Intro
When systems are small, logs are enough. You can SSH into a server, check output, and reconstruct what happened.
In distributed systems, that approach breaks immediately.
Bottlenecks
Our main issue was lack of correlation between services:
- logs existed but were isolated per service
- no request tracing across boundaries
- debugging required manual log correlation
- incident resolution time grew linearly with system complexity
We were not missing data — we were missing context.
Migration strategy
We introduced structured observability in stages:
- standardized logging format across all services
- implemented distributed tracing (OpenTelemetry)
- added trace propagation between services
- centralized metrics collection
This allowed us to reconstruct full request lifecycles across services.
Event system
Once event-driven architecture was introduced, observability became even more critical.
Each event now carried:
- trace ID
- correlation context
- service lineage
This made it possible to debug asynchronous flows as if they were synchronous.
Infrastructure
We unified observability stack:
- OpenTelemetry for traces
- Prometheus for metrics
- centralized log aggregation
- alerting based on SLOs instead of raw thresholds
The shift was from “reacting to errors” to “understanding system behavior”.
Results
- debugging time dropped from hours to minutes
- root cause analysis became deterministic
- cross-service issues became traceable
- on-call load decreased significantly
Lessons
The key insight:
Without observability, distributed systems are just distributed guessing.
Instrumentation is not optional — it is part of the architecture.