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Choose Uptime Kuma for straightforward uptime checks, built-in notifications, and shareable status pages. Choose Prometheus for labeled time-series metrics, PromQL analysis, exporters, and sophisticated alert workflows. They solve related but different problems, so many teams use both: Kuma watches whether services are reachable and communicates incidents, while Prometheus explains what the services and infrastructure are doing.
The practical choice depends on the question you need answered. “Is the website responding?” usually points to Kuma. “Why did latency rise, which service is failing, and how often does this happen?” points to Prometheus. The sections below compare their monitoring models, alerting, setup, operating costs, and a combined architecture.
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Uptime Kuma vs Prometheus at a glance
| Need | Better starting point | Why |
|---|---|---|
| A few websites, APIs, ports, or containers | Uptime Kuma | It provides monitor types, notifications, and a web interface in one application. |
| A public or customer-facing uptime page | Uptime Kuma | Multiple status pages are a documented feature. |
| Host, application, and service metrics | Prometheus | It stores labeled time series and supports PromQL, exporters, and service discovery. |
| Complex alert routing, grouping, silencing, and inhibition | Prometheus with Alertmanager | Alertmanager is designed for those notification-management functions. |
| HTTP, DNS, TCP, ICMP, or gRPC probes in a metrics stack | Prometheus with Blackbox Exporter | Blackbox Exporter supplies those probes and exposes probe metrics. |
| Simple uptime checks plus deep telemetry | Uptime Kuma and Prometheus | The tools are complementary, and Kuma can expose metrics for collection and visualization. |
Neither tool is a universal replacement for the other. Kuma is an integrated availability monitor. Prometheus is a metrics platform whose endpoint probing normally requires an additional component, and whose alert delivery normally uses Alertmanager.
What Uptime Kuma monitors
Uptime Kuma describes itself as an easy-to-use, self-hosted monitoring tool. Its monitor list is centered on whether a target is reachable and whether a simple condition is true. Supported checks include HTTP(S), TCP, HTTP(S) keyword matching, HTTP(S) JSON queries, WebSocket, ping, DNS-record, push, Steam game-server, and Docker-container monitoring.
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Checks that answer an availability question
- HTTP(S): verifies that a web endpoint responds.
- TCP: checks whether a service accepts a connection on a port.
- Keyword and JSON checks: go beyond a successful connection by looking for expected content or a value in a JSON response.
- WebSocket: tests a WebSocket endpoint rather than an ordinary page request.
- Ping and DNS-record: check network reachability or DNS behavior.
- Push: lets an external job report that it completed.
- Steam game-server and Docker-container checks: cover specialized service and container scenarios.
The README documents monitoring intervals as short as 20 seconds. That figure describes the project’s documented interval capability, not a guarantee that every deployment, network, or target will respond reliably at that cadence.
Notifications, status pages, and operator features
Notifications are integrated into Kuma. The project lists Telegram, Discord, Gotify, Slack, Pushover, SMTP email, and more than 90 notification services. You can associate notifications with individual monitors instead of building a separate alert-delivery pipeline.
Kuma also lists multiple status pages, ping charts, certificate information, proxy support, and two-factor authentication. Multiple status pages are especially useful when different customers, projects, or internal teams should see different subsets of services. Certificate information helps surface impending TLS problems before a certificate expires, while proxy support can fit deployments that already route outbound traffic through a proxy.
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Kuma is self-hosted. Its published Docker and Docker Compose instructions use a persistent data volume and port 3001. A practical deployment therefore needs an always-on host, durable storage for the application data, a protected path to the web interface, and a plan for updates and backups.
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The basic rollout is straightforward:
- Choose a host that is independent from the services you intend to monitor whenever possible.
- Deploy Kuma with the project’s Docker or Docker Compose instructions, retaining its data volume and publishing the documented port 3001 as appropriate for your network.
- Complete the initial web setup and enable two-factor authentication for administrator accounts.
- Create one monitor per endpoint, port, DNS record, container, or push job. Set the check interval and any keyword or JSON condition that represents a healthy response.
- Configure at least one notification channel and trigger a controlled test so you know the message reaches the right people.
