Path overview
In this path, you’ll learn how to use Docker and Kubernetes to containerize and orchestrate data engineering applications. You’ll build reproducible environments, manage multi-service deployments, and prepare production-ready containerized systems through practical, real-world exercises.
Key skills
- Building and deploying containerized applications with Docker
- Orchestrating multi-service applications with Kubernetes
- Preparing containerized workloads for cloud deployment
Path outline
Containerization and Infrastructure with Docker and Kubernetes [2 courses]
Course 1: Docker Fundamentals 6h
Course Objectives- Install Docker Desktop and run containers using both CLI and GUI tools
- Pull images from Docker Hub and manage container lifecycles
- Run PostgreSQL databases in containers and connect to them for data workflows
- Use Docker volumes to persist data across container restarts
- Define multi-service applications using Docker Compose with environment variables and service connections
- Build custom Docker images for Python data processing scripts
- Implement health checks to prevent race conditions in multi-container applications
- Apply multi-stage builds to reduce image size and separate build from runtime concerns
- Harden containers by running as non-root users and externalizing secrets with environment files
Course 2: Introduction to Kubernetes 6h
Course Objectives- Deploy applications to Kubernetes clusters and understand core components including pods, deployments, and services
- Configure Services for stable networking that survives pod restarts and IP address changes
- Implement rolling updates for zero-downtime deployments and use namespaces for environment separation
- Add health checks and resource limits to build production-ready applications for shared clusters
- Manage configuration and secrets externally using ConfigMaps and Secrets
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