What is Monitoring?
Turkish: Monitoring
Monitoring tracks application and infrastructure metrics, logs, and alerts to detect problems before users or SLAs are affected.
What is Monitoring?
Monitoring is the practice of continuously measuring the health and behavior of running systems. The goal is not only to be notified after an outage, but to catch signals before capacity runs out, latency rises, or user experience degrades.
What Gets Monitored?
A typical monitoring setup tracks CPU, memory, disk, network, error rate, response time, request volume, queue depth, and database query duration. These metrics appear in dashboards and generate alerts based on thresholds or anomaly rules. Logging provides detailed event records that help explain why an alert fired.
What Makes Monitoring Useful?
Not every metric should become an alert. Too many alerts create fatigue and make real incidents easier to miss. Good monitoring focuses on indicators close to user impact: error rate, p95 response time, failed payments, or processed order count. Every alert should have an owner, a response step, and an acceptable response window.
SLA targets are a natural input for monitoring because they define the service level the system must protect.
Related Terms
Anomaly detection automatically flags transactions, metrics, or events that fall outside the normal range learned from past behavior.
Application Performance Monitoring (APM)APM tracks application latency, errors, transactions, and resource use so teams can diagnose performance issues in production.
KibanaKibana is the visual component of the ELK Stack for visualizing and analyzing log and metric data stored in Elasticsearch.
Load TestingLoad testing is a performance test type that measures system stability and performance under high user traffic.
LoggingLogging is the practice of recording runtime events from applications and systems — critical for debugging and monitoring.
ObservabilityObservability is the ability to understand a system's internal state from its external outputs (logs, metrics, traces) — a key DevOps principle.
OpenTelemetryOpenTelemetry is an open-source framework for collecting logs, metrics, and traces in a standard format for application observability.
SentrySentry groups application errors with stack traces, releases, environments, and user impact so teams can monitor production issues.
SLA (Service Level Agreement)An SLA defines uptime, response time, resolution targets, measurement methods, and remedies between a provider and a customer.
Time-Series DatabaseA time-series database optimizes storage, compression, and time-based queries for timestamped metrics, logs, and sensor data.