Uptime Kuma vs Gatus: What a Click-Configured Status Page Costs a GitOps Fleet

The most popular self-hosted uptime monitor on GitHub has ten times the stars of its leanest rival — and the two tools disagree about something fundamental: whether your monitors should live behind clicks or in version control. DevHelm's June 2026 hands-on test of seven self-hosted monitoring tools put Uptime Kuma at 60,000+ stars against Gatus at 6,000+, and the gap isn't about check quality. Both tools ping HTTP endpoints reliably. The gap is about who owns the configuration: a person with a browser, or a Git repo with a review trail.

If you run a fleet where every other piece of infrastructure arrives via pull request, that difference is the whole buying decision. Here is the head-to-head, with the verdict up front.

The verdict in one table​

Short version: pick Uptime Kuma if alerting breadth and the prettiest tenant-facing status page matter most. Pick Gatus if monitors-as-YAML that reviews like any other manifest matters most. If you need infrastructure metrics, neither tool is the answer — DevHelm's own guidance is that Prometheus plus the Blackbox Exporter is overkill for endpoint checks but mandatory once you want CPU, memory, and SLO dashboards. This post is about the endpoint-and-status-page layer only.

What Uptime Kuma gives you​

Uptime Kuma is the self-hosted answer to Uptime Robot: one Docker container, a SQLite database in a volume, and you are monitoring. The onboarding really is one command — docker run -p 3001:3001 louislam/uptime-kuma — and from there everything happens in a polished, mobile-friendly UI with dark mode.

The headline numbers explain the star count. DevHelm counts 95+ notification integrations — Slack, Discord, Telegram, PagerDuty, Opsgenie, and dozens of niche providers — which means the odds are good your existing paging path already has a first-class Kuma integration.

Monitor coverage is broad: HTTP(S), TCP, DNS, ping, MQTT, gRPC, plus database and Docker-container health checks. Certificate-expiry monitoring ships with configurable thresholds, and maintenance windows let you suppress alerts during planned work instead of training the team to ignore pages.

Status pages are a core feature, not an afterthought. Kuma supports multiple public status pages with custom domains, which is exactly what a platform team needs when tenants ask "is it down for everyone or just me?" during an incident.

The project has been consistently maintained since 2021 with weekly patch releases, 500+ contributors, and issue response times typically under 48 hours. The 2.x line has been stable since October 2025, adding monitor types like RabbitMQ, SNMP, SMTP, and system-service checks.

The honest limitations, per the same hands-on test: single-node only with no built-in clustering, no infrastructure metrics, SQLite that strains past roughly 1,000 frequently-checked monitors, all probes originating from one location, and a limited API. But the limitation that matters most for a GitOps fleet deserves its own section.

What Gatus gives you​

Gatus is what you would build if you wanted a monitoring tool that fits in a single config file. You define endpoints and health conditions in YAML, Gatus checks them on a schedule, and it serves a clean status dashboard. There is no database in the default configuration — data lives in memory with optional file or SQL persistence — and the whole thing is a single Go binary with zero dependencies.

The design philosophy is minimal and opinionated. Health is expressed as conditions, not alerting rules:

endpoints:
  - name: api
    url: https://api.example.com/health
    interval: 30s
    conditions:
      - "[STATUS] == 200"
      - "[RESPONSE_TIME] < 500"
      - "[BODY].status == UP"

That snippet is reviewable in a pull request, diffable across environments, and restorable from Git after a disaster — properties no UI-configured tool can match without extra machinery. Gatus supports HTTP, TCP, DNS, ICMP, SSH, and STARTTLS checks, alerts to Slack, PagerDuty, Telegram, Teams, Discord, and more, and generates badges for README files. Resource use is tiny: around 50 MB of RAM for hundreds of checks, runnable on the smallest VM you have.

The trade-offs are the mirror image of Kuma's. There is no UI for configuration — you edit YAML and reload. Historical data is limited by configured retention and memory. It is single-instance only, collects no infrastructure metrics, and its notification catalog is smaller and less customizable than Kuma's 95+ integrations. The community is an order of magnitude smaller (one primary maintainer, TwiN, plus contributors), so niche integrations arrive more slowly.

