The SRE Book Era: Error Budgets Meet Cascading Failure
The SRE Book Era (Jul 2015 – Sep 2016) Google published Site Reliability Engineering in April 2016 and handed the industry a shared vocabulary: SLOs, error budgets, toil, and a whole chapter on postmortem culture. Meanwhile, the period’s biggest incidents were masterclasses in cascading failure — systems that fell over not from the initial fault, but from their own recovery behavior. The incidents that defined the period AWS DynamoDB, September 20, 2015 — The canonical cascading-failure postmortem (aws.amazon.com/message/5467D2). A network disruption caused storage servers to re-request membership metadata simultaneously; the metadata service, already near capacity from a new index feature, couldn’t serve the herd; retries made it worse. DynamoDB’s outage cascaded into EC2, SQS, and CloudWatch in us-east-1. Action items — capacity headroom, longer timeouts, segmented retries — read like a distributed-systems syllabus. Salesforce NA14, May 2016 — A database failure plus a failed failover left a major instance degraded for nearly a day, with some data unrecoverable. It pushed “your SaaS vendor’s DR plan is your DR plan” into procurement conversations. Southwest Airlines (July 2016) and Delta (August 2016) — Back-to-back airline meltdowns from single-point-of-failure infrastructure (a failed router; a datacenter power incident) cancelling thousands of flights. Boards started asking about technical debt. Telstra, 2016 — A string of national mobile outages in Australia, one triggered by a single node being taken offline incorrectly, normalized the telco postmortem press release. What the postmortems reveal 1. Retry storms became a named enemy. The DynamoDB writeup made “metastable failure” patterns mainstream years before the academic term: exponential backoff, jitter, circuit breakers, and load shedding moved from Netflix blog posts into default library behavior (and into everyone’s action items). ...