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Build & Publish Versioned Docker Images

本课程是多个项目的一部分。

位教师：Hurix Digital

包含在中

了解更多

2个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

2个模块

深入了解一个主题并学习基础知识。

初级等级

推荐体验

2 小时完成

灵活的计划

自行安排学习进度

您将学到什么

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.

您将获得的技能

您将学习的工具

要了解的详细信息

可分享的证书

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了解顶级公司的员工如何掌握热门技能

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

此课程作为的一部分提供

在注册此课程时，您还需要选择一个特定的合作项目。

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获得对主题或工具的基础理解
通过实践项目培养工作相关技能
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该课程共有2个模块

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.

单元详情

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

涵盖的内容

3个视频1篇阅读材料1个作业1个非评分实验室

3个视频总计15分钟

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

1篇阅读材料总计10分钟

Multi-stage Dockerfile Architecture for Data Processing10分钟

1个作业总计3分钟

Container Fundamentals Knowledge Check3分钟

1个非评分实验室总计20分钟

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

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.