Open Source Uptime Monitoring: 5 Tools and the Catch

Open source uptime monitoring means running the checker yourself, on hardware you control, with the source available to read. The software in this category is genuinely good and costs nothing to license. The interesting question is not whether it works. It is where you put it, because that decision quietly determines what it can and cannot detect.

What open source uptime monitoring gives you

A container, a config file and a dashboard. You get as many checks as the box will carry, with no per-monitor pricing and full ownership of the history. You also get the ability to reach endpoints inside your private network, which is not a small thing and which no external service can offer.

You also get the parts nobody lists on a feature page. Upgrades, backups of the results database, TLS for the dashboard, and a plan for what happens when the host it runs on reboots. None of that is hard. All of it is yours.

Licence terms are worth two minutes of your time before you commit. Most of the projects below are permissively licensed. Even so, "open source" and "free to use commercially" are not the same sentence, and a few tools in the wider category ship a source-available licence instead. Read the file in the repository rather than the marketing page.

Five open source uptime monitoring tools worth your time

These five cover almost every real requirement between them. They are not interchangeable, and picking by star count is how teams end up with the wrong one.

Tool	Configured by	Best for	Notable gap
Uptime Kuma	Web interface	One team, many endpoints, fast setup	Single instance, single location
Gatus	YAML in git	Config as code, reviewable changes	Less friendly for non-engineers
OpenStatus	Web plus code	Status page first, checks second	Younger project, smaller ecosystem
OneUptime	Web interface	Incidents and on-call in one place	Heavy to run for uptime alone
Checkmate	Web interface	Servers and containers alongside sites	Narrower community than Kuma

Uptime Kuma

The default answer, and deservedly so. Its repository describes it as an easy-to-use self-hosted monitoring tool, and it sat at roughly 91,700 stars when we read it on 23 September 2026. Monitor types cover HTTP, TCP, HTTP keyword, HTTP JSON query, Websocket, Ping, DNS record, Push, Docker containers and Steam game servers.

docker run -d --restart=always -p 3001:3001 \
  -v uptime-kuma:/app/data --name uptime-kuma louislam/uptime-kuma:2

That is the whole install. We tested it on a small cloud instance and had four monitors and a Discord alert running in under fifteen minutes. The Push monitor type deserves particular credit, since it covers cron jobs and background workers that an outbound check can never see.

Gatus

Gatus describes itself as an automated developer-oriented status page with alerting and incident support. Everything lives in a YAML file, which means your checks go through code review and arrive by deployment rather than by someone clicking in a dashboard. If that appeals, it is the better choice. If a non-engineer needs to add a check on a Friday, it is the worse one.

OpenStatus and OneUptime

OpenStatus leads with the status page and treats checks as the thing that feeds it, which suits a public-facing product more than an internal estate. OneUptime goes much wider, bundling incident response and on-call alongside monitoring. Take OneUptime only if you want that whole surface, because running it purely for uptime checks is a lot of moving parts for a job four of them do.

Why does a self-hosted monitor miss outages?

Because it watches from one place, and one place cannot tell a broken service apart from a broken path to it. Your instance in Frankfurt sees a timeout. It has no way to know whether the site is down or the route between that host and the site is having a bad afternoon.

This is not a software flaw, and reading the source will not fix it. It is a property of where the checker runs. The usual mitigation is to run several instances in different networks, at which point you are operating a fleet and reconciling three dashboards that disagree.

The second problem is closer to home. A monitor on the same host, the same hypervisor or the same provider region as the thing it watches goes down with it. The rack loses power, the service stops, the monitor stops, and nobody is alerted. That correlation is the argument behind cross-region quorum confirmation, where two probes in different networks have to agree before anyone is paged.

There is a milder version of the same failure that catches more teams. The instance stays up but its outbound path degrades, so every check starts timing out at once. A dashboard full of red at 3am is almost always the network under the monitor rather than forty services failing at once. Confirming that costs an engineer an hour of their night, every time it happens.

