GL280 · 4 days · 7+ hrs hands-on labs

Openshift Administration

Available for RHEL

Build production-ready OpenShift administration skills across the full cluster operations stack. Students progress from architecture review and cluster installation through authentication, security hardening, application lifecycle management, advanced scheduling, autoscaling, and production observability, gaining the expertise to operate OpenShift Container Platform clusters at scale.

Key topics include OpenShift 4.x installation on AWS with IPI and UPI methods, identity provider configuration with htpasswd and OAuth, Role-Based Access Control, Security Context Constraints, admission controllers with Gatekeeper policy enforcement, Deployments with rolling updates and rollbacks, ResourceQuotas and LimitRanges, node and pod affinity rules, taints and tolerations, Horizontal Pod Autoscalers with custom Prometheus metrics, MachineSet and ClusterAutoscaler management, EFK logging with Elasticsearch and Fluentd, audit log forwarding, and Prometheus-based monitoring with ServiceMonitors and Grafana dashboards.

With 17 lab exercises spanning every chapter, students work directly on live OpenShift clusters to configure identity providers, enforce RBAC policies, tune pod scheduling, set up autoscaling, deploy the logging stack, and build monitoring dashboards, developing the hands-on skills that day-2 cluster operations demand.

Who Should Attend

System administrators, DevOps engineers, site reliability engineers, and platform engineers responsible for deploying, operating, and maintaining Red Hat OpenShift Container Platform clusters who need production-ready skills in cluster security, workload scheduling, autoscaling, and observability.

Skills You'll Gain

Describe OpenShift and Kubernetes cluster architecture including control plane components, RHCOS nodes, and Operator-managed infrastructure
Configure cluster authentication using htpasswd identity providers, OAuth, kubeconfig files, and service accounts
Implement Role-Based Access Control with Roles, ClusterRoles, RoleBindings, and ClusterRoleBindings
Manage Security Context Constraints and admission controllers to enforce pod security policies
Deploy and manage applications using Deployments, ReplicaSets, rolling updates, and Pod Disruption Budgets
Configure pod health checks using startup, liveness, and readiness probes
Control pod scheduling with resource requests, limits, node and pod affinity rules, taints, and tolerations
Plan cluster capacity including control plane sizing, network CIDR allocation, and etcd performance tuning
Scale clusters using Horizontal Pod Autoscalers, MachineSets, MachineHealthChecks, and ClusterAutoscalers
Enforce organizational standards using labels, annotations, and Gatekeeper policy-based admission control
Deploy and operate the EFK logging stack with Elasticsearch, Fluentd, Kibana, and ClusterLogForwarder audit log management
Monitor cluster health using Prometheus, Grafana, Thanos Querier, ServiceMonitors, and custom application metrics

Chapters & Labs

15 labs · 7+ hours hands-on
  1. Core Concept Review 1 lab · 30 min
  2. Installation and Authentication 4 labs · 110 min
  3. Security
  4. Application Lifecycle Management 3 labs · 80 min
  5. Scheduling 4 labs · 100 min
  6. Scaling 1 lab · 30 min
  7. Logging, Monitoring, Alerting 2 labs · 60 min

Prerequisites

Solid knowledge of Kubernetes concepts including Pods, Deployments, Services, and namespaces. GL275 (Kubernetes Administration) or equivalent hands-on Kubernetes experience strongly recommended. GL120 (Linux Fundamentals) or equivalent Linux command-line proficiency required. Familiarity with container images, registries, and YAML object manifests is expected.