metrics-server
metrics-server is a Kubernetes add-on that aggregates resource metrics (CPU/memory) from kubelets and serves them to the Kubernetes API for components like kubectl top and Horizontal Pod Autoscaler (HPA).
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Security is largely delegated to Kubernetes primitives (RBAC/service accounts) and cluster TLS/kubelet configuration. Without repository-specific evidence here, dependency posture and exact secret-handling cannot be verified.
⚡ Reliability
Best When
You need lightweight CPU/memory metrics in-cluster for kubectl top and HPA, and you’re not already running a full metrics pipeline.
Avoid When
You require high-cardinality/long-retention metrics, custom metrics types, or non-CPU/memory metrics (use Prometheus Adapter or other monitoring stack).
Use Cases
- • Autoscaling workloads based on CPU/memory utilization (HPA)
- • Debugging/observability via kubectl top
- • Centralized metrics aggregation within a Kubernetes cluster
Not For
- • Metrics collection outside Kubernetes
- • Production-grade long-term metrics storage/analytics (e.g., Prometheus storage backend)
- • GPU metrics collection (not typical for metrics-server)
Interface
Authentication
As a Kubernetes component, access is typically governed via Kubernetes RBAC/service accounts rather than an external API auth scheme.
Pricing
Open-source/community component; no public vendor pricing detected from provided content.
Agent Metadata
Known Gotchas
- ⚠ Kubernetes add-ons often depend on cluster permissions (RBAC), TLS/kubelet reachability, and correct APIService registration; failures may appear as Kubernetes events/logs rather than agent-friendly HTTP error responses.
- ⚠ Because this is not a typical standalone API service, rate limits and auth semantics are governed by Kubernetes components and kubelet connectivity rather than by a documented public API.
Alternatives
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Scores are editorial opinions as of 2026-04-04.