One quick and simple way to profile Go code is benchmark test profiling.
Monitoring is a critical component of literally any application stack. Without the ability to see how Go applications perform and get notified in case of an availability or performance problem, it would be impossible to take timely action. Any downtime or performance regression can have a significant impact on the business.
Performance profiling is essential for optimizing and fixing an application’s resource consumption and latency. A performance issue without an execution profile is like an error without a stack trace. It will lead to a lot of manual work to get to the root cause.
Long-running applications are not always busy doing work. In the case of, for instance, web, serverless or microservice applications, the work is done on every request, and the processes are idle the rest of the time. Similarly, if the program is processing messages from the queue, it may be idle when it is waiting for messages.
Profilers provide application developers with critical execution insights that enable resolving performance issues, locating memory leaks, thread contention and more. Although hot code stack traces and call graphs generated by the profilers are usually self-explanatory, it is sometimes necessary to understand how profilers work underneath to infer even greater details about applications from the generated profiles.
The difference between a program’s exponential, linear, logarithmic and constant execution times is critical for various use cases. Even if an algorithm is purposely designed to satisfy a certain complexity class, there are multiple reasons why it might not. An underlying library, OS or even hardware can be the root cause of a performance problem.
The main focus of the development of version 2.0 of the Go agent was to improve reliability and reduce agent overhead by upgrading and tuning the profiling capabilities.
The traditional split of responsibilities between application development and its operation in production assumes that application performance-related efforts are developers’ business. At the same time, application availability and uptime are managed by operations teams.
Go is a relatively new open source programming language created by Google. Considering its recent growth, many developers and organizations have naturally become interested in it. With its main features, such as compiled-language performance, powerful and simple concurrency model and cross-compilation support, it can be considered as a true cloud language.