Red Hat OpenShift Administration III: Scaling Kubernetes Deployments in the Enterprise (DO380) — Lesson 1: Enterprise Cluster Architecture, Fleet Planning, Scaling, and Capacity

Learning Objectives

• Explain the structures, services, data, settings, roles, and dependencies governing fleet architecture and capacity planning.
• Implement and validate cluster sizing, workload placement, and scaling strategy using reviewable evidence.
• Evaluate the condition where the observed result differs from the approved configuration because a prerequisite, permission, dependency, or sequence was missed and select a proportionate corrective response.

Detailed Topics

• fleet architecture applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.
• capacity planning applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.
• cluster sizing applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.
• workload placement applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.
• scaling strategy applied to the course scenario, expected platform behavior, dependencies, controls, and evidence.

Instructor Demonstration

The instructor traces an enterprise platform team scaling standardized OpenShift services across multiple clusters and business units. The walkthrough connects navigation, commands, configuration logic, system messages, and evidence captured in the enterprise OpenShift scaling blueprint, GitOps repository design, policy evidence, and resilience improvement plan. It also tests the exception where the observed result differs from the approved configuration because a prerequisite, permission, dependency, or sequence was missed.

Hands-On Exercise

Complete a controlled Red Hat exercise covering Enterprise Cluster Architecture, Fleet Planning, Scaling, and Capacity and preserve the verified result in the enterprise OpenShift scaling blueprint, GitOps repository design, policy evidence, and resilience improvement plan.

1. Confirm scope, prerequisites, versions, identities, dependencies, and acceptance criteria.
2. Execute the workflow while recording commands, settings, outputs, events, and system messages.
3. Test normal behavior, one boundary condition, and the stated exception.
4. Document corrections, evidence, ownership, retest criteria, rollback, and handover actions.

Scenario Analysis

• Identify which object, service, policy, setting, or sequence most strongly influences fleet architecture.
• Compare two defensible responses and explain technical, security, operational, and support trade-offs.
• Determine how the enterprise OpenShift scaling blueprint, GitOps repository design, policy evidence, and resilience improvement plan should be approved, retained, retested, and updated.

Troubleshooting Guidance

Start where expected behavior first differs from the observed result. Check prerequisites, identity, configuration order, version compatibility, connectivity, status, resource limits, and evidence separately. Treat “the observed result differs from the approved configuration because a prerequisite, permission, dependency, or sequence was missed” as a hypothesis until commands, logs, settings, and retest outcomes confirm the cause.

Validation Checklist

• Required platform components, identities, permissions, settings, and dependencies are present.
• The enterprise OpenShift scaling blueprint, GitOps repository design, policy evidence, and resilience improvement plan connects each conclusion to objective, reviewable evidence.
• Normal processing, a boundary condition, dependency behavior, and the stated exception were tested.
• Corrections, ownership, retest criteria, rollback, documentation, and operational handover are complete.

Lesson Outcome

Learners can apply Enterprise Cluster Architecture, Fleet Planning, Scaling, and Capacity, explain the resulting platform behavior, and defend the outcome through the enterprise OpenShift scaling blueprint, GitOps repository design, policy evidence, and resilience improvement plan.