Reliability Engineering

Foundation Track | 4 Modules | ~2 hours total

The engineering discipline of building systems that work when users need them. Theory and principles that apply regardless of your tech stack.

Why Reliability Engineering?

Users don’t care about your architecture. They care about one thing: does it work?

Reliability engineering teaches you to:

Define what “reliable” means for your context
Measure reliability objectively
Design for failure before it happens
Improve continuously through data-driven decisions

This isn’t about hoping things don’t break. It’s about engineering systems that survive when they do.

Modules

#	Module	Time	Description
2.1	What is Reliability?	25-30 min	Definitions, nines, MTBF/MTTR, error budgets
2.2	Failure Modes and Effects	30-35 min	FMEA, graceful degradation, blast radius
2.3	Redundancy and Fault Tolerance	30-35 min	HA vs FT, active-active, redundancy patterns
2.4	Measuring and Improving Reliability	35-40 min	SLIs, SLOs, error budgets, continuous improvement
2.5	SLOs, SLIs, and Error Budgets	20-30 min	Deep dive into the SRE mental model for reliability targets

Learning Path

START HERE
    │
    ▼
┌─────────────────────────────────────┐
│  Module 2.1                         │
│  What is Reliability?               │
│  └── Definitions and metrics        │
│  └── The nines                      │
│  └── MTBF, MTTR, error budgets      │
└──────────────────┬──────────────────┘
                   │
                   ▼
┌─────────────────────────────────────┐
│  Module 2.2                         │
│  Failure Modes and Effects          │
│  └── Failure taxonomy               │
│  └── FMEA technique                 │
│  └── Graceful degradation           │
│  └── Blast radius                   │
└──────────────────┬──────────────────┘
                   │
                   ▼
┌─────────────────────────────────────┐
│  Module 2.3                         │
│  Redundancy and Fault Tolerance     │
│  └── HA vs FT                       │
│  └── Active-passive vs active-active│
│  └── Redundancy patterns            │
│  └── The costs of redundancy        │
└──────────────────┬──────────────────┘
                   │
                   ▼
┌─────────────────────────────────────┐
│  Module 2.4                         │
│  Measuring and Improving            │
│  └── SLIs, SLOs, SLAs               │
│  └── Error budgets in practice      │
│  └── Postmortems                    │
│  └── Continuous improvement         │
└──────────────────┬──────────────────┘
                   │
                   ▼
              COMPLETE
                   │
    ┌──────────────┼──────────────┐
    │              │              │
    ▼              ▼              ▼
Observability   Security        SRE
   Theory      Principles    Discipline

Key Concepts You’ll Learn

Concept	Module	What It Means
The Nines	2.1	99.9% vs 99.99% = 10x difference in allowed downtime
MTBF/MTTR	2.1	Mean time between failures / to recovery
Error Budget	2.1, 2.4	Acceptable unreliability as a resource to spend
FMEA	2.2	Systematic technique for predicting failures
Graceful Degradation	2.2	Partial functionality better than total failure
Blast Radius	2.2	Scope of impact when something fails
Bulkhead Pattern	2.2, 2.3	Isolation to prevent cascading failures
High Availability	2.3	System stays operational with minimal downtime
Fault Tolerance	2.3	System continues without any interruption
SLI/SLO/SLA	2.4	Indicator/Objective/Agreement framework

Prerequisites

Recommended: Systems Thinking Track
Helpful: Some experience operating production systems
Helpful: Understanding of distributed systems basics

Where This Leads

After completing Reliability Engineering, you’re ready for:

Track	Why
Observability Theory	Can’t improve reliability without seeing what’s happening
SRE Discipline	Putting reliability engineering into operational practice
Security Principles	Security and reliability share patterns
Distributed Systems	Deep dive into CAP, consensus, and distributed patterns

Key Resources

Books referenced throughout this track:

“Site Reliability Engineering” — Google
“Release It! Second Edition” — Michael Nygard
“Designing Data-Intensive Applications” — Martin Kleppmann
“Implementing Service Level Objectives” — Alex Hidalgo

Papers:

“How Complex Systems Fail” — Richard Cook (free online)

“Reliability is not a feature you add. It’s how you build from the start.”