Performance Testing Fundamentals: from Basics to Hands-on

Navigate the performance testing lifecycle from requirements gathering and planning to environment setup, test implementation, execution, monitoring, analysis, and recommendations for continuous improvement.

Explore key performance testing metrics, including application-side indicators like response time and percentiles, and server-side metrics such as CPU, memory, disk I/O, and network usage.

Define and measure non-functional requirements to drive performance testing, focusing on response time, throughput, scalability, reliability, and usability, and map targets to test scenarios.

Explore capacity testing to determine the maximum capacity, identify bottlenecks in the database, CPU, and network, and ensure the system meets requirements before reaching the saturation point and degradation.

Learn how load testing simulates normal user activity to ensure the system handles average load. Assess stability and performance metrics like response time, throughput, and user experience under typical conditions.

Stress test pushes the system beyond normal limits to assess stability, the breaking point, and recovery after peak load with rising concurrent users, and monitors response time and errors.

Endurance testing ramps up concurrent users to a steady load and runs the system for hours to reveal resource leaks, stability under load, and degradation in response time and throughput.

Spike testing simulates a sudden surge in users to assess stability and recovery after the spike. It reveals bottlenecks like caching issues, memory spikes, and database logs during traffic surges.

Explore scalability testing to assess growth, identify tipping points, and guide upgrades across hardware, software, infrastructure, and code, using auto-scaling policies to prevent performance issues.

Evaluate system performance under real-world data sizes by conducting volume testing, measuring response times, resource usage, and capacity planning as data scales from thousands to millions of records.

Determine the needed concurrent users for load, stress, and endurance tests using capacity zones—comfort, degradation, and saturation—and the ranges: 40-60 for load, 60-70 for stress, 10-30 for endurance.

Compare capacity, load, stress, endurance, spike, scalability, and volume testing in one quick reference table, recall each type's purpose, and understand load patterns via graphs and a PDF.

Learn how load model and load profile drive performance tests, detailing active users, ramp-up and ramp-down, test duration, and how capacity, spike, and endurance shapes realism and pitfalls.

Deliver performance test reports that translate results into business impact, tailor detail for executives or developers, and drive go-live and optimization decisions.

Learn how to choose the right performance testing tool by comparing open source, commercial, cloud-based, and hybrid options, and assessing protocols, scalability, scripting, reporting, licensing, and community support.

Learn how to download the latest stable version of Apache JMeter, verify Java is installed, and launch the JMeter GUI from the bin folder on Windows.

Explore the main components of a performance test plan, including thread groups, samplers, logic controllers, config elements, timers, assertions, listeners, and preprocessors and postprocessors.

Create the first performance test with Geometer against a locally dockerized PetStore API built with OpenAPI 3.0, configuring http requests, parameterizing from Swagger, and validating results.

Explore hands-on performance testing with JMeter: parametrize load, add sync time with a uniform random timer, implement data correlation, extract JSON data, assert responses, and review results using Geometer listeners.

Discover BlazeMeter, a cloud-based performance testing platform that runs load and stress tests in the cloud, eliminating local infrastructure and supporting JMeter, Godlink, Selenium, Locust, and Torus.

Record a performance testing scenario using BlazeMeter Recorder Chrome extension to capture navigation in the Apple Store and generate a JMX script for JMeter, with login and saving as JMX.

Master running BlazeMeter performance tests by creating a new project, uploading the GMeter script, configuring load for 20 users over 20 minutes, and setting a failure criterion for error rate.

Execute and analyze JMeter tests in BlazeMeter, review real-time results and history, compare runs with a baseline, and explore timeline, request stats, engine health, and pricing.

Explore how a performance testing framework orchestrates tests, collects metrics, and visualizes results for server-side and client-side tests using Jenkins, JMeter, InfluxDB, Grafana, and Sidespeed.io in Docker.

Set up a full monitoring and visualization stack for performance tests by configuring InfluxDB, linking it with JMeter, and visualizing results in Grafana using a ready-to-use dashboard.