Traces crossing services, queues, APIs or jobs
OpenTelemetry as a common layer, not a mass migration
We define conventions, collectors, OTLP pipelines and cardinality control so telemetry becomes portable without breaking what already works.
- Conventions before volume
- Governed collectors
- Observable pipelines
Where OpenTelemetry adds value
Value appears when systems are distributed, several backends coexist or teams need to speak the same signal language without depending on one vendor.
Kubernetes and mixed runtimes with inconsistent conventions
Elastic, Dynatrace, Grafana or Prometheus backends coexisting
AI and LLM applications that need custom attributes
Minimum viable design
We do not start by instrumenting everything. We pick a critical flow, define attributes, sampling and export paths, then validate that the backend receives useful signal.
Naming, service, environment and business conventions
Collector architecture with reviewable exporters and processors
Instrumentation plan by priority and risk
Compatibility tests with existing backends
Maintainable technical base
The output is not an isolated lab, but a telemetry base the team can extend with cost, quality and ownership under control.
Less lock-in without losing current backend capabilities
Comparable signals across services and teams
Auditable pipelines before data is sent
Documented sampling, cardinality and retention criteria
Evaluate OpenTelemetry
We analyze your current stack and decide where OpenTelemetry provides real interoperability.
Evaluate OpenTelemetry