Integrating Observability and Monitoring for a European Streaming Service, Reducing Latency by 20%

The client’s streaming platform experienced intermittent performance degradation during peak viewing hours, but the engineering team had no visibility into where latency was introduced. Without distributed tracing or centralised metrics, diagnosing issues required manual log analysis across dozens of microservices — a process that could take hours while users experienced buffering and playback failures.

We implemented a comprehensive observability stack using Prometheus for metrics collection, Grafana for real-time dashboards and alerting, and Jaeger for distributed request tracing across all microservices. Custom dashboards were built for the operations team showing request latency, error rates, throughput, and resource utilisation in real time. Proactive alerting rules were configured with defined thresholds for CPU usage, response time, and error rates — notifying the team before issues impacted users. Jaeger tracing identified specific bottlenecks including redundant database queries and inefficient API calls between services.

End-to-end latency was reduced by 20%. The engineering team gained the ability to identify and resolve performance issues in minutes rather than hours. Proactive alerting caught anomalies before they affected users, and the tracing data informed targeted optimisations that improved service response times across the platform. Auto-scaling strategies informed by the metrics data ensured consistent performance during peak viewership.