Explain the use of Go's built-in profiling and performance analysis tools for optimizing and improving the performance of Go programs?

Go provides several built-in profiling and performance analysis tools that can be used to optimize and improve the performance of Go programs.

One of the most commonly used tools is the **go tool pprof** command-line tool, which can be used to generate and analyze CPU and memory profiles of Go programs. The tool can be used to identify performance bottlenecks in a program by analyzing the time spent in different functions, and can also be used to identify memory leaks and other memory-related issues.

To generate a CPU profile, you can use the **pprof.StartCPUProfile** function to start profiling, and then call **pprof.StopCPUProfile** when the profiling is complete. The resulting profile can then be analyzed using the **go tool** **pprof** command-line tool.

Similarly, to generate a memory profile, you can use the **runtime/pprof** package to capture memory allocations and heap profiles, and then analyze the resulting profile using the **go tool pprof** command-line tool.

Go also provides other built-in tools for profiling and performance analysis, such as the **net/http/pprof** package, which provides HTTP endpoints for generating CPU and memory profiles of running HTTP servers, and the **runtime/trace** package, which can be used to generate trace data for analyzing the performance of a Go program.

Overall, these tools can be very useful for identifying and fixing performance issues in Go programs, and can help developers optimize their code for better performance and scalability.