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What is Monitoring? - Definition & Meaning

Learn what application monitoring is, how tools like Grafana and Datadog work, and why observability is essential for reliable software.

Definition

Monitoring is the continuous collection, analysis, and visualization of metrics, logs, and traces from applications and infrastructure. The goal is to detect issues early and ensure system reliability.

Technical explanation

Observability rests on three pillars: metrics (numerical values over time, such as CPU usage and response time), logs (structured or unstructured textual events), and traces (the path of a request through distributed services). Prometheus is the standard for metrics collection in cloud-native environments, using a pull-based model and PromQL as the query language. Grafana visualizes data from multiple sources in configurable dashboards. Datadog offers an all-in-one SaaS platform for metrics, logs, and APM (Application Performance Monitoring). SLOs (Service Level Objectives) define desired reliability (e.g., 99.9% availability), while SLAs (Service Level Agreements) are contractual obligations. Error budgets indicate how much downtime remains acceptable. Alerting through tools like PagerDuty or Opsgenie sends notifications when thresholds are exceeded. Distributed tracing with Jaeger or OpenTelemetry enables analyzing slow requests across multiple microservices. Synthetic monitoring simulates user interactions to proactively test availability.

How MG Software applies this

MG Software implements monitoring in every production project. We use Vercel Analytics and Sentry for frontend monitoring, and Grafana dashboards for backend metrics. We configure alerting so our team and clients are immediately informed of performance issues. This enables us to intervene proactively before end users experience disruptions.

Practical examples

  • A SaaS platform using Grafana dashboards to monitor real-time API response times, error rates, and active users, with alerts when the 500ms threshold is exceeded.
  • A DevOps team integrating Sentry to automatically detect, group, and assign JavaScript errors in production to the responsible developer.
  • An e-commerce company using synthetic monitoring to simulate the checkout process every 5 minutes and immediately alert if any step fails.

Related terms

cloud computingkubernetesinfrastructure as codeload balancingci cd

Further reading

Cloud computing explainedKubernetes monitoringCI/CD and monitoring

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Frequently asked questions

Monitoring focuses on watching predefined metrics and triggering alerts on deviations. Observability goes further: the ability to understand the internal state of a system based on external output (metrics, logs, traces). With good observability, you can diagnose unknown problems, not just known failure scenarios.
For startups and small teams, a combination of Sentry (error tracking), Vercel Analytics (web performance), and UptimeRobot (availability) is sufficient. Growing companies benefit from Grafana + Prometheus (self-hosted) or Datadog (managed). The choice depends on budget, team size, and infrastructure complexity.
SLOs (Service Level Objectives) are internal targets for your service reliability, such as "99.9% availability" or "95% of API calls within 200ms." They guide engineering decisions and help prioritize: when the error budget is nearly exhausted, you focus on reliability instead of new features.

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