SRE at Scale

Who this course is for

This course is for backend and infrastructure engineers who are moving into — or already doing — reliability work, and who want to run it as a discipline rather than a set of habits picked up during past outages. It's aimed at people who already operate production services and want to formalize how they reason about reliability: turning intuition about "is this service healthy" into SLOs a whole org can align around. Prior on-call experience helps ground the material but isn't required.

What you'll actually build

The course works through five problems in the order an SRE program actually gets built: defining SLOs, SLIs, and error budgets for real services, the foundation everything else depends on, since without a shared definition of "reliable enough" every reliability conversation turns into opinion; running chaos engineering and failure injection experiments safely, so you find weaknesses on your own schedule instead of during a real incident; designing incident response processes and on-call rotations that hold up under actual pressure; capacity planning at scale, so growth doesn't quietly turn into an outage; and facilitating blameless postmortems that produce real reliability improvements instead of a document nobody reads again. Every module pairs a concepts lesson with a hands-on build.

The capstone

You finish by designing a full SRE program for a live service — SLOs and error budgets, an on-call and incident response process, a chaos engineering plan, and a postmortem process, all tied together into a program you could actually hand to a team and start running. This is the artifact that goes in your portfolio, since it's the kind of end-to-end reliability design that SRE and staff-level infrastructure interviews are built around.

Why this matters right now

As systems get more distributed, the cost of an unreliable service compounds fast — the SRE discipline exists precisely because "keep it running" stops being a matter of individual engineer effort past a certain scale and needs shared definitions, tooling, and process. Engineers who can define error budgets that actually drive tradeoff decisions, run chaos experiments without causing the incident they're trying to prevent, and run a postmortem process that changes behavior rather than assigning blame, are the ones organizations lean on as reliability ownership grows past a single team.