Go Custom Profilers

In the ever-evolving landscape of software development, the need for precise and tailored performance analysis has never been more critical. Go, with its robust performance and concurrency model, offers developers a powerful platform for building efficient applications. However, even with Go’s built-in profiling tools, there are scenarios where a more customized approach is necessary to truly understand and optimize your application’s performance. This article dives into the world of custom profilers in Go, showcasing how to extend beyond the standard profiling tools to capture and analyze the specific metrics that matter most to your application. From setting up custom profiling hooks to integrating with Go’s runtime/pprof package, we’ll explore practical examples and techniques to unlock deeper insights into your Go applications.

Creating custom profile

Custom profiling in Go allows developers to track specific aspects of their application’s performance that are not covered by the default profiling tools. This section demonstrates how to implement a custom profiler to monitor resource usage, specifically tracking connections to identify potential leaks.

Step 1: Define a Custom Profile

First, we define a custom profile using Go’s runtime/pprof package. This profile will track connections in our application

package mypkg

import (
    "runtime/pprof"
)

var connProf = pprof.NewProfile("connection_profiler")

The profile name must be unique throughout the application; NewProfile will panic if it detects a duplicate name. To access a profiler defined in another package, use the Lookup function as follows:

connProf := pprof.Lookup("connection_profiler")

Step 2: Instrumentation

Next, we instrument the application to add and remove connections from our custom profile. This is done by hooking into the connection lifecycle events: when a connection is established and when it is closed.

func onConnectHook(conn wasabi.Connection) {
    connProf.Add(conn, 1)
}

func onDisconnectHook(conn wasabi.Connection) {
    connProf.Remov(conn)
}

Step 3: Collecting and Downloading the Profile

To collect data from our custom profiler, we expose it via an HTTP server, typically done using Go’s built-in net/http/pprof handler. This allows us to download the profile data for analysis.

curl http://localhost:8080/debug/pprof/connection_profiler > conn.pprof

Step 4: Analyzing the Profile

Finally, we analyze the collected profile using Go’s pprof tool. This step helps us visualize and understand the connection usage and potential leaks in our application.

go tool pprof -http=:8081 conn.pprof

By following these steps, developers can create custom profiles in Go to monitor specific resources or behaviors within their applications. This example focused on tracking connections, but the same approach can be applied to various resources or events, providing deep insights into application performance and helping identify and resolve potential issues.