applicatiemonitoring

Applicatiemonitoring is the practice of observing and measuring the behavior of software applications in production environments to ensure reliability, performance, and user satisfaction. It relies on instrumentation, telemetry, and analytics to detect anomalies, assess health, and guide improvements.

Core data types are metrics, logs, and traces, often supported by events and synthetic checks. Metrics provide numeric indicators such as latency, error rate, and throughput. Logs capture discrete events and messages. Traces reveal end-to-end request paths, enabling root-cause analysis and dependency mapping.

Key practices include instrumenting code and systems (manually or automatically), collecting data in a centralized observability platform, and maintaining dashboards and alerts. Real-user monitoring captures actual user experiences, while synthetic monitoring tests endpoints to forecast performance under controlled conditions. These data streams are typically mapped to service level objectives (SLOs) and indicators (SLIs) to align technical health with business goals.

Operational benefits include faster incident response, improved reliability, and data-driven capacity planning. Governance concerns encompass data quality, privacy, and telemetry overhead. Effective applicatiemonitoring requires integration with development and release processes and scalability for cloud-native architectures and microservices, often involving automated alerting, runbooks, and postmortems.

Relation to related concepts: applicatiemonitoring is closely tied to application performance management (APM). While APM may offer deeper analytics and code-level insights, applicatiemonitoring focuses on continuous observation and alerting to sustain service health and user satisfaction. When implemented well, it reduces mean time to detect and repair and supports ongoing optimization.