Distributed Monitoring: How to understand the Chaos

on YouTube ↗42m

" summary

Concrete recipes and failures: instrument services with OpenTracing → Zipkin/Jaeger, deploy Telegraf sidecar and daemonset on Kubernetes to scrape Prometheus-format metrics, store traces briefly and retain traces seven days then downsample. Shows reactive orchestration against AWS APIs, explains how naive retries saturate AWS rate limits and how tracing reveals which span failed, gives SLO design guidance, and describes a working InfluxData stack (InfluxDB, Chronograf, Kapacitor) used to alert and aggregate across microservices.

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" chapters (4)

1. 0:00Start
2. 5:44A multi threads application is a distributed system
3. 13:19Distributed Tracing Tracing is a way to correlate logs using a set of IDs
4. 41:16Collect data is just the beginning Aggregation, alerting, downsampling are other important steps to answer a question

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