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Performance testing with jenkins and JMeter or Gatling

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Architectural Context

Detailed reference for Performance testing with jenkins and JMeter or Gatling in the context of Platform & Site Reliability.

Table of Contents

  1. Architectural Foundations
  2. Kubernetes Tools
  3. CICD
  4. GitHub Actions
  5. Jenkins
  6. Cloud Infrastructure
  7. Azure
  8. Infrastructure
  9. Testing
  10. Performance Engineering
  11. Load Testing
  12. Systems
  13. Performance Tuning
  14. Testing
  15. Performance Testing
  16. Web Performance

Architectural Foundations

Kubernetes Tools

General Reference

CICD

GitHub Actions

Performance Automation

  • (2022) thenewstack.io: Simple Load Testing with GitHub Actions [YAML CONTENT] [COMMUNITY-TOOL] — Practical engineering guide detailing how to build an automated, zero-infrastructure load testing flow using GitHub Actions. It highlights how integrating lightweight load generators (like k6 or Vegeta) into standard YAML workflows establishes early performance baselines and guards against performance regressions.

Jenkins

Reporting Plugins

  • (2024) performance-plugin ⭐ 194 [JAVA CONTENT] 🌟🌟🌟 [COMMUNITY-TOOL] — This Jenkins CI plugin compiles, parses, and visualizes execution metrics from load testing utilities like JMeter, Taurus, and JUnit directly within build workflows. Architecturally, it helps teams enforce automated quality gates by failing pipelines based on strict metric thresholds (e.g., error percentages or response time limits).
  • (2023) plugins.jenkins.io: gatling [JAVA CONTENT] [COMMUNITY-TOOL] — Official Jenkins integration for Gatling, enabling automated parsing of Gatling simulation results inside CI workflows. It charts performance trends over time, facilitating rapid visual regression tracking and immediate identification of microservice performance degradation in downstream builds.

Cloud Infrastructure

Azure

Testing Services

  • (2024) docs.microsoft.com: Azure Load Testing [N/A CONTENT] [COMMUNITY-TOOL] — Azure's managed load testing service that lets developers generate high-scale load using existing Apache JMeter scripts. Synthesizing live cloud updates, it integrates seamlessly with Azure Monitor to provide end-to-end insights from client-side response times to server-side resource bottlenecks, aiding rapid optimization.
  • (2021) azure.microsoft.com: Introducing Azure Load Testing: Optimize app performance at scale [N/A CONTENT] [COMMUNITY-TOOL] — The launch blog post detailing the debut of Microsoft's Azure Load Testing service. It explains how the tool bridges the gap between raw load generation and cloud application monitoring, allowing developers to execute JMeter scripts in an automated cloud-native paradigm directly from GitHub Actions or Azure Pipelines.
  • (2021) infoq.com: Microsoft Introduces a Fully-Managed Azure Load Testing Service in Preview [N/A CONTENT] [COMMUNITY-TOOL] — Industry reporting on Azure's entry into fully managed performance testing, discussing how it leverages Apache JMeter under the hood. It provides a historical snapshot of Microsoft's move to simplify distributed load testing for engineering teams, eliminating the manual upkeep of VM scale sets for load generation.

Infrastructure

Testing

Load Testing

  • (2021) Distributed Load Testing on AWS 🌟 [ADVANCED LEVEL] [COMMUNITY-TOOL] [GUIDE] — An AWS Solution blueprint outlining distributed cloud load testing utilizing containerized runners inside AWS Fargate. Simulates high-velocity traffic spikes to assess API gateway throughput bottlenecks and database elasticity limits.

Performance Engineering

Load Testing (1)

Distributed Testing

  • (2022) JMeter Distributed Testing Step-by-step [N/A CONTENT] [ADVANCED LEVEL] 🌟🌟🌟🌟 [ENTERPRISE-STABLE] [GUIDE] — Operational step-by-step documentation detailing JMeter distributed execution topologies. Solves communication issues between controllers and performance workers during heavy test sequences.

Kubernetes Deployment

Observability

  • (2022) linkedin.com: Tuning Grafana - Jmeter Dashboards [N/A CONTENT] 🌟🌟🌟🌟 [ENTERPRISE-STABLE] — Examines methodologies for directing live JMeter thread telemetry to Grafana dashboards via InfluxDB. Gives operational teams real-time visibility into transaction metrics during heavy profiling runs.

