Performance Optimization in Go

1. Profiling:

Principle: Disclose and get rid of inefficiency.
Practice in Go: The prof package can be used to monitor CPU as well as memory consumption.

import _ "net/http/pprof"
go func() {
log. Println(http. ListenAndServe("localhost:6060", nil))
}()

2. Efficient Data Structures:

Principle: Employ required data structure for good running performance.
Practice in Go: Pick the best data structures (for example, a suitable data structure for a time-series data is a tree)g. , slices vs. sorting functions (from sequential-search to binary-search) which depend on use cases.

var arr [10]int // fixed size array
var slice []int // dynamically sized slice

3. Memory Management:

Principle: Logic demands minimizing memory allocation and garbage collection.
Practice in Go: Bowl as you would admit and implement a sync. Creations for most often requested object pool animation

var buffer = make([]byte, 1024)

4. Concurrency Patterns:

Principle: Incorporate the concurrency patterns for better efficiency of the throughput.
Practice in Go: To effective handle concurrent jobs, use worker pools.

var wg sync. WaitGroup
for i :client. work = 0; for(i = 0; i < numWorkers; i++) {
wg. Add(1)
go worker(&wg, jobs)
}
wg. Wait()

Design Principles for System Design in Go

In this article, we will discover essential design principles for efficient system architecture in Go programming. Learn how to optimize concurrency, leverage interfaces, and manage errors effectively, ensuring robust and scalable solutions.

Important Topics for Design Principles for System Design in Go

What is System Design?
Components which comprise the System design
Design Principles for Programming in Go
Error Handling in Go
Concurrency in Go
Performance Optimization in Go
Testing in Go

Tags:

#System Design

Concurrency in Go

Testing in Go