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Fortune 50 · Technology · 16 weeks · 200+ services, 8 collectors

OpenTelemetry Migration

Migrated 200+ services from proprietary APM to OpenTelemetry pipelines. Reduced ingest costs by 42% while preserving full trace fidelity.

Outcome at a Glance

42%
Ingest cost reduction
200+
Services migrated
0
Trace gaps

The Challenge

A Fortune 50 technology company was locked into a proprietary APM agent across 200+ services. Annual ingest costs had crossed $4M and were forecast to double in two years. They needed a vendor-neutral path forward without losing any of the observability they'd built.

  • Vendor lock-in: Proprietary instrumentation made every service migration a re-platforming exercise.
  • Runaway ingest: 100% trace capture on services that didn't need it; high-cardinality attributes inflating storage.
  • Zero-tolerance for trace gaps: Several teams used distributed traces as their primary debugging tool — a regression in trace fidelity was a non-starter.
  • Multi-language complexity: Services in Go, Java, Python, Node, and Rust — each needing its own OTel SDK strategy.

Our Approach

OTel collector architecture

8-collector deployment in a gateway-and-agent topology, with regional aggregators and tail-sampling decision tier.

  • • Sidecar agents for trace generation
  • • Gateway collectors for sampling decisions
  • • Backend exporters with vendor abstraction

Tail-based sampling

Replaced head-based 100% capture with tail sampling that keeps every error and slow trace, drops uninteresting fast-success traces.

  • • 100% retention on errors and slow traces
  • • Service-tier-based sampling rates
  • • Per-route policy overrides

Per-language SDK rollout

Standardized auto-instrumentation packages and reference services per language, with paved-path templates for new services.

  • • Auto-instrumentation defaults
  • • Internal SDK wrappers for context propagation
  • • Reference services per language

Parallel-run validation

Ran legacy and OTel pipelines side-by-side per service for a 2-week validation window before cutover. Zero trace regressions hit production.

  • • Trace-completeness regression tests
  • • Cardinality budgets enforced in CI
  • • Phased per-service cutover

Detailed Results

Before

  • • ~$4M annual ingest cost
  • • 100% trace capture on all services
  • • Single-vendor lock-in
  • • Proprietary instrumentation per language

After

  • • 42% reduction in annual ingest cost
  • • Tail-sampled with full error retention
  • • Vendor-neutral pipeline (OTLP)
  • • Standardized OTel auto-instrumentation

Considering an OTel migration?

Most OTel migrations regress on trace quality and break debug workflows. We do them without that.

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