A comprehensive guide to production log monitoring covering the full pipeline from collection to alerting. Explains the differences between log monitoring, log management, and log analytics, then walks through each pipeline stage: collection via DaemonSets and OTel Collector, aggregation and parsing, tiered storage (hot/warm/cold), real-time correlation using trace IDs, and symptom-based alerting. Covers common failure modes like ingest explosion from short-lived pods, inconsistent log formats, alert fatigue, and the retention/indexing cost trap. Recommends practices such as emitting structured JSON with OTel fields, tiering storage by access pattern, alerting on behavioral baselines rather than raw strings, and correlating logs with metrics and traces during incidents. Concludes with tool selection criteria and a walkthrough of Coralogix's in-stream processing approach.
Table of contents
What Is Log Monitoring?Why Log Monitoring Pays Off in ProductionHow a Production Log Monitoring Pipeline WorksWhere Log Monitoring Breaks in ProductionPractices That Keep Your Log Monitoring ReliableWhat to Look for in a Log Monitoring ToolHow Coralogix Approaches Log MonitoringFrequently Asked Questions About Log MonitoringSort: