Monitoring Guidelines

Apply these monitoring principles to ensure system reliability, performance visibility, and proactive issue detection.

Core Monitoring Principles

• •Monitor the four golden signals: latency, traffic, errors, and saturation
• •Implement monitoring as code for reproducibility
• •Design monitoring around user experience and business impact
• •Use SLOs (Service Level Objectives) to guide alerting decisions
• •Balance comprehensive coverage with actionable insights

Key Metrics to Monitor

Application Metrics

• •Request rate (requests per second)
• •Error rate (percentage of failed requests)
• •Response time (p50, p90, p95, p99 latencies)
• •Active connections and concurrent users
• •Queue depths and processing times

Infrastructure Metrics

• •CPU utilization and load average
• •Memory usage and available memory
• •Disk I/O and available storage
• •Network throughput and error rates
• •Container and pod health (for Kubernetes)

Business Metrics

• •Transaction volumes and values
• •User signups and conversions
• •Feature usage and adoption rates
• •Revenue-impacting events
• •Customer satisfaction indicators

Alerting Strategy

Alert Design Principles

• •Alert on symptoms, not causes
• •Make alerts actionable with clear remediation steps
• •Set appropriate severity levels (critical, warning, info)
• •Avoid alert fatigue through proper threshold tuning
• •Include runbook links in alert notifications

SLO-Based Alerting

• •Define SLOs for critical user journeys
• •Calculate error budgets and burn rates
• •Alert when error budget consumption is high
• •Use multi-window, multi-burn-rate alerts
• •Review and adjust SLOs quarterly

Alert Configuration

• •Set meaningful thresholds based on baseline data
• •Use hysteresis to prevent flapping alerts
• •Implement alert dependencies to reduce noise
• •Route alerts to appropriate teams
• •Configure escalation policies

Dashboard Design

Effective Dashboards

• •Create overview dashboards for service health
• •Build detailed dashboards for debugging
• •Use consistent layouts and naming conventions
• •Include time range selectors and drill-down capabilities
• •Display SLO status prominently

Dashboard Content

• •Show current state and recent trends
• •Include comparison to baseline or previous periods
• •Display deployment markers for correlation
• •Add annotations for significant events
• •Include links to related dashboards and logs

Monitoring Tools Integration

Data Collection

• •Use agents or sidecars for metric collection
• •Implement service discovery for dynamic environments
• •Configure appropriate scrape intervals
• •Use push vs pull based on use case
• •Ensure metric cardinality is manageable

Data Storage and Retention

• •Set retention periods based on use case
• •Implement downsampling for long-term storage
• •Use appropriate storage backends for scale
• •Plan for disaster recovery of monitoring data
• •Monitor your monitoring infrastructure

Health Checks and Probes

• •Implement liveness probes for crash detection
• •Use readiness probes for traffic management
• •Create deep health checks that verify dependencies
• •Expose health endpoints in a standard format
• •Monitor health check latency as a metric

Incident Response

• •Use monitoring data to detect incidents early
• •Correlate metrics, logs, and traces during investigation
• •Document findings and update monitoring post-incident
• •Track MTTR (Mean Time to Recovery) metrics
• •Conduct regular monitoring reviews and improvements

Capacity Planning

• •Track resource utilization trends
• •Set alerts for approaching capacity limits
• •Use forecasting for proactive scaling
• •Document capacity requirements and headroom
• •Review capacity quarterly