Metrics driven development with dedicated Observability Team
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Do Xuan Huy (LINE Corporation) LINE Vietnam Opening Day, March 31st 2018
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Metrics driven development with dedicated Observability Team
- 1. Metrics driven development, a observability perspective Huy Do LINE corp
- 2. Introduction • Huy Do • Software Engineer at Observability Team • Founded kipalog.com & Ruby Vietnam group
- 3. Agenda • Metrics driven culture at LINE • Introduce our observability stack
- 4. LINE • A lot of end users (~170M active) • A lot of traffics • A lot of services (delivery, taxi, games, manga…)
- 5. What we care • User Experience • One important prospect of User Experience is Reliability
- 6. RELIABILITY • No Downtime • Low MTTR (Mean Time To Repair) • Fast Response • Fair response time • Fair percentile latency : p99, p95, p50
- 7. HOW
- 8. CULTURE
- 9. • EVERY Engineers MUST care about their application statuses • EVERY Engineers MUST do on-call rotate • NO "application engineer" who write code only • We have a dedicate team to provide them stable tools to care about their application status at best CULTURE
- 11. OBSERVABILITY
- 12. – Wikipedia “observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs”
- 14. METRICS
- 15. • Metrics • Most simplest form is a triple • (name, value, timestamp) • Could be represent as graph METRICS
- 16. • System Metrics • CPU/Disk IO/Network/DiskUsage... • MUST: have alert for critical metrics by default (users don't know what to monitor, and don't know the good threshold) • Application Metrics • Internal queue size, endpoint latency tail (p50, p95, p99), request size, request count METRICS
- 17. • In LINE we care A LOT about Application Metrics • We try to instrument every single new added logic • Some of our heavy servers exported over 10000 metrics per server METRICS
- 18. LOGGING
- 19. Warn / Error / Fatal log for alerting
- 20. • In LINE All error / warning logs MUST be • Permanent stored (for trouble shooting later) • Used for alerting • Easy to query (you should not go to each host, and do grep access log) LOGGING
- 21. LOGGING Real time error/warn log analysis with help of Elasticsearch / Kibana
- 22. LOGGING Daily report for error trend
- 23. TRACING
- 24. • Not a common concept in normal service • Very helpful in microservice or fully async system , when a response could come from multiple services or multiple async threads. TRACING
- 27. • We call it IMON • IMON could • Aggregate metrics from dozen of thousands of hosts, and do alert • Aggregate warn/error logs from application and do alert • (on going) Tracing requests across services
- 28. HOW BIG?
- 29. • ~ 20 millions metrics per minute • And keep growing every day • ~ 500k log received per minute (peak time could up to few millions)
- 30. ARCHITECTURE
- 32. DETAILS
- 33. •Shard-ing MySQL cluster (~50 servers) •Partition by “customers” •Batching write for better throughput METRICS DATABASE
- 34. • MySQL is not fit for time series database • "Good TSDB"? • Compression • Optimize for write, but read MUST fast enough • Flexible query (topK, rate, delta) • Fast aggregate • We're moving to OpenTSDB METRICS DATABASE
- 35. • ElasticSearch to store warn/error log • ElasticSearch is very good at writing (with support of batching write from application layer) • However, some bad read query will kill the server LOGGING DATABASE
- 36. • Wrote our own in golang • Similar architect with telegraf (but with buffer) • Fully managed • Monitor all agents CPU / memory usage.. • Monitor all agents error • Automatically roll-out TELEMETRY AGENT
- 37. • Flexbile routing rules • Dedicated collector for big customer • Drop request by dynamic configuration • Written by armeria and centraldogma ROUTING GATEWAY https://github.com/line/armeria https://github.com/line/centraldogma
- 38. • Faster, more stable TSDB • Wire everything together • For every alert, see the big image with metrics/ log/tracing in same place • Autonomous alerting • With help of Machine Learning FUTURE
- 39. FINALLY • How you monitor reflect your engineering culture • Data driven culture • Stability driven culture • Monitoring IS NOT for devops engineer or sysadmin only, but for EVERY ENGINEERS
- 40. Thank you for listening