Customer description‍

A software company with multiple SaaS applications in production, spread across cloud environments. The DevOps teams lacked overview and control over incidents due to fragmented logging and monitoring.

Challenge‍

Incidents in production were often only detected after customer reports. Logs were scattered across systems, there was no central overview of performance anomalies and alerting did not work consistently. As a result, it took a long time to detect and resolve issues.

Solution‍

A solution that includes a modern observability stack including Grafana, Loki and Prometheus was implemented. Logs, metrics, and traces were centrally collected, enriched and visualized, with AI-based detection of anomalous behavior.

Approach

1. Inventory and standardization of log sources
   We collected logs, metrics, and events from various services, microservices, and infrastructure layers.
2. Observability stack setup
   Implementation of Loki for log processing, Prometheus for metrics, and Grafana for dashboards and alerts.
3. Alerting and anomaly detection
   Based on patterns in performance and error messages, alert rules were created and enriched with AI estimates of severity.
4. Dashboarding and knowledge transfer
   DevOps teams received real-time insight into system health and attended training courses to accelerate incident detection.

Results

• 60% faster detection of incidents in production
• 40% shorter average recovery time (MTTR)
• More control over system performance and availability
• Less dependence on customer reports in case of issues

Learnings‍

With central logging, smart alerting and real-time dashboards, the company got structural control over its software environment. The collaboration with the organization brought peace, control and scalability to the DevOps teams. Read how this came about.

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