MODULE 1: Performance Engineering Foundations, Strategy & Test Planning

Build a strong foundation in Performance Engineering concepts and learn how to define performance goals, create test strategies, and plan successful testing engagements. By the end of this module, you will be able to translate business requirements into measurable performance objectives and prepare for real-world performance testing projects.

• Understanding Performance Engineering fundamentals — performance mindset, testing types, and Shift-Left strategy
• Defining Non-Functional Requirements (NFRs) and converting business expectations into measurable SLAs and KPIs
• Creating performance test strategies, workload models, and success criteria for different applications
• Planning test environments, infrastructure readiness, and realistic test data for effective execution

MODULE 2: Performance Testing Tools — JMeter, LoadRunner & HAR Analysis

Gain hands-on experience with industry-leading performance testing tools and learn how to analyze application behavior across multiple system layers. By the end of this module, you will be able to create load tests, analyze HAR files, and troubleshoot performance bottlenecks effectively.

• Recording and executing your first load test using JMeter, along with an introduction to LoadRunner architecture — VuGen, Controller, and Analysis
• Understanding performance testing protocols including HTTP, SOAP, REST, AJAX, and RDP
• Capturing and analyzing HAR files using Chrome DevTools to identify client-side performance issues and hidden bottlenecks
• Building a Performance Layers Map covering Browser, Network, Application, JVM, Database, and Cloud, while using Linux monitoring tools such as Nmon, sar, iostat, htop, and top for diagnostics

MODULE 3: Monitoring & Observability

Learn how to monitor applications in real time and build end-to-end observability across metrics, logs, and traces. By the end of this module, you will be able to create dashboards, analyze logs, configure alerts, and identify performance bottlenecks using modern observability tools.

• Setting up Prometheus and exporters, writing PromQL queries, and configuring alert rules for key performance metrics
• Building real-time Grafana dashboards to visualize KPIs such as CPU, memory, P95 response time, throughput, and error rates with NFR thresholds
• Analyzing application logs using Kibana and the ELK stack, performing log correlation, and identifying hidden issues during load tests
• Gaining hands-on experience with Dynatrace and AppDynamics for automatic instrumentation, service flow mapping, and AI-driven root cause analysis

MODULE 4: JVM Internals & Performance Tuning

Develop a deep understanding of JVM internals and learn how to diagnose and resolve Java application performance issues. By the end of this module, you will be able to analyze memory behavior, troubleshoot thread issues, and optimize JVM performance for production workloads.

• Understanding JVM architecture, memory models, heap structure, garbage collection algorithms, and GC log analysis for identifying memory leaks and GC overhead issues
• Analyzing heap dumps and thread dumps using JVisualVM and YourKit to identify deadlocks, thread contention, and multithreading bottlenecks
• Configuring JVM tuning parameters, implementing effective heap sizing strategies, and optimizing garbage collection performance
• Troubleshooting real-world performance issues including UI slowness, transaction response time degradation, load balancing challenges, and high availability considerations

MODULE 5: Database Performance & Optimization

Learn how to identify, analyze, and resolve database performance bottlenecks across traditional and microservices-based architectures. By the end of this module, you will be able to interpret database reports, optimize SQL queries, and improve overall application performance.

• Analyzing Oracle AWR reports, identifying top wait events, assessing database parameters, and automating AWR report analysis using Python
• Optimizing SQL queries through execution plan analysis, indexing strategies, and workload-based database tuning techniques
• Improving ETL batch job performance and understanding database resource utilization under high-load scenarios
• Managing database performance in microservices architectures, including connection pooling, distributed transactions, caching strategies, and service-to-database interactions

MODULE 6: Cloud, Kubernetes & Microservices Performance

Learn how to engineer and validate application performance in modern cloud-native environments. By the end of this module, you will be able to test distributed systems, optimize containerized workloads, and troubleshoot performance issues across microservices architectures.

• Performing cloud performance testing on AWS EC2 and Oracle Cloud, including distributed load generation, auto-scaling validation, and cost versus performance analysis
• Designing Kubernetes performance strategies, testing Horizontal Pod Autoscaler (HPA) behavior, and optimizing Docker container performance using shell automation scripts
• Conducting SOAP and REST API performance testing while understanding performance considerations for SIEM applications
• Implementing distributed tracing techniques to analyze end-to-end transaction flows and identify bottlenecks across microservices environments

MODULE 7: AI, Root Cause Analysis & Performance Reporting

Learn how to leverage AI for proactive performance management and master structured root cause analysis techniques. By the end of this module, you will be able to identify anomalies, isolate bottlenecks, and communicate performance insights effectively to technical and business stakeholders.

• Applying AI and machine learning techniques for anomaly detection, predictive analysis, and automated root cause identification within performance workflows
• Using structured root cause analysis methodologies to isolate bottlenecks, investigate performance defects, and conduct evidence-based troubleshooting
• Building a systematic approach to performance engineering using proven investigation frameworks and AI-assisted diagnostics
• Creating executive-ready performance reports, visualizing test results for non-technical audiences, and delivering actionable benchmarking recommendations and test deliverables

MODULE 8: Real-World Project Execution & Career Growth

Apply everything you have learned by executing a complete end-to-end performance engineering project and prepare for a successful career in the industry. By the end of this module, you will be able to plan, execute, analyze, and present performance testing outcomes with confidence.

• Executing a real-world performance engineering project from planning and scripting to test data preparation, load execution, and live monitoring
• Analyzing test results, performing root cause analysis, and delivering performance tuning recommendations based on collected evidence
• Creating comprehensive performance reports and presenting findings effectively to technical teams and business stakeholders
• Preparing for performance engineering careers with interview guidance, resume and LinkedIn optimization, salary insights, and personalized career roadmaps

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