Is this skill useful for continuous integration (CI)?

Absolutely. It emphasizes performance regression testing patterns that are ideal for integration into automated DevOps pipelines.

Does it support automated reporting?

It includes structured templates for Performance Test Reports that summarize throughput, error rates, and latency percentiles (P95/P99).

Which performance testing tools are supported by this skill?

The skill provides expert guidance and script generation for industry-leading tools including k6, JMeter, and Gatling.

Can this skill help identify specific system bottlenecks?

Yes, it provides frameworks for analyzing test results to pinpoint issues in database indexing, CPU-intensive processes, or caching layers.

Performance Testing QA Engineer

Name: Performance Testing QA Engineer
Author: spjoshis

byspjoshis

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セキュリティとテスト

Conducts comprehensive load, stress, and scalability testing to ensure application stability and responsiveness under high-traffic conditions.

概要

The Performance Testing skill empowers developers and QA engineers to implement professional-grade testing strategies using industry-standard tools like k6 and JMeter. It facilitates the creation of sophisticated load test scripts, provides structured templates for performance reporting, and helps identify critical system bottlenecks through data-driven analysis. By integrating this skill, teams can validate Service Level Agreements (SLAs), conduct capacity planning, and ensure their infrastructure remains resilient as user demand scales.

主な機能

Detailed performance reporting with P95/P99 latency metrics
1 GitHub stars
System bottleneck identification and optimization advice
Scalability and capacity planning guidance
Automated k6 and JMeter load test script generation
SLA validation and performance benchmarking templates

ユースケース

Establishing performance baselines to detect regressions in CI/CD pipelines
Identifying database or CPU bottlenecks under high concurrent user stress
Validating API scalability and response times before a major product launch

概要

主な機能

Detailed performance reporting with P95/P99 latency metrics
1 GitHub stars
System bottleneck identification and optimization advice
Scalability and capacity planning guidance
Automated k6 and JMeter load test script generation
SLA validation and performance benchmarking templates

ユースケース

Establishing performance baselines to detect regressions in CI/CD pipelines
Identifying database or CPU bottlenecks under high concurrent user stress
Validating API scalability and response times before a major product launch