Chapter 8 - AI Reliability, Resilience & Observability

Chapter 8 focuses on engineering AI systems for reliable and resilient operation despite the inherent unpredictability of model behavior. It addresses latency, failures, traffic, and availability through timeouts, retries, circuit breakers, fallbacks, failover, asynchronous processing, streaming, queues, and load management, while establishing deep observability through distributed tracing, AI telemetry, prompt and response monitoring, model performance tracking, and drift detection. It also introduces AI SRE practices, incident management, and AI specific SLOs and SLIs, bringing these capabilities together in the AI Reliability & Observability Reference Architecture.