This is another very crucial aspect necessary for ensuring system reliability, performance, and quick incident response. I will be stating the approaches to achieve this.
1. METRICS to MONITOR
🔀 Infrastructure-Level Metrics
CPU Usage: for detecting high loads.
Memory Usage: to Prevent out-of-memory issues.
Disk Usage & IOPS: helps avoid storage bottlenecks.
Network Traffic: identifies unusual spikes or drops.
🔀 Application-Level Metrics:
Request Latency = focuses on measuring response times.
Error Rates = tracks HTTP 5xx and 4xx errors.
Request Rate (Throughput) = ensures expected traffic levels.
Database Queries & Cache Performance: effective in detecting slow queries or cache misses.
Dependency Health: Monitors third-party API failures.
🔀 Business-Level Metrics
User Signups/Purchases: Ensures core business functions are operational.
Transaction Failures: Detects payment or order failures.
2. LOGGING & TRACING TOOLS
Structured Logging: Logs in JSON format for better analysis.
Centralized Log Storage: Tools like ELK Stack (Elasticsearch, Logstash, Kibana), Fluentd, or Datadog.
Distributed Tracing: Tools like Jaeger, Zipkin, or OpenTelemetry help trace request flows across microservices.
3. ALERTING STRATEGIES
Threshold-Based Alerts: set limits for CPU, memory, or error rates.
Anomaly Detection: provides AI-driven detection of unusual patterns (e.g., AWS CloudWatch, Prometheus Alertmanager).
Rate of Change Alerts: notifies for when metrics change drastically in a short time.
> Multi-Level Alerts; includes:
Critical Alerts: where immediate actions are required (e.g., service down).
Warning Alerts: for potential issues (e.g., high memory usage).
Informational Alerts: regarding system updates.
4. TOOLS for MONITORING & ALERTING
🔀 Open-Source Solutions; like:
Prometheus & Grafana (metrics collection & visualization).
Zabbix (infrastructure monitoring).
Nagios (server health monitoring).
Loki (log aggregation).
🔀 Cloud-Native Solutions; e.g:
AWS CloudWatch: which provides logs, metrics, alerts.
Azure Monitor: used with Azure services.
Google Cloud Operations (Stackdriver): used in monitoring for GCP.
🔀 Third-Party Services
Datadog: for full-stack monitoring.
New Relic: for application performance monitoring (APM).
PagerDuty: for incident management & alerting.
Opsgenie: for on-call scheduling & notifications.
5. INCIDENT RESPONSE & AUTOMATION, like;
On-Call Rotation: PagerDuty, Opsgenie, or VictorOps.
Automated Remediation: runbooks & self-healing mechanisms.
ChatOps: integrate alerts with Slack or Microsoft Teams.
6. BEST PRACTICES
Set Meaningful Alerts: to avoid alert fatigue.
Use Dashboards: for real-time visualization of quick insights.
Test Alerts Regularly: ensures notifications work.
Correlate Logs & Metrics: helps in faster root cause analysis.
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