Monitorimise

Monitorimise is a term used in some technology and operations circles to describe the combined practice of continuous monitoring and real-time optimization of a system or process. It denotes an approach that not only observes performance and health metrics but also actively adjusts configurations, resources, or workflows to improve outcomes.

In practice, monitorimise relies on instrumentation to collect data such as metrics, logs, and traces; real-time analytics or machine learning to detect deviations; and automation to enact corrective or performance-enhancing actions. It may include auto-scaling, adaptive rate limiting, dynamic resource allocation, and software tuning, all guided by feedback loops and governance policies.

Common applications are cloud-based services, data centers, software development pipelines, and industrial internet of things systems, where maintaining reliability while controlling cost is essential. Proponents argue that monitorimise can reduce mean time to recovery, increase availability, and optimize throughput, while critics warn of over-automation, increased complexity, and potential blind spots if data quality or model drift is not managed.

Etymology and status: monitorimise appears as a neologism used mainly in blogs and conference talks rather than as a formal term in dictionaries. It blends monitor with the sense of minimising or optimising, signaling the dual aim of observation and improvement. It is related to concepts such as observability, AIOps, and autonomous operations.

See also: observability, AIOps, auto-scaling, dynamic optimization.