High-cardinality labels are the most common silent Mimir and Cloud Metrics cost driver.
Grafana
Bring discipline to Prometheus and Mimir metrics at scale
Metrics estates grow faster than governance — high-cardinality labels, redundant scrapes, and recording rules nobody owns. Costs rise and alerts still lack the signal SREs need during incidents.
Cardinality control Recording rules Scrape hygiene Alert-ready metrics
Why this matters
Why this matters
Cardinality and rule sprawl undermine both billing predictability and alert quality in Grafana-backed observability.
Recording rules without documentation become tribal knowledge when on-call rotates.
Remote write and HA patterns need explicit design — not copy-paste from blog posts.
What you get
Clear outputs you can use
Bounded Prometheus/Mimir programme: cardinality analysis, recording and aggregation rules, scrape hygiene, and alert-ready metric standards for agreed domains.
- ✓ Cardinality and scrape findings for agreed namespaces or services
- ✓ Recording rule and aggregation standards with implemented exemplars
- ✓ Runbooks for onboarding new metrics safely into Mimir or Prometheus
Why teams talk to GKC
Calm, practical, and grounded in the environment you already have
Targets agreed upfront — e.g. series reduction bands on priority metrics
Self-managed Prometheus or Grafana Mimir/Cloud Metrics as scoped
Coordinates with general ingestion optimisation when pipelines overlap
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 metrics posture
We review cardinality hotspots, scrape configs, recording rules, and alerts tied to priority services.
2
Implement controls and rules
Agreed label rules, recording rules, and scrape changes are deployed with validation on representative workloads.
3
Hand over standards
You receive governance notes and backlog for wider rollout or dashboard implementation.
Questions teams often have
Common questions
We only use Grafana Cloud Metrics. Is Prometheus relevant?
Yes. The programme addresses Cloud Metrics and Mimir patterns — Prometheus-compatible discipline applies across deployments.
Can you eliminate all high-cardinality metrics?
We prioritise cost and alert impact — some cardinality is legitimate. The goal is governance, not arbitrary slashing.
Will this fix logs and traces too?
Logs belong in Loki optimisation; traces in a Tempo wave. This engagement stays metrics-focused.
Related services
If this is close, these may be relevant too
Grafana
Loki Log Pipeline Optimisation
A scoped optimisation of your Loki ingest path: label strategy, retention, agents/collectors, and query patterns — with measurable before/after targets.
Grafana
LGTM / Grafana Cloud Architecture Design
Scoped LGTM and Grafana Cloud architecture design: tenancy, environments, cardinality and retention guardrails, access model, and coexistence with existing observability tools.
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.
Value and Cost Clarity
Data Ingestion Optimisation
Data Ingestion Optimisation reviews where data volume is coming from, what is worth retaining, and where fast savings may be available.
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.