- Create a status page only for information you are comfortable exposing. Keep administrative access separate from the public page.
- Back up the persistent data and document how to restore the instance before treating it as an important incident system.
That workflow is approachable because one application supplies the checks, history, notifications, and status-page interface. It does not remove the operational responsibility of securing the host, keeping it available, and checking that notifications still work.
What Prometheus monitors
Prometheus is an open-source systems monitoring and alerting toolkit. Its core data model is numeric time series: each sample has a timestamp and can carry key/value labels. Prometheus collects those samples over HTTP, stores them locally, evaluates rules, and provides PromQL for querying and analysis.
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A metric can describe a quantity such as request duration, active connections, or query count. Labels add dimensions that let you ask focused questions, such as how a measurement differs by service, instance, route, or environment. PromQL then turns those stored samples into graphs, calculations, and alert expressions.
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This model is powerful when you need history and context rather than a binary result. A failed HTTP check tells you that a request did not meet its condition. A metrics system can show whether latency was gradually increasing, whether only one instance is affected, or whether traffic and resource usage changed at the same time—provided the relevant metrics are being collected.
The ecosystem around the server
Prometheus is a server in a broader ecosystem rather than an all-in-one status-page application. The official overview identifies exporters, Alertmanager, client libraries, and visualization consumers as separate or optional parts.
- Exporters expose metrics from systems that do not natively provide Prometheus-formatted endpoints.
- Service discovery helps Prometheus find changing targets in dynamic, service-oriented environments.
- Alerting rules evaluate PromQL expressions and create alerts when a condition is met.
- Alertmanager receives those alerts and handles silencing, inhibition, aggregation, and notification delivery.
- Visualization consumers turn the queryable data into dashboards and graphs.
This separation makes Prometheus adaptable, but it also means a first deployment involves more design choices than a single Kuma instance.
Black-box endpoint checks with Prometheus
Prometheus is primarily a numeric telemetry system. For external probing, the official Blackbox Exporter adds HTTP, HTTPS, DNS, TCP, ICMP, and gRPC probes. It exposes a probe_success result along with timing metrics for Prometheus to scrape.
That arrangement lets you query probe history alongside application and infrastructure metrics. It is not the same operating model as Kuma’s built-in monitor list: you run and configure an additional exporter, define the targets and probe modules, configure Prometheus to scrape it, and decide how alert rules and notifications should work.
The decisive difference: availability checks versus telemetry
The simplest way to choose is to write down the sentence your monitor must answer.
| Question | Uptime Kuma | Prometheus stack |
|---|---|---|
| Did an HTTPS endpoint respond? | Built-in HTTP(S) monitor. | Blackbox Exporter probe, then Prometheus collection. |
| Did the response contain the expected word or JSON value? | Built-in keyword or JSON-query monitor. | Possible only after building a suitable metric-producing check or exporter. |
| How long did requests take over time? | Provides ping charts and monitor history. | Stores numeric timing metrics for PromQL analysis and correlation. |
| How many active connections does each instance have? | Not its primary data model. | Natural fit for labeled application or exporter metrics. |
| Can I show selected services to customers? | Multiple status pages are built in. | Requires a dashboard or an additional status-page layer. |
| Can alerts be grouped, inhibited, or silenced by policy? | Uses its integrated notification configuration. | Alertmanager is designed for those routing and suppression functions. |
Kuma is usually the faster route from “I have an endpoint” to “I know when it is down.” Prometheus is usually the better route from “I have many measurements” to “I need to query, correlate, and alert on them.”
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Kuma’s integrated path
In Kuma, the monitor and notification configuration live in the same application. You select a monitor, define its failure condition, attach one or more notification services, and receive an outage or recovery message. This minimizes the number of moving parts for a small service portfolio.
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The trade-off is that the workflow is organized around monitors and their notification settings. If your organization needs elaborate escalation trees, cross-service deduplication, or policy-driven suppression, you may eventually want the separate alert-management model used by Prometheus.
Prometheus and Alertmanager’s separated path
Prometheus documentation describes alerting as two parts. Prometheus evaluates alerting rules and sends resulting alerts to Alertmanager. Alertmanager then handles silencing, inhibition, aggregation, and delivery to email, on-call systems, or chat platforms.
