Indexed logs without lifecycle rules are the most common silent bill driver.
Datadog
Reduce Datadog spend without breaking signals teams trust
Datadog economics track indexed logs, custom metrics, and hosts — choices made under delivery pressure. Finance sees spikes; engineering fears blind cuts; security worries about losing cloud detection signals.
Bill drivers Indexed logs Custom metrics Guardrails
Why this matters
Why this matters
Blind sampling or index changes break incidents and compliance narratives. Optimisation needs cross-functional guardrails, not arbitrary caps.
Custom metrics from auto-instrumentation sprawl inflate cost faster than teams realise.
Cribl or pipeline reduction upstream should align with Datadog indexing — not fight it.
What you get
Clear outputs you can use
Scoped Datadog cost optimisation: indexed log and custom metric review, sampling and pipeline guardrails, tag discipline enforcement, and measurable targets — aligned with general observability cost visibility where helpful.
- ✓ Top bill driver analysis for agreed orgs and services
- ✓ Recommendations for logs, metrics, hosts, and sampling with consumer sign-off criteria
- ✓ Before/after targets and runbooks for ongoing cost governance
Why teams talk to GKC
Calm, practical, and grounded in the environment you already have
Measurable targets agreed upfront — not fear-based downsell
Coordinates with general observability-cost-visibility and Cribl optimisation when pipelines overlap
Security-relevant streams explicitly protected where cloud monitoring is in scope
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
Baseline spend and drivers
We analyse usage by product line, top services, indexed logs, and custom metrics with FinOps and platform input.
2
Design and apply optimisations
Agreed changes to indexes, metrics, hosts, or pipelines deploy in controlled windows with validation.
3
Validate and hand over
You receive governance notes and monitoring for cost health — usable with internal FinOps cadences.
Questions teams often have
Common questions
Can’t we just drop log indexes?
Index changes affect search and detections. We fix structure and lifecycle first, then economics — with explicit protected streams.
Will you make us leave Datadog?
No. Optimisation assumes Datadog remains in play. Exit or consolidation conversations are separate, explicitly scoped decisions.
Splunk is our log archive. Does Datadog cost work still apply?
Yes, for what you intentionally operate in Datadog. We align with Cribl or Splunk routing so reduction does not duplicate or drop required events.
Related services
If this is close, these may be relevant too
Datadog
Monitor & SLO Rationalisation
Bounded monitor and SLO rationalisation: policy cleanup, threshold alignment, ownership mapping, and SLO patterns for priority services — with measurable before/after targets.
Datadog
Datadog Estate Assessment
A bounded Datadog estate assessment: agent and integration coverage, bill drivers, monitor and tag hygiene, and prioritised recommendations — with practical boundaries for what belongs in Datadog versus existing SIEM or logging platforms.
Value and Cost Clarity
Observability Cost Visibility
Observability Cost Visibility gives teams a clearer view of what is driving cost, where patterns are changing, and which areas deserve attention first.
Cribl
Pipeline Optimisation & Reduction Programme
Bounded Cribl pipeline optimisation programme: route and processor changes, sampling and aggregation guardrails, before/after targets, and runbooks — coordinated with Splunk, Elastic, and SaaS sink owners.
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.