Operations | Monitoring | ITSM | DevOps | Cloud

Famed management thinker Peter Drucker is often quoted as saying, “You can’t manage what you can’t measure.” Tracking and analyzing data of a system provides metrics to measure, predict, and improve the underlining health of the system. Logging data is the simplest act of collecting data for measurement and plays an important role in modern enterprises, as it provides a way to measure the health of hardware devices and software applications alike.

Scenario You are running a large production environment with many Windows servers. There are multiple forests in the network and some forests have multiple domain controllers. Your Windows server security is paramount – you want to track and audit suspicious activities and view detailed Windows reports extracted from the Windows servers event logs.

Organizations that depend on distributed systems often write their applications in Go to take advantage of concurrency features like channels and goroutines (e.g., Heroku, Basecamp, Cockroach Labs, and Datadog). If you are responsible for building or supporting Go applications, a well-considered logging strategy can help you understand user behavior, localize errors, and monitor the performance of your applications.