Kubernetes Container Orchestration
COURSE.002

Kubernetes Container Orchestration

Master container orchestration for deploying and managing scalable applications in production environments

¥49,000

Course Overview

This training program provides comprehensive instruction in container orchestration using Kubernetes, the industry standard for managing containerized applications at scale. The curriculum begins with Docker containerization fundamentals before progressing to Kubernetes architecture and core components.

Participants learn pod management strategies, service discovery mechanisms, and ingress controller configuration for external access. The program addresses persistent storage solutions for stateful applications, security policy implementation, and cluster monitoring strategies for production environments.

The course covers CI/CD pipeline implementation using Kubernetes, performing rolling updates without downtime, and managing multi-tenant clusters with resource isolation. Students gain practical experience deploying microservices applications, implementing horizontal pod auto-scaling, and configuring high-availability cluster architectures.

Designed for DevOps engineers and cloud architects working with containerized applications, the training emphasizes hands-on laboratory exercises. Participants configure Kubernetes clusters, deploy applications using manifests and Helm charts, and troubleshoot common operational issues in controlled virtual environments.

Technical Competencies

Develop operational skills across container orchestration and cloud-native application deployment

Container Management

Build Docker images using multi-stage builds and best practices. Manage container lifecycle, networking, and storage across development and production environments.

Kubernetes Architecture

Understand control plane and worker node components. Configure etcd, API server, scheduler, and controller manager for cluster operations and resource management.

Application Deployment

Deploy applications using Deployments, StatefulSets, and DaemonSets. Implement rolling updates, rollback strategies, and health check configurations for reliability.

Cluster Operations

Configure horizontal pod autoscaling based on metrics. Manage resource quotas, limit ranges, and implement pod security policies for multi-tenant environments.

Tools and Technologies

Docker Engine

Container runtime and image building platform. Learn Dockerfile syntax, image layering, and registry operations for artifact management.

kubectl CLI

Command-line interface for cluster interaction. Master resource management, debugging commands, and declarative configuration application.

Helm Charts

Package manager for Kubernetes applications. Create and manage chart templates for repeatable application deployments across environments.

Prometheus

Monitoring and alerting toolkit for metrics collection. Configure service discovery, create recording rules, and build monitoring dashboards.

CI/CD Integration

Pipeline tools including Jenkins and GitLab CI. Implement automated testing, image building, and deployment workflows for applications.

Cloud Platforms

Managed Kubernetes services including EKS, GKE, and AKS. Understand cloud-native integration patterns and platform-specific features.

Training Approach

Progressive Skill Development

Training begins with containerization fundamentals before advancing to orchestration concepts. Each module introduces increasingly complex scenarios, ensuring participants build solid understanding of core principles before tackling advanced cluster management topics.

Practical Laboratory Exercises

Virtual lab environments provide access to multi-node Kubernetes clusters for hands-on practice. Participants deploy applications, configure networking, implement storage solutions, and troubleshoot common operational issues in realistic scenarios without production system risk.

Real-World Application Projects

Course projects involve deploying microservices architectures, implementing service mesh patterns, and configuring observability stacks. These practical exercises mirror actual DevOps workflows, preparing participants for operational responsibilities in production environments.

Expert-Led Instruction

Courses delivered by certified Kubernetes administrators with production deployment experience. Small class format allows detailed technical discussion and individualized guidance on implementation patterns and operational best practices.

Professional Audience

DevOps Engineers

Operations professionals implementing container orchestration for application deployment automation and infrastructure modernization initiatives.

  • CI/CD pipeline development
  • Infrastructure automation focus

Cloud Architects

Infrastructure designers developing cloud-native application platforms and containerized workload deployment strategies for organizations.

  • Platform architecture design
  • Cloud-native technology adoption

Software Engineers

Developers seeking understanding of container orchestration to optimize application deployment and operational characteristics in Kubernetes environments.

  • Container-aware development
  • Deployment optimization skills

System Administrators

Infrastructure operators transitioning to container-based platforms and expanding technical capabilities into orchestration and microservices management.

  • Platform modernization skills
  • Container operations expertise

Skill Assessment

Competency evaluation through practical demonstrations and implementation exercises

Deployment Projects

Participants deploy complete application stacks including databases, application servers, and ingress controllers. Project evaluation assesses manifest structure, resource configuration, and operational considerations.

Configuration Management

Hands-on exercises creating ConfigMaps, Secrets, and persistent volume claims. Participants demonstrate understanding of application configuration patterns and state management in Kubernetes.

Troubleshooting Exercises

Problem scenarios requiring diagnosis of pod failures, networking issues, and resource constraints. Assessment evaluates systematic approach to identifying and resolving cluster problems using kubectl and logging tools.

Performance Optimization

Tasks involving resource request and limit tuning, autoscaling configuration, and performance monitoring setup. Participants demonstrate ability to optimize application performance within cluster constraints.

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