Auto-instrumentation without sampling discipline can inflate ingest without improving triage.
Splunk Observability Cloud
Implement APM and tracing for the services that matter most
APM programmes stall when every team wants full coverage day one. Without scoped instrumentation and sampling rules, traces are incomplete, costs climb, and service maps mislead during outages.
Top-N services Sampling strategy Service maps SRE handover
Why this matters
Why this matters
Reliable traces for priority services shorten MTTR and make observability spend defensible to engineering leadership.
Service maps only help when naming, dependencies, and ownership match how teams run incidents.
OpenTelemetry can feed Observability Cloud — instrumentation choices belong in scope upfront.
What you get
Clear outputs you can use
Bounded APM and distributed tracing implementation in Splunk Observability Cloud: instrumentation for agreed services, trace sampling strategy, service map validation, and SRE handover.
- ✓ Instrumented services per SOW with trace and service map validation evidence
- ✓ Sampling and retention guidance for metrics and traces on agreed services
- ✓ Runbooks and tuning notes for SRE and development owners
Why teams talk to GKC
Calm, practical, and grounded in the environment you already have
Scoped by service count and complexity — additional services are change-controlled
Testing on representative load and failure modes — not demo-only happy paths
No SIEM or detection content — stays in Observability Cloud and SRE workflows
What happens next
A straightforward first step
We keep the first step straightforward so you can understand fit, scope, and likely value before deciding what to do next.
1
Agree services and acceptance
We confirm priority services, instrumentation approach (agent, OTEL, language SDKs), and what “done” means for traces and maps.
2
Implement and validate
Instrumentation and sampling are deployed with validation against representative traffic and incident scenarios.
3
Hand over for day-2
You receive documentation, ownership map, and backlog for the next service wave or signal optimisation.
Questions teams often have
Common questions
We already instrument with OpenTelemetry elsewhere. Can you use that?
Yes when architecture supports it. We align collectors and exporters with Observability Cloud ingest — without forcing duplicate agents.
Why not implement on Dynatrace or Datadog instead?
This service is for Splunk Observability Cloud. Portfolio workshops can compare fit; implementation stays on the hub you operate.
Will you tune our ES correlation searches?
No. Detection engineering belongs on the Splunk ES hub. We focus on traces, metrics, and SRE triage workflows here.
Related services
If this is close, these may be relevant too
Splunk Observability Cloud
Signal Optimisation & Alert Rationalisation
Focused signal optimisation in Splunk Observability Cloud: noise reduction, detector and alert review, SLO-oriented alerting patterns, and a prioritised backlog SRE teams can own.
Splunk Observability Cloud
Observability Cloud Integration (K8s, Cloud, CI/CD)
Scoped Observability Cloud integration for agreed environments: collectors and operators, Kubernetes and cloud patterns, CI/CD deployment hooks, and handover runbooks for platform owners.
Value and Cost Clarity
Observability Health Check
The Observability Health Check is a focused review of how your current setup is performing, where value is being lost, and what to improve first.
Splunk Platform
Data Onboarding & Sourcetype Design Accelerator
Accelerated onboarding for agreed priority sources: sourcetype design, parsing, field extraction, CIM alignment, and validation evidence your platform team can maintain.
Next step
Start with a practical conversation
We can talk through the environment, what is making this feel urgent or uncertain, and whether this service is the right fit. If another starting point makes more sense, we will say so.