The real cost: where your monitors live​

Here is the question that decides it for a GitOps fleet: when a monitor changes, is that change a commit or a click?

In Uptime Kuma, every monitor lives in a SQLite file on the instance's volume. Adding a check for a new service means opening the UI and clicking through a form. Auditing who changed what means hoping someone remembers. Disaster recovery means restoring a database backup — DevHelm notes backups are just copying the SQLite file, which is simple but sits entirely outside your Git workflow. There is no native config-as-code path; the community has built workarounds like a Terraform provider for Kuma 2.x and API-driven reconciler scripts, but those are bridges over an architecture that assumes a human with a browser.

In Gatus, every monitor lives in config.yaml. Adding a check for a new service is a pull request that gets reviewed, tested in staging, and rolled out with the same pipeline as the app change that motivated it. Drift between environments shows up as a diff. Rollback is git revert. For a team already running GitOps, this isn't a nice-to-have — it is the difference between monitoring configuration that participates in your change-control story and monitoring configuration that quietly opts out of it.

That is why the practitioner verdicts keep landing on Gatus for GitOps shops despite the 10-to-1 star gap. Better Stack's 2026 comparison makes the same split explicit: Gatus is the YAML-configured alternative whose UI is less polished, while Kuma wins on approachability and integration breadth. Stars measure popularity across all users — homelabbers included, where Kuma's one-container setup dominates. Your fleet is not a homelab.

One caveat worth stating plainly: neither tool does distributed checking. Every probe originates from wherever the single instance runs, so a network partition between your monitor and your tenants can read as an outage that isn't one — or worse, miss one that is. If you need multi-region probing, that is a separate buying decision (OpenStatus is the self-hostable option DevHelm points at), not a tiebreaker between these two.

Two buying decisions, not one​

The TODO item that prompted this post frames it exactly right: "who pages the platform team" and "what tenants see during an outage" are two different decisions, and the tools score differently on each.

Paging the platform team rewards integration breadth and alerting ergonomics. Kuma's 95+ notification providers, maintenance windows, and certificate-expiry thresholds are purpose-built for this. If your on-call rotation already lives in PagerDuty or Opsgenie with escalation policies tuned over years, Kuma plugs into that world with less friction. Gatus covers the major providers, but the long tail of niche integrations is thinner.

What tenants see during an outage rewards a status page that is always reachable, always current, and cheap to keep accurate. Kuma's multi-page status pages with custom domains look better out of the box. But Gatus wins on the accuracy half of that equation for a GitOps team: a status page whose underlying checks are version-controlled is a status page you can trust to reflect what you actually monitor, because the check definitions went through the same review as the services they watch. A beautiful page fed by hand-clicked monitors that nobody audits is a liability wearing good design.

For a self-hosted PaaS fleet, the pragmatic answer is often Gatus for the checks with Kuma's status-page polish acknowledged but not decisive — unless your alerting surface genuinely needs providers only Kuma ships. Either way, keep the two decisions separate in the evaluation doc: score paging and public status independently instead of letting one great demo carry both.

The decision guide​

• Solo dev or small team, first status page: Uptime Kuma. Lowest friction from zero to monitored, and the UI means no YAML learning curve for whoever is on call.
• GitOps fleet, config-as-code everywhere: Gatus. Monitors in Git, reviewed like manifests, with a dashboard good enough for tenants.
• Complex paging (many providers, escalation policies): Uptime Kuma, for the 95+ integrations and maintenance windows.
• Hundreds of checks on a tiny box: Gatus. Single binary, ~50 MB RAM, no database to back up.
• Need metrics, traces, or SLO dashboards: Neither — that is Prometheus/Grafana (or SigNoz) territory, paired with one of these for endpoint checks.

Whichever you pick, the meta-lesson from the June 2026 comparisons holds: self-hosting monitoring is about owning your incident story end to end. The tool that fits your change-control workflow will get updated; the one that fights it will quietly go stale, and stale monitors are worse than none because they teach the team that green means nothing.

Bex.co is the open-source, AI-native Render alternative — push a git repo, get a running HTTPS service on machines you own. Monitoring-as-code fits the same philosophy: if your platform state lives in Git, your uptime checks should too.