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Course Outline

[Day 01]

Course Introduction

  • Comparative analysis: Containers versus virtual machines
  • Performance optimization and operational speed

Examination of Docker architectural frameworks

  • Integration of Docker with the Linux kernel for government environments
  • Essential Docker components (client, daemon, images, registry, containers)

Leveraging Docker for container execution and administration

  • Management of images, containers, volumes, and networks

Fundamental concepts in container orchestration

Installation and configuration of Docker

Retrieval of container images from external repositories

  • Demonstration using Apache Tomcat

Execution of deployed containers

Management of Docker image registries

  • Distinction between public and private registry access

Development and maintenance of Dockerfiles

Compilation of custom Docker images

Deployment of web-based applications

  • Implementation example: Java EE application server

Inter-container communication protocols

Configuration of storage volumes and network structures in Docker

  • Data linkage and state management


[Day 02]

Advanced exploration of Kubernetes for container orchestration

Detailed analysis of Kubernetes system architecture

  • Core elements: Pods, labels, selectors, replication controllers, services, and API

Establishment of a Kubernetes cluster environment

Creation and management of Kubernetes pods, volumes, and deployments

Organizational structure and cluster resource grouping

Service discovery and publication mechanisms

Connectivity and discovery of individual containers

Deployment of enterprise web applications

  • Management of distributed application components
  • Configuration of database connectivity

Security frameworks for Kubernetes

  • Authentication and authorization protocols

Advanced network configuration strategies

  • Comparative analysis: Docker networking versus Kubernetes networking

Monitoring and observability of Kubernetes clusters

  • Centralized logging via Elasticsearch and Fluentd
  • Container-level metrics (cAdvisor UI, Influxdb, Prometheus)


[Day 03]

Strategies for scaling Kubernetes clusters

Infrastructure requirements for Kubernetes deployment

  • Resource provisioning, partitioning, and network setup

Construction of high-availability cluster environments

  • Load balancing algorithms and service discovery implementations

Deployment of scalable application architectures

  • Implementation of horizontal pod autoscaling
  • Database clustering within Kubernetes infrastructure

Application update and release management

  • Version control and release processes in Kubernetes

Diagnostic procedures and troubleshooting

Concluding summary and next steps

Requirements

  • Proficiency with Linux command-line interfaces
  • Fundamental comprehension of virtualization principles
  • Working knowledge of networking frameworks and protocols
  • Understanding of web application architecture and functionality

Target Audience

  • Software Engineers and Developers
  • Systems and Software Architects
  • Deployment and Release Engineers
 21 Hours

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