SRE 101: Complete Guide

Site Reliability Engineering (SRE) is what happens when you treat operations as a software problem. This comprehensive series shares my journey implementing SRE practices in Go-based microservices, from managing a single API to orchestrating multiple production systems.

What You'll Learn

Through this series, I'll share practical lessons from implementing SRE principles in my personal projects and production environments. Each article builds on real experiences, mistakes I've made, and solutions that actually worked. All examples use Go applications because that's what I use day-to-day for building reliable systems.

Series Overview

How I discovered SRE after a production outage, what SRE really means, and why treating operations as a software problem changed everything for my projects.

Key Topics:

  • The midnight incident that introduced me to SRE

  • Core SRE principles from Google's practices

  • How SRE differs from traditional DevOps

  • Setting up your first Go service with SRE in mind

Moving from vague "99.9% uptime" promises to meaningful reliability targets. How I defined and measured what "reliable" actually means for my Go APIs.

Key Topics:

  • Choosing the right Service Level Indicators (SLIs)

  • Setting realistic Service Level Objectives (SLOs)

  • Understanding Service Level Agreements (SLAs)

  • Implementing SLI measurement in Go applications

  • Error budgets and how they guide engineering decisions

The difference between monitoring (knowing when things break) and observability (understanding why). Building comprehensive visibility into Go microservices.

Key Topics:

  • The four golden signals: latency, traffic, errors, saturation

  • Instrumenting Go applications with Prometheus

  • Structured logging with zerolog

  • Distributed tracing with OpenTelemetry

  • Building dashboards that actually help during incidents

What I learned from managing my first major incident at 2 AM, and how to build a repeatable incident response process that keeps you calm under pressure.

Key Topics:

  • Incident severity levels and when to declare an incident

  • On-call rotation setup for small teams

  • Incident response workflow that I use

  • Post-mortem culture: learning without blame

  • Runbooks and playbooks in Go projects

How I learned to plan for growth after my API fell over during a traffic spike. Predicting and managing capacity in Go services.

Key Topics:

  • Load testing Go applications with k6

  • Understanding resource utilization patterns

  • Horizontal vs vertical scaling for Go services

  • Performance profiling with pprof

  • Cost-effective capacity planning

Identifying and eliminating repetitive manual work that was eating up my time. Building automation that actually reduces toil instead of creating more complexity.

Key Topics:

  • What counts as toil (and what doesn't)

  • Measuring and tracking toil in your workflow

  • Automating deployments with CI/CD

  • Self-healing systems in Go

  • When NOT to automate

From writing code that "just works" to building applications designed for reliability from the ground up. How programming practices directly impact system reliability.

Key Topics:

  • Designing Go services for failure

  • Resilient API patterns and error handling

  • Building observable applications from the start

  • Database design for SRE (idempotency, soft deletes, optimistic locking)

  • Testing strategies that prevent production incidents

  • Self-documenting code for operations

Who This Series Is For

This series is for developers and operations engineers who want to:

  • Build more reliable systems using SRE principles

  • Move from reactive firefighting to proactive system design

  • Learn practical SRE techniques with real Go code examples

  • Understand how to balance reliability with feature velocity

  • Apply Google's SRE practices to smaller-scale projects

Prerequisites

To get the most out of this series, you should have:

  • Basic understanding of Go programming

  • Experience deploying applications to production

  • Familiarity with APIs and web services

  • Basic knowledge of Linux/Unix systems

My SRE Journey

I started as a developer who treated operations as "someone else's problem." After experiencing multiple production outages and spending too many weekends debugging instead of building, I discovered SRE. The journey from reactive ops to reliability engineering transformed not just how I build systems, but how I think about software.

These articles share what I wish someone had told me when I started. They're based on real projects, actual incidents, and lessons learned the hard way - so you don't have to.

Let's build reliable systems together.

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