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Apache JMeter Performance Testing Course with CI/CD, Dynatrace ,Groovy & Grafana – Live Training Demo

Apache JMeter Performance Testing Course with CI/CD, Dynatrace ,Groovy & Grafana – Live Training (Master end-to-end performance testing with Apache JMeter with Groovy, REST API, GraphQL, CI/CD, Jenkins, GitHub Actions, Docker, Kubernetes, Grafana, InfluxDB, Dynatrace Distributed Testing & CI/CD Pipelines) …

Event Information

  • Price Rs.8,900.00 per participant
  • Location Online
  • Start Time 8:00 pm August 17, 2026
  • Finish Time 9:00 pm August 17, 2026
  • Capacity Limited to 100 people

Apache JMeter Performance Testing Course with CI/CD, Dynatrace ,Groovy & Grafana – Live Training

(Master end-to-end performance testing with Apache JMeter with Groovy, REST API, GraphQL, CI/CD, Jenkins, GitHub Actions, Docker, Kubernetes, Grafana, InfluxDB, Dynatrace Distributed Testing & CI/CD Pipelines)

 

Master Apache JMeter Performance Testing with our comprehensive, industry-focused live training program designed for aspiring Performance Test Engineers and experienced QA professionals. This course provides in-depth knowledge of performance engineering concepts, JMeter architecture, scripting, parameterization, correlation, REST API testing, advanced Groovy scripting, distributed load testing, and performance analysis. Through practical labs and real-world scenarios, you’ll gain the skills to design, execute, and optimize enterprise-grade performance tests with confidence.

The program also covers modern performance engineering practices, including CI/CD integration with Jenkins and GitHub Actions, monitoring using Grafana and Dynatrace, Docker and Kubernetes-based load testing, and enterprise reporting. With hands-on projects, a real-time capstone, interview-focused guidance, and expert mentor support, you’ll develop the practical expertise needed to deliver high-performing, scalable, and reliable applications in real-world enterprise environments.

 

About The Instructor:

Visvashwarr is a Performance Engineering expert with over 11 years of industry experience in designing, executing, and optimizing enterprise-scale performance testing solutions. He has worked across diverse domains, including Enterprise SIEM platforms, Web Applications, REST & SOAP APIs, Oracle Retail Applications, ETL Batch Processing, and Messaging Queue (MQ) systems, helping organizations build scalable, reliable, and high-performing applications.

His expertise includes Apache JMeter, LoadRunner, Performance Engineering, API Performance Testing, Groovy Scripting, Dynatrace, AppDynamics, Grafana, CI/CD Integration, Docker, Kubernetes, Jenkins, AWS, and Oracle Cloud. He has extensive experience in identifying and resolving complex performance bottlenecks such as memory leaks, JVM heap issues, garbage collection overhead, thread contention, response time degradation, load balancing, and high-availability challenges.

With 5+ years of professional training experience, Vishweshwar has successfully trained 300+ students and working professionals through instructor-led, hands-on training programs. His practical teaching methodology combines real-world projects, live demonstrations, performance analysis techniques, and interview-focused guidance, enabling learners to gain industry-ready skills. Throughout this course, he shares practical insights, real-world case studies, and proven best practices, helping participants confidently execute enterprise-level Performance Engineering projects and accelerate their careers in Performance Testing and Performance Engineering.


Live Sessions Price:

For LIVE sessions – Offer price after discount is 200 USD 159 USD 109 USD Or 15000 INR 13000 INR 8900 Rupees.

 

Enroll For Free Demo

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Free Demo Session:

17th  August @ 8:00 PM – 9:00 PM (IST) (Indian Timings)

17th August @ 10:30 AM – 11:30 AM (EST) (U.S Timings)

17th August @ 3:30 PM – 4:30 PM (BST) (UK Timings)

 

Class Schedule:

For Participants in India: Monday to Friday @ 8:00 PM – 9:00 PM (IST)

For Participants in the US:  Monday to Friday @ 10:30 AM – 11:30 AM (EST)

For Participants in the UK:  Monday to Friday @ 3:30 PM – 4:30 PM (BST)

 

What student’s have to say about Trainer :

⭐ The course focuses on real-world performance testing challenges rather than just theory. I gained confidence in creating scalable JMeter scripts, analyzing bottlenecks, and generating professional performance reports.” – Anjali.

