What is the difference between monitoring and observability?

Monitoring collects predefined metrics and alerts when thresholds are crossed. Observability provides enough data to investigate any question about system behaviour, including unexpected issues. Good observability enables effective monitoring.

How much does monitoring cost?

Free options include Grafana + Prometheus and CloudWatch basic metrics. Commercial platforms start at $15-$25/host/month. For most mid-market businesses, monitoring costs $200-$2,000/month. The ROI from faster incident resolution typically exceeds the cost.

What should I monitor first?

Start with the four golden signals: latency, traffic, errors, and saturation. These provide a comprehensive view of service health. Add application-specific metrics as you mature.

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Monitoring and Observability

Collecting, analysing, and acting on data about system health and performance through metrics, logs, and traces to ensure reliable applications.

In-Depth Explanation

Monitoring and observability are complementary practices for understanding system behaviour. Monitoring tells you when something is wrong; observability helps you understand why.

Three pillars of observability:

Metrics: Numerical measurements over time (CPU, error rate, latency)
Logs: Timestamped records of events and errors
Traces: End-to-end request tracking across distributed services

Monitoring types:

Infrastructure: Server health, CPU, memory, disk, network
Application Performance (APM): Response times, error rates, throughput
Real User Monitoring (RUM): Actual user experience from browsers
Synthetic: Automated tests simulating user interactions
Log monitoring: Alerting on specific log patterns
Uptime: External availability checking

Popular monitoring tools:

Datadog: Comprehensive monitoring platform
New Relic: Application performance monitoring
Grafana + Prometheus: Open-source metrics stack
AWS CloudWatch: Native AWS monitoring
Sentry: Application error tracking
PagerDuty/OpsGenie: Incident alerting

Alerting best practices:

Alert on symptoms (user-facing impact) not causes
Set meaningful thresholds to avoid alert fatigue
Use severity levels (critical, warning, info)
Include runbook links in notifications
Implement escalation policies
Review and tune alerts regularly

Business Context

Effective monitoring reduces mean time to detection and recovery, cutting incident impact by 60-80% and preventing many issues from affecting customers.

How Clever Ops Uses This

Clever Ops implements monitoring and observability for Australian businesses, setting up dashboards, alerts, and automated response workflows for reliable system operations.

Example Use Case

"A SaaS company implements Datadog monitoring with custom dashboards and distributed tracing. Mean time to detection drops from 30 minutes to 2 minutes, and MTTR drops from 2 hours to 15 minutes."