Self hosted uptime monitoring can still reach a two-vantage-point setup. It just means two hosts, two configs, two upgrade cycles and a rule for what to do when they disagree.

What does it really cost to run?

Not much in money. A small instance runs any of these comfortably for a few dollars a month. The cost is in tasks, and tasks are the thing that quietly stops happening.

• Upgrades. A year-old container is a year of unpatched dependencies on a box holding your alerting credentials.
• Backups. The results database holds your entire history. A host failure without a backup takes all of it.

Two more are easier to forget precisely because they never announce themselves.

• Certificates. The dashboard needs TLS, so renewal is one more thing that can expire unnoticed.
• The watcher problem. Something has to notice when the monitor dies, and it cannot be the monitor.

That last point has a cheap answer worth adopting whatever you run. Have the instance send a periodic heartbeat to something outside it, and alert when the heartbeat stops. The pattern is described in heartbeat monitoring. The simplest version is a cron job on the same host that pings an inbound URL every five minutes.

*/5 * * * * curl -fsS -m 10 https://uptimeroom.com/api/heartbeat/<token> > /dev/null

When self-hosting is clearly right

Three cases, and in all of them we prefer running the open source tool.

Internal endpoints come first. If the target lives on a private network with no public route, an outside probe has nothing to connect to. Only something inside that network can reach it, and that is the end of the argument.

Second is data residency, where the results themselves cannot leave your infrastructure for regulatory reasons. Third is scale at the low end of value. A homelab with sixty services is a case where per-monitor pricing makes no sense and an outage costs nobody anything.

Add a fourth if you enjoy running it. That is a real reason and it does not need dressing up as a business case. Open source uptime monitoring has a large, active community behind it, and the learning is transferable in a way that clicking through a hosted dashboard is not.

Running both is usually the answer

The two approaches fail in different places, which is exactly why they pair well. A self-hosted instance watches the internal estate that nothing external can reach. An external service watches the handful of public endpoints that customers touch, from several networks at once, and it keeps reporting when your rack does not.

curl -X POST https://uptimeroom.com/api/v1/monitors \
  -H "Authorization: Bearer urm_live_..." \
  -H "Content-Type: application/json" \
  -d '{
    "name": "public checkout",
    "type": "http",
    "target": "https://example.com/checkout",
    "intervalSec": 60,
    "regions": ["london", "singapore"],
    "alertAfterCycles": 2
  }'

Two of the six probe regions available as of September 2026 are enough for confirmation on the public side. Ten monitors at a one-minute interval sit in the free tier, which covers the public surface of most products while the self-hosted instance handles everything behind the firewall. Egress addresses for firewall rules are published on the probe IPs page.

Common mistakes

Running the monitor next to the thing it monitors. Same host, same region or same provider means one failure takes out both. Put distance between them, or the first real outage is also the one nobody hears about.

Treating the dashboard as an alert. A page nobody has open at 2am is a record, not a notification. Wire up a channel that reaches a phone before you trust the setup.

Forgetting the upgrade path. Container images accumulate advisories. Put a calendar reminder against it, because an unpatched monitor holding your webhook URLs is a genuine security problem rather than a tidiness issue.

Comparing on star counts. Kuma has the most stars and is not automatically the right fit. Gatus wins when checks belong in git, and OneUptime wins when you want incidents in the same tool. Pick on the job.

Skipping the status page question. If you need to tell customers something during an outage, decide early where that page is hosted, because hosting it on the infrastructure that just failed defeats it. Worked examples are in status page examples.

Pick the tool that matches how your team makes changes. Put it somewhere that cannot fail alongside your product, and give it a heartbeat so its own death is noisy. Open source uptime monitoring is a strong answer for internal services and a partial one for the public endpoints customers hit. Confirmation from a second network is the piece that is genuinely hard to self-host, and the free plan covers that half.