Monitoring A-Z
summary
Practical runbook of monitoring choices: sets up structured JSON logs to avoid regex parsing, centralizes logs with a queue for bursts, and uses a time-series database with pre-aggregation and retention windows for fast long-range graphs. Describes alerts driven from metrics (example: 90% disk threshold), tracing with parent-child IDs and sampling traces to control volume, and instrumentation tradeoffs (counters on hot paths, logs for failures). Emphasizes costs and operational complexity of DBs, queues and tracing.
AI-written summary · about
chapters (9)
- 0:00Start
- 10:12Log Aggregation
- 13:11Log Parsing
- 16:41Structured Logging
- 21:20Logs - Databases
- 24:34Logs - Queuing
- 36:44Metrics - Collection
- 39:36Metrics - Databases
- 55:27Summary
related talks
01h 15mMonitoring: Turning Noise into Signal
55mBeginner's guide to observability
38mLogging, Instrumentation, Dashboards, Alerts
41mMetrics Applied
52mHolistic Monitoring
42mDistributed Monitoring: How to understand the Chaos- 42mDistributed Monitoring: How to understand the Chaos
38mPractical Guide to Application Observability in 10 Steps