Testing Frameworks

  • (2026) jmeter.apache.org [JAVA CONTENT] 🌟🌟🌟🌟🌟 [DE FACTO STANDARD] — Industry-standard, open-source performance evaluation engine. Simulates high-velocity workloads against a wide array of application protocols to measure system response under stress.
  • (2026) jmeter.apache.org: Best Practices [N/A CONTENT] [DOCUMENTATION] 🌟🌟🌟🌟🌟 [DE FACTO STANDARD] — Official design guidelines detailing how to configure JMeter for massive volume tests. Recommends relying on CLI mode and minimizing logging resources to avoid client-side load skew.

Tutorials

  • (2023) youtube: JMeter API Performance Testing Tutorial 🌟 [N/A CONTENT] 🌟🌟🌟🌟 [ENTERPRISE-STABLE] — Educational walkthrough mapping API load-test workflows. Covers parameterizing user requests, analyzing server metrics, and troubleshooting unexpected timeouts in dynamic microservices backends.
  • (2021) tutorialspoint.com: JMeter Quick Guide [N/A CONTENT] 🌟🌟🌟 [COMMUNITY-TOOL] [GUIDE] — Reference manual covering basic JMeter thread management and test flow structures. Designed to help teams write simple API validations and performance regression scripts.

Systems

Performance Tuning

Diagnostic Tools

Testing (1)

Performance Testing

Gatling

  • (2025) gatling.io [SCALA CONTENT] [ADVANCED LEVEL] [LEGACY] — Gatling is a highly optimized, asynchronous load-testing framework designed for high-concurrency scenarios. Written in Scala and Java, it utilizes Netty and Akka actors under the hood to handle thousands of concurrent virtual users on a single host machine, avoiding the thread-per-user overhead common in legacy frameworks like JMeter.

JMeter

  • (2022) softwaretestingmagazine.com: Learning JMeter : Documentation, Tutorials, Videos [JAVA CONTENT] [COMMUNITY-TOOL] — A comprehensive compilation of tutorials, documentation, and videos for Apache JMeter. From an architectural standpoint, JMeter remains a foundational Java-based tool for load testing and performance measurement. Although newer Go/Rust-based tooling is rising, JMeter's extensive protocol support (HTTP, JDBC, JMS) ensures its continued enterprise relevance.

Locust

  • (2025) Locust [PYTHON CONTENT] 🌟🌟🌟🌟🌟 [DE FACTO STANDARD] — An open-source, developer-centric performance testing tool that enables writing load scenarios in pure Python. It avoids fragile XML configuration files by favoring dynamic, code-as-configuration scripts, allowing engineering teams to scale out tests across millions of concurrent users using an event-driven greenlet model.

SaaS Platforms

  • (2024) octoperf.com [N/A CONTENT] [COMMUNITY-TOOL] — Octoperf is a commercial, cloud-native performance testing platform built directly on top of Apache JMeter. It streamlines the creation, execution, and analysis of large-scale JMeter tests without the burden of managing local load generator infrastructure. Ideal for modern DevOps pipelines seeking codeless test design and real-time reporting dashboards.
  • (2024) flood.io [N/A CONTENT] [COMMUNITY-TOOL] — Tricentis Flood is a cloud-hosted load testing platform that supports JMeter, Gatling, and Selenium. It allows engineering teams to scale massive distributed loads from global geographic regions to assert system resiliency. It serves as a critical integration point for modern CI/CD pipelines aiming to shift performance testing left.

Service Level Objectives

  • (2023) thenewstack.io: Simple HTTP Load Testing with SLOs [N/A CONTENT] [COMMUNITY-TOOL] — A technical exploration of how modern load testing tools are adopting Service Level Objectives (SLOs) as first-class assertions. It contrasts classical metric collections against modern SLO-driven assertions (e.g., verifying 95th percentile latency is under 100ms), showcasing how to integrate these checks directly into automated deployment flows.

Vegeta

  • (2025) tsenart/vegeta 🌟 ⭐ 25067 [GO CONTENT] 🌟🌟🌟🌟🌟 [DE FACTO STANDARD] — Vegeta is an incredibly fast, highly optimized command-line HTTP load-testing tool and library written in Go. From an architectural perspective, it excels at maintaining a constant request rate (RPS) to pinpoint precisely when and where services break down, generating highly customizable text or vector graphic reports.

Web Performance

Industry Acquisitions

  • (2020) devops.com: Catchpoint to Acquire Webpagetest.org [N/A CONTENT] [COMMUNITY-TOOL] — An analysis of Catchpoint's acquisition of WebPageTest, the industry-standard front-end performance auditing tool. Synthesizing live ecosystem changes, the platform continues to operate as an essential resource for tracing core web vitals and waterfall execution charts, bolstered by Catchpoint's global infrastructure.

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