Coursera

DevOps and CI/CD for Data Engineering Performance

Coursera

DevOps and CI/CD for Data Engineering Performance

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Resolve merge conflicts and trace bugs using Git history tools, keeping collaborative codebases stable and production-ready.

  • Design branching strategies and automate deployments with CI/CD pipelines to safely promote data pipeline artifacts across environments.

  • Build and publish versioned Docker images and automate server configuration with Ansible for consistent, reproducible environments.

  • Analyze query execution metrics and optimize resource allocation to maintain performance targets in production data systems.

Details to know

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Recently updated!

March 2026

Assessments

21 assignments¹

AI Graded see disclaimer
Taught in English

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This course is part of the Open source Data Engineering with Spark, dbt & Airflow Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
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There are 13 modules in this course

You will learn systematic approaches to resolve merge conflicts that automated Git processes cannot handle, distinguishing between text-based line conflicts and binary file selection strategies in data engineering environments.

What's included

2 videos1 reading1 assignment

You will learn systematic debugging techniques using Git's historical analysis capabilities to identify the exact commit that introduced software defects through binary search and commit analysis methodologies.

What's included

3 videos1 reading2 assignments

You will understand fundamental branching models and design strategic workflows that enable parallel development while maintaining code stability.

What's included

2 videos1 reading2 assignments

You will implement their branching strategy using GitHub's protection features and automation tools, creating a production-ready development.

What's included

3 videos1 reading2 assignments

You will learn containerization fundamentals and create production-ready multi-stage Dockerfiles for data processing environments.

What's included

3 videos1 reading1 assignment1 ungraded lab

You will implement systematic version tagging strategies and integrate with enterprise container registries for automated deployment workflows.

What's included

2 videos2 readings2 assignments

You will understand why automation tools are essential for scalable infrastructure management and explore foundational configuration management concepts through real-world enterprise scenarios.

What's included

2 videos1 reading2 assignments

You will create functional Ansible playbooks that automate Python installation, pip package management, systemd service configuration, and webserver verification to achieve consistent server deployments across multiple environments.

What's included

2 videos2 readings2 assignments1 ungraded lab

You will learn the foundational concepts and practical applications of CI/CD pipelines for data deployment automation.

What's included

3 videos1 reading1 assignment

You will implement comprehensive automated deployment workflows that safely promote data pipeline components from staging to production with proper validation and monitoring.

What's included

2 videos2 readings2 assignments1 ungraded lab

You will learn the fundamentals of query performance analysis by learning to identify bottlenecks, interpret execution plans, and understand key performance metrics that guide optimization decisions.

What's included

4 videos1 reading1 assignment

You will apply performance analysis insights to make strategic resource allocation decisions and implement targeted optimizations that maintain service level agreements in production environments.

What's included

2 videos1 reading2 assignments

You will create a complete DevOps workflow that integrates version control, containerization, automation, and performance optimization to deploy and maintain data engineering systems. This project combines Git conflict resolution, Docker containerization, Ansible automation, CI/CD pipeline design, and query performance optimization into a realistic enterprise deployment scenario.

What's included

4 readings1 assignment

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Instructor

Professionals from the Industry
307 Courses 44,329 learners

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.