⭐ An ideal course for anyone looking to build a successful career in JMeter – Rahul.

⭐ This course helped me build production-ready JMeter scripts and improve my performance engineering skills.– Priya.

⭐ I gained practical experience in identifying performance bottlenecks, analyzing reports, and optimizing application performance. The hands-on approach made learning both engaging and effective. This is one of the best JMeter training programs available. – Mohammed.

⭐ Very interactive and engaging sessions. Trainer focuses on practical implementation, which helped me prepare for interviews and real-time projects. – Neha.

⭐ I was impressed by the depth of the course and the focus on real-time enterprise scenarios. From JMeter fundamentals to advanced Groovy scripting and observability tools, every topic was covered thoroughly. The live demonstrations made complex concepts easy to understand. The hands-on exercises boosted my confidence in handling production workloads. I would strongly recommend this course to aspiring Performance Engineers. – Suresh.


What will I Learn by end of this course?

  • Build correlated, parameterised JMeter scripts with Groovy HMAC signing
  • Write advanced Groovy: HMAC crypto, file I/O, token refresh, error budgets
  • Run distributed tests across multiple machines or K8s pods
  • Stream live metrics to Grafana + InfluxDB during test execution
  • Build Jenkins pipelines with performance gates and trend analysis
  • Write GitHub Actions workflows with PR comments and matrix environments
  • Annotate Dynatrace with JMeter test runs via the Events API
  • Query Dynatrace Davis AI problems API and auto-abort on HIGH severity
  • Build SLO-gated promotion pipelines with zero human approval
  • Produce executive-ready reports and stakeholder presentations

 

Salient Features:

  • 32 Hours of Live Training along with recorded videos
  • 1 Year access to the recorded videos
  • Course Completion Certificate

 

Who can enroll in this course?

  • Software Test Engineers (Manual & Automation)
  • Performance Test Engineers and Performance Engineers
  • QA Engineers and QA Leads
  • SDET (Software Development Engineers in Test)
  • API Testing Professionals
  • DevOps and CI/CD Engineers
  • Site Reliability Engineers (SREs)
  • Developers interested in Performance Engineering
  • System Administrators and Infrastructure Engineers
  • Freshers and graduates looking to build a career in Performance Testing
  • Professionals preparing for Performance Testing and Performance Engineering interviews
  • Anyone who wants to master Apache JMeter with real-world enterprise projects and industry best practices

 

Course syllabus:

Phase 1: Foundations & Core Concepts (Sessions 1–5 · Build the mental model before touching the tool)
Session 1: Performance Engineering Mindset & JMeter Overview
Why performance testing exists, where JMeter fits, and how to think before writing a single script.
  • Load · Stress · Spike · Soak · Endurance
  • NFRs and SLAs
  • Apdex score
  • JMeter vs LoadRunner vs k6
  • Lab: Install JMeter + Launch GUI

Session 2: JMeter Architecture & Installation Deep-Dive
Thread model, JVM heap sizing, jmeter.properties, GUI vs Non-GUI mode, and plugin classpath.
  • One thread = one virtual user
  • -Xms / -Xmx heap sizing
  • jmeter.properties vs user.properties
  • Lab: Configure JVM & Run First Non-GUI Test

Session 3: Test Plan Anatomy — Every Component Explained
The execution hierarchy, scope rules, and the mental map you’ll use for every script you write.
  • Execution order: Pre → Sampler → Post → Assert
  • Thread Group / Sampler / Controller / Listener
  • Config Elements & scope rules
  • Lab: Build a 3-Request Test Plan from Scratch

Session 4: HTTP Sampler & Proxy Recording
Record real user journeys, handle HTTPS certs, filter static resources, and clean up captured scripts.
  • Proxy recorder setup (port 8888)
  • HTTPS certificate installation
  • Filtering CSS / JS / images
  • Lab: Record a Login Flow

Session 5: Thread Groups & Load Shape Basics

Thread count, ramp-up, duration, think time, and the throughput vs concurrency mental model.

