The nature of monitoring is developing and changing. What we monitor is no longer only traditional servers and metrics, but so much more. Stateless architectures, logs, events and sensor data today come together to generate thousands of events per minute.

With data sources multiplying by every year the monitoring landscape have quickly become complex. The data volume, variety and speed of ingestion creates a noise impossible to keep up with for human beings. As such monitoring today requires a state of observing.

Observing means analyzing, collecting and keeping track of applications states and their output. Together with traditional monitoring this gives a more holistic picture of the health in complex IT environments. Algorithms and machine learning assists with making sense of the data and detect anomalies based on history.