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Build & Publish Versioned Docker Images

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Build & Publish Versioned Docker Images

This course is part of multiple programs.

Instructor: Hurix Digital

Included with

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2 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Containerization removes environment inconsistencies, creating portable data processing across dev, test, and production.
Systematic versioning and tagging strategies are essential for maintaining reliable deployment pipelines and enabling rollback capabilities.
Integration between container registries and orchestration platforms forms the backbone of modern cloud-native data infrastructure.
Reproducible containerized environments are fundamental to collaborative data engineering and DevOps practices.

Skills you'll gain

Tools you'll learn

Details to know

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This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 2 modules in this course

Transform your data engineering workflows with enterprise-grade containerization skills that eliminate "works on my machine" problems forever. This Short Course empowers data engineers to master the critical containerization pipeline from development to production deployment.

By completing this course, you'll confidently create robust Dockerfiles that package complex data processing environments, systematically version and tag container images for release management, and seamlessly integrate with cloud-native deployment pipelines. You'll discover how to eliminate environment inconsistencies, accelerate team collaboration, and establish the foundation for scalable, reproducible data infrastructure. By the end of this course, you will be able to: - Apply containerization to build and publish versioned images with runtime dependencies This course is unique because it bridges the gap between development containerization and production-ready deployment, focusing specifically on data engineering use cases with hands-on experience using industry-standard tools like Amazon ECR and Kubernetes. To be successful in this course, you should have basic familiarity with command-line interfaces, understanding of software dependencies, and exposure to data processing concepts.

Module details

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

What's included

3 videos1 reading1 assignment1 ungraded lab

3 videosTotal 15 minutes

Why Containerization Transforms Data Engineering Workflows3 minutes
Container Fundamentals for Data Processing Environments9 minutes
Building Multi-stage Dockerfiles for Spark Data Processing3 minutes

1 readingTotal 10 minutes

Multi-stage Dockerfile Architecture for Data Processing10 minutes

1 assignmentTotal 3 minutes

Container Fundamentals Knowledge Check3 minutes

1 ungraded labTotal 20 minutes

Build Production-Ready Multi-stage Dockerfile for Data Processing20 minutes

Learners will implement systematic version tagging strategies and integrate with enterprise container registries for Learners will master containerization fundamentals and create production-ready multi-stage Dockerfiles for data processing environments.