Monitoring with quantitative time series of a system status enables us to briskly dig out which components in our system failed, but it's still inadequate to diagnose with the root cause under syndromes. As a result, a logging system that gathers, persists, and searches logs is certainly helpful for uncovering the reason why something went wrong by means of correlating events with the anomalies detected.
In general, there are two main components in a logging system: the logging agent and the logging backend. The former is an abstract layer to a program. It gathers, transforms, and dispatches logs to the logging backend. A logging backend warehouses all logs received. As with monitoring, the most challenging part of building a logging system for Kubernetes is ascertaining how to gather logs from containers to a centralized logging backend. Typically, there are...
