Apache Flink’s dashboard is the Web UI bundled with Flink’s operational tooling—not a separate product you must install. It lets operators inspect running and recently completed jobs, view task and operator metrics, investigate failures, submit executions, and cancel jobs. The JobManager serves the dashboard and monitoring API together; the documented default REST port is 8081, but deployments can change it with rest.port.
What the Flink dashboard does
Flink processes bounded data sets and unbounded streams with stateful computations, making it suitable for continuous analytics and streaming pipelines. The project describes its Web UI this way: “Flink features a web UI to inspect, monitor, and debug running applications.”
The interface is primarily an operational view of a Flink cluster. It is useful for checking whether a job is running, identifying slow or failed operators, examining task-level statistics, and taking immediate control actions. Programmatic workflows can use the same monitoring service through Flink’s REST API.
How the dashboard and monitoring API fit together
The JobManager-hosted monitoring API supplies status, statistics, metadata, and collected metrics for running and recently completed jobs. Flink’s own Web UI consumes this API, and custom monitoring tools can consume it as well. The web server and API are documented as part of the same Flink service.
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Connect to the deployed Web UI
- Identify the JobManager address exposed by your deployment, whether it runs on standalone infrastructure, Kubernetes, YARN, or another supported environment.
- Open the JobManager host and configured REST port in a browser. The default documented port is
8081; verify the actual value in the release-specific configuration becauserest.portcan override it. - Confirm that the page lists the expected cluster and jobs before diagnosing application behavior.
Do not assume that an unreachable page means the job itself is unhealthy. Network policy, ingress settings, authentication, TLS termination, or a non-default REST port can prevent access even while task managers continue processing.
How to monitor a Flink job in the dashboard
Check job state and topology
Start with the jobs view and open the application you need to inspect. Review its current state, start time, parallelism, vertices, and execution graph. A failed or canceled vertex narrows investigation to a specific operator or task rather than the entire pipeline.
Inspect task and operator behavior
Open the job’s metrics area to examine measurements collected for tasks and operators. Numeric measurements can be plotted with time on the horizontal axis and the metric value on the vertical axis. The Apache Flink 2.1 metrics documentation describes graphs refreshing every 10 seconds, but that page labels itself out of date; treat the interval as release-specific rather than a universal promise.
Use metrics to answer operational questions
- Progress: Are records, bytes, or other application counters advancing?
- Throughput: Is an operator keeping up with its input, or is work accumulating upstream?
- Backpressure and imbalance: Is one subtask behaving differently from its peers?
- Reliability: Are failures, restarts, or checkpoint-related indicators changing?
- Resource behavior: Do task-level measurements point to uneven workload or a constrained component?
A graph is evidence about the metric that was collected, not a complete health assessment. Interpret it alongside job state, logs, checkpoint and restart information, deployment events, and the application’s own counters.
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The Web UI can submit executions and cancel them. For automation, Flink’s REST API supports programmatic submission and operational actions such as taking savepoints, and it returns job metadata and collected metrics.
Choose the control path
| Need | Best path | Reason |
|---|---|---|
| Quick inspection or an emergency cancellation | Web UI | Interactive view with immediate status and topology context |
| Repeatable deployment or scheduled operation | REST API or deployment tooling | Scriptable and suitable for change control |
| Savepoint-driven maintenance | REST API and your deployment process | Allows the action to be coordinated with automation and recovery steps |
Protect the JobManager endpoint as an administrative interface. Apply the authentication, authorization, network controls, and TLS settings required by your environment before exposing it beyond trusted operators.
Where Flink metrics come from
Flink’s metrics system contains built-in system measurements and user-defined metrics. Reporters export those measurements to external monitoring systems. The operations documentation lists reporter options including JMX, Ganglia, Graphite, Prometheus, StatsD, Datadog, and Slf4j; the available reporters and configuration details can vary by Flink release and deployment, so use the documentation matching the version you run.
Built-in versus user-defined metrics
- Built-in metrics describe framework, task, operator, and cluster behavior supplied by Flink.
- User-defined metrics are application measurements added by your operators or functions to expose business progress or domain-specific conditions.
The dashboard can only display measurements that Flink collected and exposed at the requested scope. A metric that was never registered, was filtered out, or is not supported by the selected reporter cannot appear merely because a dashboard widget expects it.
Why Flink dashboard metrics are missing
“No data” is not synonymous with “the job is broken.” An external dashboard may be querying a scope or reporter that has no backing data.
Check the metric scope
| Scope | What it represents | Typical check |
|---|---|---|
| JobManager | Cluster-control and JobManager measurements | Verify the JobManager reporter and endpoint are producing data |
| TaskManager | Worker-level measurements | Confirm TaskManager reporters are configured and connected |
| Job or operator | Measurements associated with a specific execution and its operators | Check that the selected job, vertex, subtask, and metric name match the running deployment |
SkyWalking’s Flink dashboard documentation explicitly notes that widgets are empty until data is reported at the corresponding JobManager, TaskManager, or job level. A widget without backing data is shown as “no data.”
Use this troubleshooting sequence
- Verify that the job is running and that you selected the correct cluster and job identifiers.
- Confirm the metric is numeric if you expect it to be plotted in Flink’s Metrics tab.
- Check the reporter configuration on the component that owns the metric: JobManager, TaskManager, or job/operator.
- Confirm that the external system accepts the reporter or telemetry path enabled in your deployment.
- Compare the queried metric name and scope with the labels emitted by the deployed Flink version.
- Inspect JobManager and TaskManager logs for reporter startup, connection, authentication, or serialization errors.
- Allow for the reporter’s collection and dashboard refresh interval before concluding that data is absent.
If only one scope is empty, investigate that scope’s reporter and permissions rather than treating the entire Flink cluster as unobservable.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When an external dashboard is worth adding
Flink’s built-in UI is the fastest way to inspect an individual job and perform immediate actions. An external observability platform becomes useful when you need organization-wide retention, alerts, shared dashboards, or correlation with infrastructure and application telemetry.
Compare platforms on operational fit
- Metric coverage: Can it ingest and display the JobManager, TaskManager, job, and operator measurements you actually need?
- Telemetry path: Does it support the reporter or collection pipeline already available in your deployment?
- Workflow support: Can it cover debugging, throughput and progress checks, checkpoint and restart visibility, alerting, and historical retention?
- Compatibility: Does its integration match your Flink release and deployment architecture?
Do not judge a platform by a blank widget alone. First establish that the relevant metric is emitted at the scope being queried and that the external collector can receive it.
Version and deployment cautions
Flink’s labels, REST behavior, reporter availability, and UI details can change between releases and deployment modes. The 10-second graph refresh description comes from release 2.1 documentation that is marked out of date, so it should not be copied into a production runbook as a current guarantee. Check the documentation for the exact Flink release, distribution, and cluster configuration you operate before relying on a port, endpoint, reporter, metric name, or refresh cadence.
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