Module 4 of 5
Reliability in production
How to state reliability as a number, see what a running system is doing, change it without breaking it, and get the data back when something destroys it.
The earlier modules designed systems that keep their promises under overlap, failure, and load. This module is about keeping those promises after launch, when the system changes every day, the traffic is real, and the people operating it need to know whether to wake up. It starts by turning “reliable” into a measured objective with a budget, then covers the telemetry that tells you how close you are to it, the release practices that stop most outages before they reach users, and the backups and failover plans that limit the damage when everything else has failed.
By the end of it you should be able to write an SLO and the alerts that defend it, read a latency histogram without being fooled by it, design a rollout that catches a bad change on a few percent of traffic, and state, for a given dataset, how much you would lose and how long you would be down after a deletion, a ransomware attack, or a lost region.
Lessons
- 4.aSLOs and error budgetsHow do you decide how reliable a service must be, and when to wake someone up?21 min
- 4.bObservability signalsWhat should a service emit so you can tell what it is doing, and how do the numbers lie?20 min
- 4.cSafe changeHow do you ship changes every day without each one being a bet on the whole system?21 min
- 4.dBackup and disaster recoveryAfter a deletion, a ransomware attack, or a lost region, how much data do you lose and how long are you down?21 min