Kubernetes Observability
Control Kubernetes observability cost in dynamic production environments
SAB Consulting analyzes how clusters, namespaces, workloads, labels, containers, agents and telemetry pipelines generate observability cost across Kubernetes environments.
The problem with Kubernetes observability cost
Kubernetes changes the economics of observability. Ephemeral workloads, container churn, high-cardinality labels, Prometheus metrics, verbose application logs and multiple collection agents can create rapid and difficult-to-allocate growth. The problem is rarely solved by one retention change. It requires policies that connect telemetry generation with platform ownership and diagnostic value.
What we assess
- Cluster and namespace structure
- Host, node, pod and container monitoring
- Labels, annotations and cardinality
- Prometheus metrics and scrape configuration
- Application and platform logs
- Trace generation and sampling
- DaemonSets, agents and duplicate collection
- Ephemeral jobs and autoscaling behaviour
- Telemetry routing and filtering
- Allocation by team, namespace, service and environment
- OpenTelemetry adoption opportunities
- Governance for onboarding new workloads
What you receive
- A Kubernetes telemetry baseline
- Cardinality and volume findings
- Collection and agent-rationalization recommendations
- Filtering, sampling and routing opportunities
- Allocation and governance model
- Implementation priorities with production safeguards
Frequently asked questions
Yes. The assessment can cover managed and self-managed clusters across one or more cloud environments.
No. Existing agents and pipelines are evaluated first. Replacement or consolidation is recommended only where it provides a clear operational or financial benefit.
Related services
Start with a focused assessment
Share the platform, cost or reliability problem you are trying to solve. SAB Consulting will help define the right assessment, the evidence required and the practical next step.