This separation is valuable when a single underlying incident would otherwise create dozens of messages. It also lets operators silence a known maintenance event, inhibit lower-priority alerts when a dependency is already down, and aggregate alerts by labels before sending them. The price is configuration and another service to operate, secure, back up, and monitor.
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- Use Kuma notifications when the main requirement is a prompt message for each monitored endpoint.
- Use Prometheus rules and Alertmanager when alert conditions depend on numeric thresholds, labels, aggregation, or suppression policy.
- Use both when an outage needs an immediate endpoint notification and the response team also needs metric context.
Status pages and communication outside the operations team
A status page is a communication product, not merely a graph. Kuma explicitly includes multiple status pages, making it suitable for publishing a selected view of service health to customers or other non-operators.
Prometheus’ official overview emphasizes metrics, alerting, graphing, and dashboard consumers; it does not describe a built-in public status-page product. A Prometheus deployment therefore normally adds a dashboard or another status-page layer when external communication is required.
Keep the audiences separate. A public page should expose only service-level state and planned-maintenance information. Internal Prometheus dashboards can contain host names, labels, error details, and other operational data that should not be public. If you use Kuma for both, create distinct status pages and protect the administrative interface.
Setup effort and operating responsibilities
When Kuma is the sensible first deployment
Kuma is a strong starting point for a homelab, a small collection of websites and APIs, or a team that wants a web UI without assembling a monitoring stack. The initial design work is mainly deciding what constitutes a healthy response, where the monitor should run, who receives notifications, and which services belong on each status page.
Do not place the only monitor on the same host, network, or power circuit as the service you care about if you need meaningful outage evidence. A host failure could otherwise make the monitor and the target disappear together. For internet-facing services, an independent monitoring location gives a more useful view of reachability from outside your primary environment.
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When Prometheus is worth the additional components
Prometheus earns its setup cost when you need metrics from hosts, applications, and services; historical analysis with labels; service discovery; or alert rules based on numeric behavior. Plan the components before deploying:
- Identify the metrics you need and the systems that expose them natively or through exporters.
- Deploy the Prometheus server and define how it discovers or reaches scrape targets.
- Set retention, access controls, backups, and an independent way to observe the monitoring host.
- Write alerting rules only for conditions that require action, and include labels that help identify the affected service.
- Deploy Alertmanager if you need delivery, grouping, silencing, or inhibition.
- Add a visualization consumer for operators who need graphs and dashboards.
- Add Blackbox Exporter when external HTTP, DNS, TCP, ICMP, or gRPC probing is part of the requirement.
Prometheus can be the right long-term foundation, but installing the server alone does not automatically provide public status pages, endpoint probes, or notification delivery.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Using Uptime Kuma and Prometheus together
A combined design assigns each tool the work it handles best. Kuma monitors externally visible endpoints, sends straightforward outage and recovery notifications, and publishes selected status pages. Prometheus collects application and infrastructure metrics, evaluates numeric rules, and provides the historical context needed for diagnosis.
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A practical division of responsibility
- Kuma: website and API reachability, keyword or JSON content checks, DNS and TCP checks, container checks, notification delivery, and public status communication.
- Prometheus: host and application measurements, exporter data, service discovery, PromQL queries, recording or alerting rules, and metric-based investigations.
- Alertmanager: grouping, silencing, inhibition, and policy-based notification routing for Prometheus alerts.
- Blackbox Exporter: probe execution when endpoint results must live in the Prometheus metric model.
Exporting Kuma’s own metrics
Kuma documentation describes scraping its Prometheus endpoint with an API key and placing those metrics into Grafana. That option lets Prometheus and a dashboard show Kuma’s monitor state without replacing Kuma’s monitor configuration or status-page features.
Protect the API key, restrict access to the metrics endpoint, and decide whether those internal monitor metrics belong in the same Prometheus environment as production telemetry. The integration is useful for detecting that the monitoring application itself has stopped reporting, but it does not eliminate the need for an independent location from which to observe either system.
