What is the role of telemetry in database observability?

Telemetry plays a critical role in database observability by providing real-time and historical data about a database’s performance, health, and behavior. It involves collecting metrics, logs, and traces from the database system and its components, enabling developers and administrators to monitor, troubleshoot, and optimize operations. Without telemetry, diagnosing issues like slow queries, resource bottlenecks, or unexpected errors would rely heavily on guesswork or manual inspection. Telemetry automates data collection, surfaces patterns, and offers insights into how the database interacts with applications and infrastructure, making it foundational for maintaining reliability and performance.

For example, telemetry systems track metrics such as query execution times, connection counts, CPU/memory usage, and error rates. If an application experiences sudden latency, telemetry data can reveal whether the issue stems from a spike in query response times, a shortage of available connections, or high disk I/O. Tools like Prometheus or built-in database monitors (e.g., PostgreSQL’s pg_stat_activity) aggregate this data into dashboards, allowing teams to correlate anomalies with specific events, such as a deployment or traffic surge. Telemetry also captures structured logs (e.g., failed login attempts or deadlock warnings) and distributed traces, which help pinpoint the root cause of cascading failures across microservices that share the same database.

Beyond troubleshooting, telemetry supports proactive optimization. By analyzing trends in query performance or resource utilization, teams can identify inefficient indexes, over-provisioned instances, or underused caching strategies. For instance, consistently high CPU usage might prompt a review of unoptimized queries or the need for read replicas. Telemetry also aids capacity planning—tracking storage growth rates helps predict when to scale disk space. Additionally, security auditing benefits from telemetry by logging access patterns or unauthorized activities. By making database behavior transparent, telemetry transforms raw data into actionable insights, ensuring systems remain scalable, efficient, and resilient under varying workloads.