  • Thread count vs Ramp-up vs Duration
  • Loop Count vs Scheduler
  • Constant / Uniform / Gaussian Timer
  • Lab: Ramp 100 Users Over 5 Minutes

Phase 2: Scripting Mastery (incl. Groovy Deep-Dive) (Sessions 6–14 · Build production-grade, parameterised, correlated scripts — with full Groovy mastery)

Session 6: Correlation — The #1 Scripting Skill
Why replayed recordings fail, and how to extract and reuse dynamic values.
  • Regular Expression Extractor
  • JSON Extractor (JSONPath / JMESPath)
  • XPath 2.0 · Boundary Extractor
  • Lab: Correlate a JWT Token

Session 7: Parameterisation & Data-Driven Testing

CSV Data Set Config, sharing modes, recycle strategies, and built-in functions for unique data.

  • CSV Data Set Config — all options
  • Sharing modes: All Threads / Thread
  • __RandomString · __UUID · __counter
  • Lab: 500-User Login with Unique Credentials

Session 8: Assertions & Validation

Multi-layer assertions that catch business failures, not just HTTP errors.
  • Response Assertion
  • JSON Assertion
  • Duration Assertion (SLA enforcement)
  • JSR223 Assertion (Groovy)
  • Lab: Validate API Response Schema

Session 9: Controllers — Logic & Flow

Branching, looping, traffic splitting, and grouping for realistic user journey modelling.
  • If · While · Loop Controller
  • Transaction Controller
  • Throughput Controller (traffic splits)
  • Lab: Simulate Browse → Cart → Checkout

Session 10: Pre & Post Processors
Logic before and after every request — dynamic headers, request signing, response processing.
  • JSR223 PreProcessor (Groovy)
  • JSR223 PostProcessor
  • HTTP Header Manager · Cookie Manager
  • Lab: Dynamic Auth Header per Request

Session 11: Groovy Scripting — Language Essentials EXPANDED
Master Groovy types, closures, collections, all JMeter context objects (vars/props/prev/sampler/ctx), null safety, and string manipulation — with full runnable code examples.
  • def / GString / GDK methods
  • vars · props · log · prev · ctx · sampler
  • collect · findAll · inject · each
  • ?. operator · Elvis ?: · null safety
  • Lab: Groovy String & Collection Workout

Session 12: Groovy Scripting — Advanced Patterns NEW
HTTP calls from Groovy, file I/O at runtime, HMAC-SHA256 request signing, compiled script caching, and shared utility library via props.
  • HttpURLConnection from Groovy
  • HMAC-SHA256 + Base64 signing
  • File.text · readLines · append
  • Compiled script caching — static vars only
  • Lab: HMAC-SHA256 Request Signing

Session 13: Groovy Scripting — Real-World Recipes NEW
Auto token refresh on 401, dynamic JSON body builder, response schema validation, custom CSV log, and global error budget counter with AtomicInteger.
  • Token refresh on 401 via If Controller
  • JsonBuilder — nested dynamic payloads
  • JsonSlurper schema validation
  • AtomicInteger error budget counter
  • Lab: Auto Token Refresh on 401

Session 14: REST API, GraphQL & OAuth 2.0 Testing
Full CRUD, GraphQL queries, OAuth 2.0 token flows, and API chaining patterns.
  • HTTP verbs: GET POST PUT PATCH DELETE
  • GraphQL over HTTPOAuth 2.0 client_credentials & password grant
  • Lab: Full CRUD Test

Phase 3: Execution, Monitoring & Analysis (Sessions 15–20 · Run tests right and read what they’re telling you)
Session 15: Listeners, Results & HTML Reporting
What to capture, what to skip, JTL format, and generating professional HTML dashboards.
  • Summary vs Aggregate Report
  • JTL file — every column explained
  • HTML Dashboard Report
  • Lab: Generate Full HTML Report from JTL

Session 16: Non-GUI Mode & Command-Line Mastery
CLI flags, property overrides, log levels, and CI/CD integration signals.
  • jmeter -n -t -l -e -o
  • -Jpropname=value runtime overrides
  • ${__P(propname, default)}
  • Lab: Parameterise Test via CLI

Session 17: Distributed Testing — Master / Worker Architecture
RMI config, data distribution across workers, and result aggregation.
  • RMI port & remote_hosts config
  • CSV partitioning across workers
  • Result aggregation
  • Lab: 3-Worker Distributed Test

