Observability spending grows faster than engineering value.
SAB reviews Datadog, Elastic, OpenSearch, Splunk — logs, metrics, traces, retention, indexing, telemetry volume, and vendor cost traps — to reduce spend without weakening the signals engineers need during production incidents.
Telemetry grows silently
Logs, metrics, and traces expand faster than business value or engineering usefulness — with no one watching the meter.
Retention goes unreviewed
Teams keep low-value data for too long while critical signals remain hard to find during actual incidents.
Cost ownership is split
Platform teams pay the bill while application teams generate most of the volume — with no shared accountability model.
The problem
Observability spend grows silently until it becomes a platform-level business problem.
Teams keep too much low-value telemetry. Retention policies are rarely reviewed. Logs, metrics, and traces grow faster than business value. Engineers still miss the right signals during incidents because volume is not the same as visibility.
Common patterns
Platform teams inherit the bill
Application teams create telemetry volume, but platform or cloud teams explain the spend to finance.
Dashboards multiply, signal does not
More dashboards and alerts do not guarantee better incident response or better decisions.
Vendor pricing becomes the architecture
Datadog, Elastic, OpenSearch, Splunk costs shape engineering behavior when policy is unclear.
What SAB reviews
The review separates useful production visibility from expensive telemetry habit.
Every item below is reviewed against the actual production incidents of the past 12 months — to distinguish signal from cost habit.
Telemetry volume
Where logs, metrics, and traces grow faster than production usefulness.
Retention policy
Which data deserves long retention, short retention, or no retention at all.
Indexing strategy
How indexing choices affect cost, search speed, storage, and incident response time.
Dashboards & alerts
Which dashboards support action, and which only create noise and maintenance overhead.
Cost allocation
How to make teams accountable for the observability costs they generate.
Vendor lock-in
Where Datadog, Elastic, OpenSearch, Splunk, or cloud-native costs limit your negotiating leverage.
Team ownership
Who owns volume, retention, signal quality, and cleanup decisions going forward.
Optimization paths
Where to optimize first: policy change, contract renegotiation, migration, or architecture redesign.
What you receive
A practical decision pack for reducing spend without creating operational risk.
The output is designed for both executive review and platform implementation. It identifies where money is going, what can change safely, and what the first 90 days should look like.
Audit fee fully refunded if identified savings are under €75K annualized.
Cost driver analysis
Where spend is concentrated and what is driving growth.
Retention & signal policy
Recommendations for what to keep, compress, or delete.
Architecture review
How the current stack compares to lower-cost alternatives.
Vendor leverage
Where contract terms, pricing models, or alternatives give leverage.
Team ownership model
Who is accountable for what, going forward.
30/60/90-day roadmap
Sequenced implementation plan ready for engineering execution.
Executive-ready decision pack
Formatted for CTO and CFO review. Quantified savings estimate. Implementation risk assessment included.
Built for teams accountable for visibility, spend, and production operations