Continuous integration and delivery of performance testing in Go: Best practices for integrated performance testing: Early integration into CI pipeline Automated test cases Collect performance indicators Set performance indicator acceptance thresholds Practical case: Use httperf to create performance test cases Integrate use cases into CI/CD tools (such as Jenkins) Set threshold assertions to compare performance metrics Trigger alarms to notify performance issues
Persistence of performance testing in Go language Integration and Delivery
When developing modern software, performance is critical. Performance testing is a necessary practice to verify the performance of an application in a production environment.
Continuous Integration (CI) and Continuous Delivery (CD) automate the software development and deployment process, enabling development teams to quickly and continuously deliver high-quality software.
Integrate performance testing in CI/CD
Integrating performance testing into your CI/CD pipeline ensures that potential performance issues are detected before new code is deployed. Here are some best practices:
Practical case
Consider a Web service developed using Go language. In order to integrate performance testing in the CI/CD pipeline, we can:
httperf
Create performance test cases: import ( "fmt" "log" "github.com/httperf/httperf" ) func main() { // 创建 HTTP 性能测试请求 req := httperf.NewRequest("GET", "https://example.com/api/v1/users") req.AddHeader("Content-Type", "application/json") // 设置性能测试选项 opts := httperf.Options{ NumConnections: 10, // 并发连接数 Timeout: 10, // 超时时间(秒) Duration: 60, // 测试持续时间(秒) Rate: 100, // 请求速率(次/秒) PrintInterval: 10, // 打印结果的时间间隔(秒) OutputFile: "test.log", // 保存结果的文件名 } // 执行性能测试 err := httperf.Run(req, opts) if err != nil { log.Fatal(err) } // 解析测试结果 results, err := httperf.ParseResults("test.log") if err != nil { log.Fatal(err) } // 比较结果与阈值 if results.MeanResponseTime > 500 { // 响应时间阈值 500 毫秒 fmt.Printf("响应时间超标:%d 毫秒\n", results.MeanResponseTime) } }
By integrating performance testing into the CI/CD pipeline, we can ensure that applications always meet expected performance goals and proactively detect and resolve performance issues before they occur.
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