Failure scenarios to test
- Stop a test endpoint and verify that Kuma detects the failure, sends a notification, updates the intended status page, and records recovery.
- Break a Prometheus scrape target and confirm that the resulting alert identifies the target rather than silently disappearing.
- Temporarily block the notification channel and verify that operators have another way to notice the failure.
- Restart each monitoring component separately to confirm that persistent data, rules, API credentials, and dashboards return as expected.
Decision guide by common setup
A personal server or homelab
Start with Kuma if your goal is to know whether a few services, ports, containers, or DNS records are working. Its web interface and integrated notifications keep the maintenance burden low. Add Prometheus later when you want host metrics, application measurements, or historical capacity analysis.
A small business with customer-facing services
Kuma is often the first useful layer because it combines endpoint checks, notifications, and status pages. Use an independent host and keep the public page free of sensitive details. Add Prometheus when incident response requires explanation rather than only detection.
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A multi-service application team
Prometheus is the better center for application and infrastructure telemetry. Use exporters and service discovery as the environment changes, and introduce Alertmanager when several alerts must be routed or suppressed intelligently. Add Kuma if customers need a polished availability page or if operators want a separate, simple endpoint monitor.
An internet-facing API with strict external testing
Use Kuma for a quick endpoint workflow, or use Prometheus with Blackbox Exporter when probe results must be analyzed alongside internal metrics. A hybrid arrangement can provide both an external availability signal and detailed application evidence.
A team with limited monitoring experience
Begin with one tool that answers the most urgent question instead of deploying every component at once. Kuma is generally the shorter path to a working notification. Prometheus becomes easier to justify after you can name the numeric questions—latency, request volume, active connections, or error behavior—that the team needs to answer regularly.
Pitfalls that make either tool less useful
Monitoring from the same failure domain
If the monitor shares a host, network path, or power source with the target, a local outage can remove both evidence and notification. Place monitoring outside the most important failure domain and test the path from the perspective that matters to users.
Defining “up” too narrowly or too broadly
An HTTP status code alone may not prove that an application is serving useful content. Kuma’s keyword and JSON-query checks can test a meaningful response. Conversely, a check that depends on a fragile optional string can create noise. Choose conditions that represent a real user or service contract.
Sending alerts without an operating procedure
A notification is only useful when someone knows what to do next. For each important alert, document the owner, the first diagnostic step, and the recovery or escalation path. Test recovery notifications as well as failure notifications.
Treating dashboards as status pages
Internal metric dashboards are designed for operators and can reveal sensitive implementation details. A customer-facing status page should be deliberately curated. Kuma’s multiple status-page feature helps separate those audiences; a Prometheus deployment needs an additional communication layer.
Deploying more components than the team can maintain
Prometheus, exporters, Alertmanager, visualization, and black-box probing form a capable stack, but every component needs updates, access control, backups, and failure testing. If the immediate requirement is a handful of uptime checks, that architecture may delay rather than improve the result.
A staged adoption plan
- Write the monitoring questions. Separate binary availability questions from numeric telemetry questions.
- Instrument the highest-value endpoints first. Include the response condition that actually represents health.
- Prove notification delivery. Test both failure and recovery, and record who owns each alert.
- Add metric collection where diagnosis needs it. Start with the services whose failures are hardest to explain.
- Introduce routing and suppression only when noise appears. Alertmanager is most valuable when grouping, silencing, or inhibition solves a real operational problem.
- Review the monitoring system itself. Back up data, protect credentials, update components, and verify that an outage of the monitoring host cannot hide the outage you care about.
Bottom-line choice
Pick Uptime Kuma when the outcome you need is clear, self-hosted uptime monitoring with a web interface, notifications, and status pages. Pick Prometheus when the outcome is a queryable store of labeled numeric telemetry, PromQL analysis, exporters, service discovery, and rule-based alerting. Add Blackbox Exporter to Prometheus for external protocol probes, and add Alertmanager when alert delivery needs grouping or policy.
For many real deployments, the strongest design is not an either-or decision. Kuma can remain the simple incident-facing and customer-facing layer while Prometheus supplies the evidence needed to understand causes, trends, and dependencies.
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