Cloud-Native O11y: Building Scalable Enterprise Systems
summary
Claims a 40% faster incident resolution and 25% resource efficiency during peak traffic, with 200 ms anomaly detection and 58% faster incident detection; reports a 35% database load reduction and 50% downtime reduction. Implementation uses Prometheus and ELK for metrics and logs, Dynatrace and GCP Stackdriver for production tracing, and scalable ingestion via Kafka or GCP Pub/Sub with Jäger-style distributed traces. Roadmap shows start-one-service, add tracing, then AI anomaly detection and automated remediation.
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chapters (12)
- 0:00Introduction and Overview
- 0:45From Monitoring to Observability
- 2:32Real-World Implementation Metrics
- 3:37The Pillars of Observability
- 5:03Stateless vs Stateful Services
- 7:02Distributed Tracing Implementation
- 8:08API Gateway Observability
- 11:20Designing an Observability Pipeline
- 12:38High Availability Strategies
- 14:43Capacity Planning and Optimization
- 15:53Implementation Roadmap
- 16:47Conclusion
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