Red Hat Performance Tuning: Linux in Physical, Virtual, and Cloud (RH442) — Lesson 2: CPU, Memory, NUMA, Scheduling, Kernel, and Process Tuning

Learning Objectives

• Configure the principal services, objects, workflows, and controls for CPU scheduling, memory management, and NUMA.
• Apply kernel parameters and process tuning while preserving reviewable technical evidence.
• Recognize and correct the condition where a valid change produces the wrong outcome because variables, permissions, mapping, or sequencing are incorrect.

Detailed Topics

• CPU scheduling: apply the concept to the course scenario, identify dependencies and controls, and record objective evidence of the result.
• memory management: apply the concept to the course scenario, identify dependencies and controls, and record objective evidence of the result.
• NUMA: apply the concept to the course scenario, identify dependencies and controls, and record objective evidence of the result.
• kernel parameters: apply the concept to the course scenario, identify dependencies and controls, and record objective evidence of the result.
• process tuning: apply the concept to the course scenario, identify dependencies and controls, and record objective evidence of the result.

Instructor Demonstration

The instructor demonstrates cpu, memory, numa, scheduling, kernel, and process tuning by tracing architecture, commands, configuration, system messages, and evidence. The walkthrough tests how a valid change produces the wrong outcome because variables, permissions, mapping, or sequencing are incorrect and explains how to isolate the cause without masking related issues.

Hands-On Exercise

Implement the core workflow for CPU, Memory, NUMA, Scheduling, Kernel, and Process Tuning and add the verified result to the performance baseline, benchmark evidence, tuning plan, validation results, and capacity recommendations.

1. Confirm scope, versions, access, dependencies, assumptions, and acceptance criteria.
2. Perform the workflow while recording commands, configuration, output, events, and decisions.
3. Test the normal path and one course-specific exception or boundary condition.
4. Retest the correction and document rollback, ownership, and follow-up actions.

Scenario Analysis

• Identify which dependency most strongly influences CPU scheduling in the stated scenario.
• Compare two approaches for kernel parameters and explain the security, reliability, performance, and support trade-offs.
• Decide what evidence must be retained in the performance baseline, benchmark evidence, tuning plan, validation results, and capacity recommendations before operational acceptance.

Troubleshooting Guidance

Begin with the first observable difference from the expected result. Check configuration, permissions, sequence, connectivity, and functional behavior separately, then correlate logs, events, commands, metrics, and configuration history. Treat the assumption that a valid change produces the wrong outcome because variables, permissions, mapping, or sequencing are incorrect as a hypothesis until a reproducible retest confirms the cause.

Validation Checklist

• The required configuration, permissions, sequence, connectivity, and functional behavior were checked and recorded.
• The normal path and a course-specific exception were tested.
• The performance baseline, benchmark evidence, tuning plan, validation results, and capacity recommendations links conclusions to commands, configuration, logs, metrics, or other objective evidence.
• Corrective actions, rollback, ownership, and handover notes are complete.

Lesson Outcome

Learners can apply CPU, Memory, NUMA, Scheduling, Kernel, and Process Tuning, explain the observed platform behavior, and support the result with a reviewable performance baseline, benchmark evidence, tuning plan, validation results, and capacity recommendations.