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Cluster Monitoring is a Kubernetes-native monitoring stack built on Prometheus Operator that bundles Prometheus, Grafana, Alertmanager, and exporters into pre-configured manifests. It supports hybrid ARM/x86-64 clusters and simplifies deployment with jsonnet-based customization and make-based tooling.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | carlosedp/cluster-monitoring |
| Owner | carlosedp |
| Primary language | Jsonnet |
| License | MIT — OSI-approved |
| Stars | 754 |
| Forks | 199 |
| Open issues | 4 |
| Latest release | Unknown |
| Last updated | 2025-08-22 |
| Source | https://github.com/carlosedp/cluster-monitoring |
What cluster-monitoring is
A jsonnet-based IaC layer over Prometheus Operator that generates Kubernetes manifests for a complete monitoring observability stack including highly available Prometheus/Alertmanager, node-exporter, kube-state-metrics, and Grafana with optional modules for specialty metrics (MetalLB, Traefik, ElasticSearch, UPS). Supports multi-architecture container images (AMD64, ARM64, ARM, PPC64le) and both standard and K3s deployments.
Get the cluster-monitoring source
Clone the repository and explore it locally.
git clone https://github.com/carlosedp/cluster-monitoring.gitcd cluster-monitoring# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Requires Go 1.18+ and jb toolchain for any customization; docker make target available to avoid local setup but still requires Docker.
- Pre-built manifests provided for quick start, but ingress domain/suffix customization via Makefile targets or full vars.jsonnet rebuild may be needed for production.
- Persistence (PVC/PV) disabled by default; must explicitly enable in vars.jsonnet and verify UID:GID (Prometheus 1000:0, Grafana 472:472) for existing PVs.
- CRD application may require multiple kubectl apply runs due to ordering dependencies; documented as a known issue with workaround provided.
- Custom container images mean responsibility for tracking upstream Prometheus/Alertmanager CVEs separately from official channels; no stated patching cadence.
When to avoid it — and what to weigh
- Need active upstream maintenance and frequent updates — No versioned releases (latest: none), last push August 2025 but no release history published. Unclear frequency of updates to bundled component versions.
- Require minimal customization friction — Heavy reliance on jsonnet + jb + Go toolchain for customization. Pre-built manifests available but any tuning beyond vars.jsonnet requires full rebuild pipeline; steeper than Helm charts.
- Need commercial support or SLA guarantees — Single-author open-source project with Patreon funding model. No documented support pathway, SLA, or vendor backing. Community-driven only.
- Seeking vendor-neutral standard distribution — Uses custom container images (carlosedp/prometheus, carlosedp/alertmanager, etc.) rather than upstream official images. Dependency on personal Docker Hub repositories introduces supply-chain risk.
License & commercial use
MIT License—permissive, allows commercial use, modification, and distribution with attribution and no warranty. No proprietary or copyleft restrictions.
MIT is an OSI-compliant permissive license permitting commercial use without restrictions. However, the project uses custom container images (carlosedp/*) which introduce supply-chain considerations; verify image source and maintenance policies for production workloads. No commercial support offered by the author.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Moderate |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Good |
| Assessment confidence | Medium |
No security audit or vulnerability disclosure policy mentioned. Custom container images (carlosedp/prometheus, etc.) shift responsibility for CVE tracking to user; no stated image scanning or update SLA. TLS ingress configurable but no hardening guide. Grafana and Prometheus default credentials/access control configuration not explicitly documented. SMTP relay (Gmail) requires plaintext credential secrets; no encryption at rest mentioned.
Alternatives to consider
kube-prometheus-stack (Helm chart)
Upstream, actively maintained by Prometheus community, official images, Helm packaging reduces deployment friction, broader adoption and support. Best for teams preferring vendor-maintained standards.
Prometheus Operator + custom manifests
Full control over component versions, images, and configuration; no dependency on third-party jsonnet libraries or custom images. Suitable if you need minimalist or tightly audited environments.
Rancher Monitoring (fleet-managed)
Opinionated, multi-cluster focused, tighter Kubernetes/Rancher integration, enterprise support options. Better fit if managing clusters at scale across diverse environments.
Build on cluster-monitoring with DEV.co software developers
Review the maintenance status, image sources, and support model before committing to production. Consider it for quick evaluation labs or hybrid ARM clusters; assess upstream kube-prometheus-stack or managed solutions for mission-critical deployments.
Talk to DEV.coRelated open-source tools
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cluster-monitoring FAQ
Can I use this on production Kubernetes clusters?
Do I need to install jsonnet and jb to use this?
What happens if I want to upgrade Prometheus, Grafana, or Alertmanager versions?
Are the custom container images (carlosedp/*) necessary or can I use official images?
From evaluation to production software
Bringing cluster-monitoring into production usually means new services, new interfaces, and new failure modes. DEV.co is a software development agency that builds all three and stays on for the open-source observability maintenance.
Evaluate cluster-monitoring for your Kubernetes observability
Review the maintenance status, image sources, and support model before committing to production. Consider it for quick evaluation labs or hybrid ARM clusters; assess upstream kube-prometheus-stack or managed solutions for mission-critical deployments.