Session 18:Metrics That Matter — Interpreting Results
Throughput, percentile latency, error rate, Apdex, saturation — reading data like an engineer.
  • P90 / P95 / P99 — which to use when
  • Throughput plateau = saturation signal
  • Apdex score · Concurrency curve
  • Lab: Identify the Saturation Point

Session 19: Real-Time Monitoring: Grafana + InfluxDB
Backend Listener setup, Grafana dashboard 5496, custom panels, threshold alerts.
  • Backend Listener → InfluxDB
  • Grafana dashboard ID 5496
  • Alert rules on P95 breach
  • Lab: Live Dashboard During 1000-User Test

Session 20: Server-Side Monitoring & APM Fundamentals
JVM metrics, GC analysis, DB pool exhaustion, ELK log correlation, and APM introduction.
  • GC pause correlation with P99 spikes
  • DB connection pool exhaustion pattern
  • Kibana + ELK log correlation
  • Lab: Correlate P99 Spike with GC Full Event

Phase 4: Advanced Topics (Sessions 21–25 · Enterprise-grade patterns and professional reporting)
Session 21: Advanced Load Shapes — Concurrency & Arrivals
Model production traffic accurately with Concurrency Thread Group, Arrivals Thread Group, Throughput Shaping Timer.
  • Concurrency Thread Group (JP@GC)
  • Arrivals Thread Group (RPS-based)
  • Throughput Shaping Timer · Flash-sale patterns
  • Lab: Model a Flash Sale Traffic Spike

Session 22: Plugins, WebSocket & Non-HTTP Protocols
Plugin Manager, WebSocket sampler, JDBC database load testing.
  • JMeter Plugin Manager
  • WebSocket Sampler
  • JDBC Request Sampler + Connection Config
  • Lab: 200-User Database Read Load Test

Session 23: Bottleneck Analysis & Root Cause Methodology
Thread dump analysis, GC log interpretation, connection pool exhaustion, N+1 query detection.
  • Flat vs waterfall latency signatures
  • Thread dump analysis
  • GC log — G1GC pause patterns
  • Lab: RCA on a Deliberately Broken App

Session 24: Docker & Kubernetes for JMeter
Containerised load generation — Dockerfile, Docker Compose master/worker, K8s Jobs.
  • JMeter Dockerfile
  • Docker Compose: master + 3 workers
  • JMeter on Kubernetes — ephemeral workers
  • Lab: 5000-User Test via K8s Cluster

Session 25: Performance Reporting & Stakeholder Communication
NFR gathering, test strategy, executive summaries, and risk communication.
  • NFR gathering template
  • Executive summary: one page, clear verdict
  • Pass/fail criteria framing
  • Lab: Write a 1-Page Executive Summary

Phase 5: CI/CD & Dynatrace Integration ALL NEW (Sessions 26–31 · Automated pipeline gates and full observability integration)
Session 26: CI/CD Part 1 — Jenkins Pipeline Integration NEW
Complete Jenkinsfile with performance gate, build trend analysis, JTL archiving, and email notification on failure.
  • Jenkins Performance Plugin
  • Jenkinsfile declarative pipeline
  • errorFailedThreshold · relativeFailedThresholdPositive
  • Build trend analysis across 10 builds
  • Lab: Jenkinsfile with Performance Gate

Session 27: CI/CD Part 2 — GitHub Actions & Azure DevOps NEW
Complete perf.yml, matrix strategy for parallel environment testing, PR comment automation, Azure DevOps and GitLab CI pipelines.
  • GitHub Actions — full perf.yml workflow
  • Matrix strategy: dev / staging / prod in parallel
  • PR comment via GitHub API
  • Azure DevOps · GitLab CI
  • Lab: GitHub Actions PR Comment with P95 Result

Session 28: CI/CD Part 3 — Advanced Pipeline Patterns NEW
Environment promotion gates, parallel test sharding across CI agents, scheduled nightly soak tests, chaos hooks, and Slack/Teams notifications.
  • Promotion gate: block staging→prod on SLA breach
  • Parallel sharding across CI agents
  • Nightly cron soak test (8-hour schedule)
  • Slack webhook notifications
  • Lab: Slack Notification on Test Completion

