etcd on Netdata

etcd Monitoring

Mon, 01 Jan 0001 00:00:00 +0000

etcd Monitoring

What Is etcd?

etcd, a distributed key-value store, is a critical component for service discovery and storing all of a cluster’s data reliably. It ensures that the systems in production environments are available and consistent. etcd is often implemented in environments requiring fault tolerance, distributed networking, or consensus building. Learn more about etcd.

Monitoring etcd With Netdata

When it comes to monitoring etcd, Netdata stands out as a powerful tool. Netdata leverages an OpenMetrics (Prometheus) exporter to monitor etcd, facilitating effortless integration. This capability permits Netdata to ingest metrics from any Prometheus exporter, delivering dynamic dashboards, alerts, and comprehensive insights that require neither a dedicated Prometheus server nor Grafana setup.

Kubernetes API Server etcd Latency: How To Fix It

Mon, 01 Jan 0001 00:00:00 +0000

When etcd slows down, the entire control plane slows with it. A few extra milliseconds on disk fsync turns into hung kubectl commands, backed-up controller queues, and eventually a cluster that cannot schedule pods or update endpoints. Detect the etcd latency cascade, confirm whether storage is the root cause, and break the feedback loop before the cluster becomes effectively read-only.

What This Means

etcd serializes every Kubernetes mutation. Every API server write becomes a Raft proposal that must fsync to the WAL before etcd acknowledges it. When the disk under etcd is slow, every fsync waits longer. The API server holds mutating requests open until etcd responds. Requests pile up in the inflight queue. Once the queue hits the limit, the API server returns 429 Too Many Requests. Controllers that depend on writes (scheduler, replica set controller, and others) fall behind and retry. Retries generate more write load. The result is a feedback loop: slow disk -> slow etcd -> slow API server -> retry storm -> amplified etcd load.

Kubernetes API Server Slow Or Unresponsive: Causes & Fixes

Mon, 01 Jan 0001 00:00:00 +0000

When kubectl hangs, controllers log context deadline exceeded, and deployments stall, the Kubernetes API server is usually the bottleneck. It is the single funnel for every read and write to cluster state. Slowness propagates to scheduling, pod lifecycle, service discovery, and external automation.

This article covers operational causes and gives a step-by-step diagnostic flow to run during an incident. Use it to distinguish etcd latency, admission webhook stalls, request saturation, and memory pressure.

Kubernetes Controller-Manager Leader Election Failures

Mon, 01 Jan 0001 00:00:00 +0000

Your Deployment has stopped scaling. Nodes cordoned hours ago are still draining. Garbage collection is paused, and orphaned volumes are not being cleaned up. The kube-controller-manager runs these reconciliation loops, and in an HA cluster only the leader performs work. When leader election fails, the controller-manager exits, and the control plane stops acting on desired state. Existing workloads keep running, but nothing new is managed.

The kube-controller-manager coordinates through a Lease object in the coordination.k8s.io API group. The leader must renew the lease before --leader-elect-renew-deadline (default 10 seconds) elapses. The lease itself expires after --leader-elect-lease-duration (default 15 seconds). Renewal is attempted every --leader-elect-retry-period (default 2 seconds). If a write to etcd is too slow, if the API server is saturated, if RBAC is stripped, or if the election timing is misconfigured, the leader loses the lock, logs leaderelection lost, and exits. During the gap, no instance holds a valid lease, so controllers stop reconciling.

Kubernetes Monitoring Checklist: The Signals Every Production Cluster Needs

Mon, 01 Jan 0001 00:00:00 +0000

This article is a reference checklist for senior engineers who are wiring up, auditing, or hardening monitoring for a production Kubernetes cluster. It assumes you already understand the control plane architecture and focuses on what to collect, where to find it, and which symptoms matter. Use it during greenfield instrumentation, post-incident gap analysis, or routine health audits.

The signals are grouped by domain. Each entry leads with a short noun phrase, followed by one sentence explaining why it matters, and a concrete warning sign to alert on. Thresholds are drawn from upstream SLOs, kubelet defaults, and etcd operational limits documented in the Kubernetes source and production playbooks. If you run a managed service such as EKS, GKE, or AKS, treat control-plane metrics as provider-mediated; many etcd and API server internals are opaque in those environments.

Kubernetes Operations Guides

Mon, 01 Jan 0001 00:00:00 +0000

Learn what actually breaks in production Kubernetes clusters, how to diagnose it, and what to monitor so the next incident is shorter than the last one.

Kubernetes Scheduler Not Scheduling Pods: Queue Depth & Failure Reasons

Mon, 01 Jan 0001 00:00:00 +0000

Pods stay Pending for many reasons, but the scheduler process being down is rarely one. More often, pods accumulate in internal queues because the cluster is out of capacity, a control plane dependency stalls the binding cycle, or a filter plugin rejects every candidate node. Distinguishing “unschedulable” (no node fits) from “not scheduling” (the scheduler cannot keep up or the binding cycle is failing) prevents wasted node scaling when the real problem is an etcd latency spike or a volume affinity conflict.