
Identify five core performance test types—load, endurance, stress, volume, and scalability—and explain how each applies to production workloads, data volumes, and processing capacity.
Learn key performance testing terms, transactions and business flow, and explore transaction workload, think time, pacing time, ramp up, ramp down, and concurrent users.
Defines transaction workload in performance testing as the load for each business function, specifying users and transactions per duration, with banking and trading examples.
Learn to quantify think time and pacing time, and simulate production-like load in performance testing by matching user delays and transaction intervals.
Ramp up and ramp down describe gradually increasing test users to reach peak load, while excluding these phases from results and configuring run-time settings in testing tools.
Explore application performance metrics across web and API, batch jobs, and queues, including response times, transactions per second, throughput, and queue depth, with practical monitoring during performance testing.
Track server-side metrics such as CPU utilization, memory utilization in megabytes or gigabytes, and IO performance (IO operations per second, throughput, latency, disk utilization) across the full performance test.
Explore database performance metrics, including query response time, connections, and deadlocks, with examples on indexing, connection pool limits, and monitoring during load testing.
Explore network performance metrics for application performance testing, focusing on end-to-end latency in milliseconds and bandwidth utilization, and how throughput reveals bottlenecks in the transport layer.
Monitor application and testing tool logs to validate transaction completeness and identify bottlenecks during performance testing. Track file system storage and read-write errors to support compliance.
Identify what is tested for performance across web, mobile, cloud, APIs, databases, streaming, gaming, blockchain and AI apps; exclude client-side and single-user tests, and CAPTCHA or MFA features from testing.
Explore the why of performance testing by aligning business and end-user expectations for fast apps, while planning for scalability, cost efficiency, uptime, SLS standards, and CI/CD automation.
This course covers the basics and fundamental concepts of Application Performance Engineering.
The course is aimed for those who want to learn Performance Engineering from the scratch but to learn towards the advance level of performance engineering concepts.
This course is designed specifically for those who are in QA or Test Automation role but want to learn the performance engineering concepts which is always a complementary skill to the QA an Test Automation. Suitable for non functional engineers, testing professionals, and whoever has a delivery responsibility in software development lifecycle as well.
This course very useful for those who want to choose a career or change career into Performance Testing / Performance Engineering.
This course will give the confidence and fundamental knowledge in the Performance testing area, to clear any level of interviews.
This course also has an introduction to PT with Gen AI model, that gives the high-level strategy to the model. You can use and develop the same too.
It covers the following course contents:
- Fundamental concepts of Performance Engineering.
- Introduction, Types of performance testing, Terminologies - Transaction, workflow, workload, think time, pacing time, ramp up, ramp down and concurrent users.
- Performance Monitoring Metrics - Application, Server, DB, Network and Logs & Errors monitoring metrics.
- Future of Performance Engineering
- Road map further