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Monitoring & Alerting Platform

Infrastructure in View, Problems Under Control

The Challenge

The client had a server infrastructure that had grown over time without any monitoring at all. Outages were only noticed when users complained, often hours after the actual problem. There was no overview of system states, no log aggregation and no alerting. Every outage meant time-consuming troubleshooting on individual servers.

The IT department was reactive instead of proactive and spent more time firefighting than on further development.

Our Solution

We cleaned up the infrastructure and built a complete monitoring stack:

Prometheus Metrics Collection

Systematic collection of all relevant system metrics:

  • Node Exporter on all servers for CPU, RAM, disk and network
  • Custom exporters for application-specific metrics
  • Service discovery for automatic detection of new instances
  • Retention policies for efficient long-term storage

Grafana Dashboards

Custom visualizations for different audiences:

  • Operations dashboard: Real-time overview of all systems with traffic-light status
  • Application dashboard: Request rates, latencies, error rates per service
  • Capacity planning: Trend analyses for disk, RAM and CPU usage
  • Business metrics: Order volume, API calls and processing times

Loki Log Aggregation

Centralized log management instead of scattered files:

  • All server logs searchable in one place
  • Correlation of logs with metric anomalies
  • Label-based filtering by service, severity and environment
  • Log-based alerting rules for critical error patterns

Alloy Collection Agent

Grafana Alloy as a unified agent on all servers:

  • Metrics collection and forwarding to Prometheus
  • Log shipping to Loki
  • Centrally managed configuration via Git
  • Automatic deployment via Ansible

Alerting with Escalation Chains

Smart alerting instead of alert fatigue:

  • Multi-level escalation: email → Slack → Teams → phone
  • Grouping of related alerts into one incident
  • Silence rules for scheduled maintenance windows
  • Runbook links directly in the alert message

The Result

  • MTTR (mean time to resolve) reduced from hours to under 15 minutes
  • Proactive detection of 90% of problems before users are affected
  • Central overview of 24 servers and 61 microservices
  • Capacity planning prevents bottlenecks through trend analysis

Highlights

✓ Prometheus metrics collection
✓ Grafana dashboards
✓ Loki log aggregation
✓ Alloy as collection agent
✓ Alerting via email/Slack/Teams
✓ Infrastructure-as-code setup