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Course Outline

Module 1: Introduction to OpenShift and Kubernetes

  • OpenShift architecture and components
  • Relationship between OpenShift and Kubernetes
  • Containers, images, and registries
  • Overview of OpenShift editions (OKD vs OCP)

Module 2: OpenShift 4 Architecture

  • Control plane components
  • Worker nodes and MachineSets
  • Red Hat CoreOS overview
  • Operators and Operator Lifecycle Manager (OLM)

Module 3: Installing OpenShift 4

  • Installation methods (IPI vs UPI)
  • Cluster bootstrap process
  • Networking and DNS requirements
  • Hands-on cluster deployment

Module 4: Managing Cluster Resources

  • Nodes and MachineSets
  • Scaling the cluster
  • Resource quotas and limits
  • Namespaces and projects

Module 5: Deploying Applications

  • Deployments, ReplicaSets, Pods
  • Source-to-Image (S2I)
  • Container-based deployments
  • Rolling updates and rollbacks

Module 6: Working with Operators

  • Operator concept and benefits
  • Installing and managing Operators
  • Using Operators for application lifecycle
  • Custom Resource Definitions (CRDs)

Module 7: Networking in OpenShift

  • Cluster networking basics
  • Services and routes
  • Ingress and load balancing
  • Network policies

Module 8: Storage Management

  • Persistent Volumes (PV) and Persistent Volume Claims (PVC)
  • Storage classes
  • Stateful applications
  • Dynamic provisioning

Module 9: Security in OpenShift

  • Authentication and authorization (RBAC)
  • Security Context Constraints (SCC)
  • Managing users and roles
  • Securing applications and secrets

Module 10: Monitoring and Logging

  • Built-in monitoring stack
  • Metrics and alerts
  • Logging architecture
  • Troubleshooting cluster issues

Module 11: Upgrades and Lifecycle Management

  • Cluster upgrades in OpenShift 4
  • Operator upgrades
  • Backup considerations
  • Migration from OpenShift 3 (high-level)

Module 12: Troubleshooting and Best Practices

  • Diagnosing cluster issues
  • Debugging applications
  • Performance considerations
  • Production best practices

Requirements

Prerequisites

  • Basic understanding of containers and Docker concepts
  • Familiarity with Linux system administration
  • Basic DevOps knowledge is recommended

Target Audience

  • System administrators
  • DevOps engineers
  • Platform engineers
  • Cloud and infrastructure architects
 35 Hours

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