85 observability cost engineering
In this section
- Build Your Observability SkillCreate your observability and cost engineering skill in one prompt, then learn to improve it throughout the chapter
- JIT Chapter 85: Observability & Cost EngineeringMaster the three pillars of observability (metrics, tracing, logging), SRE foundations, and FinOps practices for cloud-native AI applications
- Three Pillars of ObservabilityUnderstand metrics, traces, and logs as complementary signals for debugging AI applications at scale
- Metrics with PrometheusDeploy Prometheus in Kubernetes, write PromQL queries for the 4 golden signals, and instrument your Task API with custom metrics using prometheus_client
- Visualization with GrafanaBuild production-ready Grafana dashboards that transform raw Prometheus metrics into actionable insights using the 4 golden signals, dashboard variables, and JSON models
- Distributed Tracing with OpenTelemetry & JaegerLearn to instrument FastAPI applications with OpenTelemetry, create custom spans for business operations, deploy Jaeger for trace visualization, and implement sampling strategies for production
- Centralized Logging with LokiImplement log aggregation with Grafana Loki and Promtail, write LogQL queries, configure structured logging in Python, and correlate logs with traces for distributed debugging
- SRE Foundations: SLIs, SLOs, and Error BudgetsMaster the reliability dial through Service Level Indicators, Objectives, and Error Budgets for production AI applications
- Alerting and Incident ResponseImplement multi-window, multi-burn-rate alerting based on SLOs, configure Alertmanager routing, and establish incident response runbooks for production AI services
- Cost Engineering and FinOpsImplement FinOps practices to gain visibility into Kubernetes costs, identify waste, right-size resources with VPA, and schedule non-production for 75% savings
- Dapr Observability IntegrationConfigure Dapr-native observability with metrics, tracing, and logging for sidecars, actors, and workflows in your Kubernetes observability stack
- Capstone: Full Observability Stack for Task APIDeploy complete observability with metrics, traces, logs, SLOs, alerts, and cost monitoring for production AI applications