Session 29: Dynatrace Integration Part 1 — OneAgent & PurePath NEW
Dynatrace architecture, PurePath distributed tracing, test annotation API, x-dynatrace header injection, and filtering test data by timeframe.
  • OneAgent · ActiveGate · Smartscape
  • PurePath — end-to-end distributed trace
  • Test annotation API: POST /api/v1/events
  • x-dynatrace header linking requests to PurePaths
  • Lab: Annotate a JMeter Test Run in Dynatrace

Session 30: Dynatrace Integration Part 2 — Davis AI & Problem Detection NEW
Davis AI anomaly detection, Problems API real-time querying, Smartscape impact analysis, automatic baselining, and pipeline integration to fail build on HIGH severity.
  • Davis AI — automatic anomaly detection
  • GET /api/v2/problems — real-time querying
  • Smartscape topology-aware impact analysis
  • Auto-abort test on HIGH problem via Groovy
  • Lab: Auto-Abort Test on Dynatrace HIGH Problem

Session 31: Dynatrace + CI/CD — Full Integrated Pipeline NEW
Complete observability-driven pipeline: annotate Dynatrace → JMeter run → pull problems → SLO gate via Metrics API v2 → Slack notification → auto-promotion.
  • Full pipeline: commit → test → gate → notify → promote
  • Dynatrace SLO-based quality gate
  • Metrics API v2: service response time SLO
  • Pipeline as evidence for change advisory record
  • Lab: End-to-End JMeter + Dynatrace Gate

Phase 6: Real-World Mastery & Capstone (Enterprise campaign — own it from brief to sign-off)
Session 32: Capstone Project — Enterprise Performance Campaign
Full 3-environment campaign: correlated Groovy-signed script → distributed execution with live Grafana + Dynatrace → CI/CD pipeline gate → executive report + 5-min stakeholder presentation.
  • 3-environment test strategy with Dynatrace SLOs
  • Groovy HMAC signing + auto token refresh + error budget
  • Distributed (3 workers) + Grafana live + DT annotated
  • CI/CD: Jenkins + GitHub Actions + DT problems gate
  • Executive report + Slack notification + 10-slide deck

 

How can I enroll for this course?

 

Enroll For Free Demo

OR

For any other details, Call me or Whatsapp me on +91-9133190573

 

Live Sessions Price:

For LIVE sessions – Offer price after discount is 200 USD 159 USD 109 USD Or 15000 INR 13000 INR 8900 Rupees.

 


FAQ –Apache JMeter Performance Testing Course with CI/CD, Dynatrace & Grafana:

1️⃣ Who can enroll in this course?

This course is ideal for Manual Testers, Automation Test Engineers, Performance Test Engineers, QA Professionals, Developers, DevOps Engineers, SREs, and freshers who want to build expertise in Performance Engineering.


2️⃣ Do I need prior experience with Apache JMeter?

No. The course starts with JMeter fundamentals and gradually progresses to advanced enterprise-level topics, making it suitable for both beginners and experienced professionals.


3️⃣ What tools and technologies will I learn?

You will learn Apache JMeter, Groovy, REST API Performance Testing, Grafana, Dynatrace, Docker, Kubernetes, Jenkins, GitHub Actions, CI/CD, and enterprise performance engineering practices.


4️⃣ Is this course practical or theory-based?

The training is highly practical, with hands-on labs, real-world assignments, enterprise use cases, and a capstone project to reinforce your learning.


5️⃣ Will I work on real-time projects?

Yes. The course includes real-world performance testing scenarios and an enterprise capstone project to help you gain practical experience.


6️⃣ Will I receive a course completion certificate?

Yes. A Course Completion Certificate will be awarded after successfully completing the training.


7️⃣ Are session recordings provided?

Yes. Recorded sessions will be available so you can revisit the lessons anytime for revision.


8️⃣ Will this course help me prepare for interviews?

Absolutely. The course includes interview-focused guidance, practical exercises, and industry best practices to help you confidently attend Performance Testing and Performance Engineering interviews.


9️⃣ What career opportunities can I pursue after this course?

You can apply for roles such as Performance Test Engineer, Performance Engineer, QA Engineer, SDET, DevOps Engineer, and Site Reliability Engineer (SRE).


🔟 Will I get support after the training?

Yes. You will receive mentor support, guidance for practical exercises, and assistance with your learning throughout the course.

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