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Deploy VictoriaMetrics on Kubernetes: Fast Metrics

Tags:
Time Series DatabaseKubernetesvictoriametricsKubekanvasPrometheus
Created by:
Siddiqui
Deploy VictoriaMetrics on Kubernetes: Fast Metrics template preview
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Engineering teams requiring efficient time series metric collection often face high memory consumption with standard Prometheus setups. This architecture provisions a lightweight monitoring stack using a VictoriaMetrics time series database and a vmagent metrics collector. Setting up this VictoriaMetrics Kubernetes deployment provides a scalable destination for Prometheus-compatible remote write targets and scrapers, making it straightforward to deploy VictoriaMetrics on Kubernetes.

What's Included

ComponentTypePortRole
monitoringNamespaceN/AIsolates monitoring resources within the cluster
victoriametrics-dataPersistentVolumeClaimN/AProvisions 20Gi persistent storage for time series data
victoriametrics-svcService8428Exposes VictoriaMetrics API and ingestion endpoints internally
vmagent-configConfigMapN/ADefines Prometheus-compatible scrape configuration for vmagent
vmagentDeployment8429Collects operational metrics and pushes them to VictoriaMetrics
vmagentService8429Exposes vmagent metrics and health probes internally
victoriametricsDeployment8428Runs the single-node VictoriaMetrics time series database

Architecture Overview

The vmagent Deployment reads target endpoints from vmagent-config and continuously scrapes operational metrics. Collected data streams directly to victoriametrics-svc on port 8428 using the Prometheus remote write protocol. The victoriametrics Deployment writes time series data to the victoriametrics-data PersistentVolumeClaim mounted at /storage. Internal traffic routes across ClusterIP Services within the isolated Namespace.

Prerequisites

  • Active Kubernetes cluster with persistent volume provisioning enabled
  • KubeKanvas CLI installed and running on your computer (Optional, if you want to use one-click deployment)

How to Deploy

  1. Review the vmagent-config ConfigMap to add your custom target scrape jobs.
  2. Adjust the victoriametrics-data PersistentVolumeClaim size from 20Gi if your metrics retention demands more storage.
  3. Update resource requests and limits in the victoriametrics and vmagent Deployments according to your workload size.
  4. Deploy the template to your cluster via the Play button in the top right bar. If you prefer to deploy manually, download the YAML and apply it with kubectl.
  5. Wait for all pods to reach Running status. You can monitor progress in the Release Monitor screen.

How to Test

  1. Port-forward the victoriametrics-svc Service to your local machine using port 8428.
  2. Query the /health endpoint on localhost:8428 to confirm the VictoriaMetrics storage engine is responsive.
  3. Access http://localhost:8428/vmui in your browser and run a PromQL query such as up to verify metrics ingestion from vmagent.

Use Cases

  • Prometheus Replacement: Collects and stores high-cardinality time series metrics with reduced CPU and RAM usage compared to standard Prometheus instances.
  • Edge Metric Scraping: Collects operational metrics using vmagent and forwards them to a centralized VictoriaMetrics cluster over remote write.
  • Long-Term Metric Storage: Retains operational telemetry for 30 days using persistent volume storage mounted directly to the database container.

Summary

This VictoriaMetrics Kubernetes template deploys a single-instance time series database paired with a dedicated vmagent collector in a dedicated namespace. The configuration establishes automated metrics scraping, persistent storage mounting, and remote-write data ingestion.