Master Docker, CI/CD Pipelines, Dockerfiles & Build Scalable Test Automation Frameworks for QA Engineers and SDETs
β±οΈ Length: 10.7 total hours
β 4.65/5 rating
π₯ 1,547 students
π November 2025 update
Add-On Information:
Get Instant Notification of New Courses on our Telegram channel.
Noteβ Make sure your ππππ¦π² cart has only this course you're going to enroll it now, Remove all other courses from the ππππ¦π² cart before Enrolling!
- Course Overview
- This comprehensive training program is specifically engineered to transition quality assurance professionals into the realm of DevOps-enabled testing, ensuring that every SDET can confidently manage containerized environments.
- The curriculum focuses on the architectural shift from monolithic local test executions to scalable, distributed testing infrastructures using the power of Docker engine and its ecosystem.
- Students will explore the core philosophy of containerization, understanding why the “it works on my machine” syndrome is a critical bottleneck in modern software delivery and how Docker resolves it for QA teams.
- The course provides a deep dive into Dockerizing heterogeneous automation frameworks, including those built on Selenium, Playwright, Cypress, and Appium, ensuring cross-tool compatibility.
- Participants will master the art of orchestrating multi-container environments, where the application under test, its supporting databases, and the testing tools themselves coexist in a synchronized virtual network.
- A significant portion of the course is dedicated to optimization strategies for test execution, teaching learners how to achieve massive parallelization and significantly reduce build times in the pipeline.
- The training emphasizes Infrastructure as Code (IaC) principles, allowing testers to version control their testing environments just as easily as they version control their automation scripts.
- Requirements / Prerequisites
- A foundational understanding of software testing life cycles (STLC) and familiarity with at least one object-oriented programming language like Java, Python, or JavaScript is highly recommended.
- Basic comfort with Command Line Interfaces (CLI) and terminal operations is necessary, as the majority of Docker interactions are performed via the command prompt or shell.
- Learners should have administrative access to their workstations to install Docker Desktop or Docker Engine and configure virtualization settings in the BIOS/UEFI.
- Functional knowledge of Git and version control systems is beneficial, as the course involves pulling repositories and managing configuration files for container builds.
- A stable internet connection capable of downloading large Docker images and layers from public registries like Docker Hub is essential for the hands-on lab sessions.
- Prior exposure to automated web or API testing will help in understanding the context of why certain containers are configured for specific browser drivers or network protocols.
- Skills Covered / Tools Used
- Docker Engine & Architecture: Mastering the lifecycle of containers, from image creation and pulling to starting, stopping, and monitoring active instances.
- Dockerfile Crafting: Learning to write production-grade Dockerfiles using multi-stage builds to minimize image size and improve security for test runners.
- Docker Compose: Utilizing YAML configurations to manage multi-service applications, ensuring seamless communication between the app and the test automation suite.
- Container Networking: Configuring bridge, host, and overlay networks to simulate complex production environments and ensure isolated test execution.
- Persistent Data Management: Implementing Docker Volumes and Bind Mounts to ensure that test reports, logs, and screenshots are preserved after a container terminates.
- Selenium Grid in Docker: Setting up scalable browser clusters using official Selenium images to perform cross-browser testing without maintaining local infrastructure.
- CI/CD Integration: Incorporating Docker commands into Jenkins pipelines, GitHub Actions, or GitLab CI to trigger automated tests upon every code commit.
- Image Registry Management: Working with Docker Hub and Private Registries to tag, push, and pull custom-built testing images across different team environments.
- Benefits / Outcomes
- Elimination of Environment Inconsistency: Achieve 100% parity between local development, testing, and production environments, resulting in reliable and repeatable test results.
- Enhanced Scalability: Gain the ability to spin up hundreds of browser instances or service mocks in seconds, enabling high-speed parallel execution that was previously impossible.
- Resource Optimization: Learn to run lightweight containers instead of heavy Virtual Machines, drastically reducing the hardware footprint and costs of the QA infrastructure.
- Improved Collaboration: Provide developers with a ready-to-run test environment in a single image, making it easier to reproduce bugs and verify fixes across teams.
- Career Advancement: Position yourself as a Modern SDET who understands the infrastructure layer, making you an invaluable asset in any Agile or DevOps-driven organization.
- Simplified Dependency Management: Package all necessary drivers, libraries, and binaries into a single portable unit, removing the need for complex manual setup on new machines.
- Accelerated Feedback Loops: Integrate testing directly into the deployment pipeline, providing developers with immediate insights into the quality of their code changes.
- PROS
- Hands-on Laboratory Focus: Unlike theoretical courses, this provides real-world scenarios that mimic the daily challenges faced by QA engineers in the industry.
- Up-to-Date Content: Includes the latest features of Docker 2025, ensuring that students learn current best practices rather than outdated legacy methods.
- QA-Specific Context: Every lesson is tailored for testing use cases, focusing on how to containerize test scripts rather than just generic application deployment.
- Comprehensive Resource Material: Access to a library of reusable Dockerfiles and Compose templates that can be directly implemented in professional projects.
- CONS
- Initial Learning Curve: Students with no prior Linux or networking knowledge may find the initial sections on container routing and permissions somewhat challenging to navigate.
Learning Tracks: English,IT & Software,Other IT & Software
Found It Free? Share It Fast!