Overview
In this unit, we focus on incident management, root cause analysis, and troubleshooting frameworks. These are foundational skills for Linux administrators who are responsible for maintaining system reliability and responding effectively to issues.
You’ll explore structured approaches like the Scientific Method, 5 Whys, FMEA, and PDCA, as well as methodologies like Six Sigma, TQM, and systems thinking. We’ll also look at tools for visual problem solving, including the Fishbone Diagram and Fault Tree Analysis, and discuss how data types play a role in investigations.
Learning Objectives
By the end of this unit, you will be able to:
- Apply the Scientific Method to real-world troubleshooting scenarios
- Understand and use structured methods like FMEA, 5 Whys, and PDCA
- Differentiate between continuous and discrete data in diagnostics
- Use visual tools like Fishbone Diagrams and Fault Tree Analysis to trace causes
- Explain the OSI model as it applies to layered troubleshooting
- Leverage concepts from Six Sigma and 5S methodology to organize your workflows
- Document and communicate incidents effectively with post-mortem writeups
Relevance & Context
Troubleshooting is not guesswork — it’s a discipline. Whether you’re debugging a failed deployment or analyzing a high watermark in system performance, incident management requires both technical skill and structured reasoning.
This unit bridges engineering troubleshooting and administrative troubleshooting, providing multiple models to approach problems methodically. These frameworks are used by professionals across industries to maintain uptime, solve complex problems, and continuously improve system reliability.
Prerequisites
Before starting Unit 15, you should have:
- A working knowledge of Linux system administration
- Familiarity with logs, alerts, and system metrics
- Understanding of basic monitoring and baseline performance concepts
- Comfort using Linux command-line tools and interpreting output
Key Terms and Definitions
Incident
Problem
FMEA
Six Sigma
TQM
Post Mortem
Scientific Method
Iterative
Discrete data
- Ordinal
- Nominal (binary - attribute)
Continuous data
Risk Priority Number (RPN)
5 Whys
Fishbone Diagram (Ishikawa)
Fault Tree Analysis (FTA)
PDCA
SIPOC