control over the ordering of concurrent events in order to reliably test hard-to-reproduce scenarios.

Unfortunately, neither approach can check for goroutine leaks in production systems, especially at larger scales, which may behave in ways unaccounted for by tests. Goroutine profiles are a rudimentary way to check for operations that block too many goroutines, or analyze growth trends. However, goroutine profiles cannot distinguish between goroutines which are leaked, and those which are temporarily blocked in high numbers by design, e.g., as caused by increased traffic in a microservice. Likewise, leaks which are low in number may slip by undetected for many years.

Go 1.27 introduces the goroutine leak profiler, a flexible and lightweight mechanism for finding goroutine leaks in running Go programs, including production systems. Unlike previous approaches, which require human analysis, this mechanism is precise and generates little-to-no false positives. The trade-off is that it is limited to a subset of goroutine leaks: goroutines permanently blocked on channels or primitives in the sync package. Luckily for us, this already covers a very large subset of goroutine leaks, as we’ll see in our examples.

In the following sections, we showcase how to use the feature, followed by some additional examples of detectable leaks, and a description of the underlying implementation and trade-offs.

Example: concurrent workers

Consider a function that processes work items concurrently:

type result struct {
res workResult
err error
}

func processWorkItems(ws []workItem) ([]workResult, error) {
// Process work items in parallel, aggregating results in ch.
ch := make(chan result)
for _, w := range ws {
go func() {
res, err := processWorkItem(w)
ch <- result{res, err}
}()
}

// Collect the results from ch, or return an error if one is found.
var results []workResult
for range len(ws) {
r := <-ch
if r.err != nil {
// This early return may cause goroutine leaks.
return nil, r.err
}
results = append(results, r.res)
}
return results, nil
}

Because ch is an unbuffered channel, each worker goroutine blocks when sending its result until the main goroutine receives from the channel. If processWorkItems returns early due to an error, the receiving loop terminates, and all remaining sender goroutines block forever.

This example is emblematic of a common mistake discovered in real Go programs, including Uber production services. Let’s see how we can find these leaks by using the new goroutine leak profiler.

Debugging with the goroutine leak profiler

The profile is available through the runtime/pprof package, as the goroutineleak profile type, or by installing the profile handlers defined by the net/http/pprof package. If you already have net/http/pprof set up in your service, then you don’t need to do anything else! The profile will be automatically made available for collection at the /debug/pprof/goroutineleak endpoint on whatever host and port the handlers are installed.

Let’s put our concurrency bug in context and set up the net/http/pprof package. This way, you can try it yourself!

package main

import (
"errors"
"log"
"net/http"
_ "net/http/pprof"
"time"
)

type workItem int
type workResult int

func processWorkItem(w workItem) (workResult, error) {
time.Sleep(10 * time.Millisecond)
if w == 5 {
return 0, errors.New("simulated error")
}
return workResult(w * 2), nil
}

type result struct {
res workResult
err error
}

func processWorkItems(ws []workItem) ([]workResult, error) {
ch := make(chan result)
for _, w := range ws {
go func() {
res, err := processWorkItem(w)
ch <- result{res, err}
}()
}

var results []workResult
for range len(ws) {
r := <-ch
if r.err != nil {
return nil, r.err
}
results = append(results, r.res)
}
return results, nil
}

func main() {
// Start pprof server
go func() {
log.Println(http.ListenAndServe("localhost:6060", nil))
}()

// Repeatedly trigger the leak
for {
items := []workItem{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}
_, err := processWorkItems(items)
if err != nil {
log.Printf("Error processing items: %v", err)
}

time.Sleep(time.Second)
}
}

Build the program above, then run it:

$ go build -o leaky
$ ./leaky

Collecting the profile

It won’t take long for the program to start accumulating leaks, which you can then view by using the web UI at http://localhost:6060/debug/pprof.

Alternatively, you can collect the goroutine leak profile using curl, and then examine it with go tool pprof:

$ curl http://localhost:6060/debug/pprof/goroutineleak > leak.prof
$ go tool pprof leak.prof
Type: goroutineleak
Time: 2026-03-01 13:19:49 UTC
Entering interactive mode (type "help" for commands, "o" for options)
(pprof) list processWorkItems
Total: 116
ROUTINE ======================== main.processWorkItems.func1 in .../main.go
0        116 (flat, cum)   100% of Total
.          .     31:           go func() {
.          .     32:                   res, err := processWorkItem(w)
.        116     33:                   ch <- result{res, err}
.          .     34:           }()

The profile reveals the goroutines leaked at ch <- result{res, err} (line 33), pinpointing the culprit operation. Notably, the longer the program is running, the larger the number of leaked goroutines.

Addressing the leak

This leak can be simply fixed by giving ch a buffer:

ch := make(chan result, len(ws))

This allows all the work item goroutines to send a message without blocking in the event of a premature return of processWorkItems.

We list more real-world examples in this section.

Implementation

This section is for those interested how leak detection works under the hood of the goroutine leak profiler. For details strictly pertaining to performance overhead and limitations, skip ahead to this section.

（节选）

原文：The Go Blog｜Goroutine Leak Profiles，2026-09-02