Optimizing Golang Application for Performance and Scalability

Quick Summary: The modern app market dictates high requirements and overall app performance for the user experience. But it is advisable to optimize the Go performance only if the improvements can be justified, i.e., resource efficiency-related benefits for the business. In this blog, we’ll discuss the most awaited performance patterns for your Golang application, make your app load fast, work seamlessly, and not crash.


When investing time and effort for performance tunning, ensure that even if your application is optimizable for efficiency, it doesn’t necessarily have to be optimized. There may be various reasons for optimizing performance, but the need is always the same. As you have chosen Go language for your project, you’re already on the right track. But you need to improve your Go application’s performance and speed to make it the best in the market.

Everyone wants a high performance and speedy application; a user wants speedy delivery, a developer wants fast performance, whereas an entrepreneur wants both!

The two main motive of app performance monitoring are:

Get data on app performance: There are APM tools to monitor data on its performance, converted it into reports, and help you identify ways to optimize performance.

Get regular alerts on unusual action: APM software is used to analyze data over the long term on non-deterministic behavior, so you can alert DevOps engineers of the need to scale on time.

Here we’re going to learn about how to improve your Golang application’s performance, so without further ado, let’s get started!

Efficiency Optimization vs. Latency Optimization

The two different but related aspects of application performance are efficiency and operation latency. They aim to optimize the performance of the entire program’s resource consumption and focus on specific function latency improvements. Improvements in resource efficiency have a positive effect on latency, which may increase resource utilization.

There are few parts of the program which will utilize more resources compared to others. To improve latency, it is essential to identify bottlenecks to represent the code that consumes a significant amount of time processing a single task.

Profiling Tools

Locating program hot spots and bottlenecks during the development process and simulated test environments are the most suitable. We prefer the Instana Go Profiler as it uses Go’s built-in pprof securely in any environment.

To determine the hidden parts of the program, benchmark profiling can be used.

Use efficient network polling for some requests

Goroutine is responsible for handling network IO using an operating system polling machine. There are many waiting goroutines that will be serviced by a single operating system thread.

Despite local file IO, Go doesn’t implement any IO polling as each of these consumes one operating system thread while in progress. You can use a buffered channel as a semaphore to limit the amount of concurrent blocking IO.

var semaphore = make(chan struct{}, 10)

func processRequest(work *Work) {
semaphore <- struct{}{} // acquire semaphore
// process request
<-semaphore // release semaphore

Algorithm Efficiency

Algorithm optimizations offer the highest performance gains. It is a good idea to take into consideration algorithm improvements and focus on the language optimizations. Go performance optimization focus on the efficient use of the programming language. Various micro-optimizations are automatically taken care of by the compiler.

Golang Performance Patterns

● Parallelize CPU work
Your work can be parallelized without synchronization by taking advantage of all the cores that help you speed up performance to the number of physical cores.

● Make I/O operations asynchronous
Network and file I/O is the widely used bottleneck in I/O-bound applications. Making independent I/O operations asynchronous can improve downstream latency. Use sync—WaitGroup to synchronize multiple operations.

● Do not allocate memory in hot spots
Creating objects require additional CPU cycles and also keeps the garbage collector busy, which is a good practice to reuse objects in program hot spots.

● Favor read-only locks
Synchronization leads to race conditions. Avoiding mutexes will have a positive impact on efficiency and latency. Lock-free alternatives to some common data structures are available.

● Use regular expressions
It is incapable of compiling the same regular expression before every matching. While obvious, it is often overlooked.

● Use int, not string, for maps
If the program relies heavily on maps, using int keys might be meaningful, if applicable.

● Use read-only locks
Using full locks for read-heavy synchronized variables will make the goroutine wait, so you can use rad-only locks to avoid this.

Final Thoughts

After reading this blog, you may have realized that application performance monitoring is very important and must be done regularly. There are various performance management solutions available which made this process more efficient. Today’s world is dependent on apps, so improving your Golang application’s performance is critical for your business’s success. However, you have to optimize your application along the critical path, which is likely to identify what adequate performance is. If you think you need an experienced Golang development company to help you in optimizing your golang application, get in touch with our expert on Skype- Bacancy or visit our website.

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Optimizing Golang Application for Performance and Scalability
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