Usar a interface de monitoramento de jobs do Dataflow
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Ao executar o pipeline usando o Dataflow, é possível visualizar esse job e qualquer outro com a interface de monitoramento do Dataflow. A interface de monitoramento permite visualizar e interagir com suas tarefas do Dataflow.
É possível acessar a interface de monitoramento do Dataflow no
Google Cloud console.
As tarefas que você pode realizar usando a interface de monitoramento incluem o seguinte:
Confira uma lista de jobs em execução, concluídos e com falha.
Ver uma representação gráfica dos estágios de um job e o progresso de cada um deles
Veja gráficos de métricas de job, como atualização de dados, utilização de recursos e solicitações de E/S.
Monitore o custo estimado de um job.
Ver registros de pipeline.
Identifique quais etapas podem causar atraso no pipeline.
Identifique as causas da latência nas suas fontes e receptores.
Entender os erros do pipeline.
Componentes da interface de monitoramento
A interface de monitoramento contém os seguintes visualizadores e gráficos:
Uma lista de todos os jobs do Dataflow em execução e todos os jobs executados nos últimos 30 dias, com status, região, tempo decorrido e outras informações.
Uma representação gráfica de um pipeline. O gráfico do job também fornece um resumo e um registro do job, além de informações sobre cada etapa do pipeline.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-09-04 UTC."],[[["\u003cp\u003eThe Dataflow monitoring interface allows users to view and interact with their Dataflow jobs directly from the Google Cloud console.\u003c/p\u003e\n"],["\u003cp\u003eUsers can track running, completed, and failed jobs, alongside a graphical representation of a job's stages and its progress.\u003c/p\u003e\n"],["\u003cp\u003eThe interface provides job metrics like data freshness, resource utilization, and estimated costs, as well as pipeline logs and potential error sources.\u003c/p\u003e\n"],["\u003cp\u003eThe monitoring interface includes a project dashboard, job list, job graph, execution details, and cost estimation, and also provides recommendations for job performance and error troubleshooting.\u003c/p\u003e\n"],["\u003cp\u003eThe monitoring interface can show data samples of each step of a pipeline.\u003c/p\u003e\n"]]],[],null,["# Use the Dataflow job monitoring interface\n\nWhen you run your pipeline by using Dataflow,\nyou can view that job and any others by using the Dataflow monitoring\ninterface. The monitoring interface lets you see and\ninteract with your Dataflow jobs.\n\nYou can access the Dataflow monitoring interface in the\n[Google Cloud console](https://console.cloud.google.com/).\n\nTasks that you can perform by using the monitoring interface include the\nfollowing:\n\n- See a list of running, completed, and failed jobs.\n- View a graphical representation of a job's stages and the progress of each stage\n- View graphs of job metrics, such as data freshness, resource utilization, and I/O requests.\n- Monitor the estimated cost of a job.\n- View pipeline logs.\n- Identify which steps might cause pipeline lag.\n- Identify causes of latency in your sources and sinks.\n- Understand pipeline errors.\n\n| **Note:** Sometimes job data is intermittently unavailable. When data is missing, gaps appear in the job monitoring charts.\n\nMonitoring interface components\n-------------------------------\n\nThe monitoring interface contains the following visualizers and charts:\n\n[Project monitoring dashboard](/dataflow/docs/guides/project-monitoring)\n: A dashboard that monitors your Dataflow jobs at the project\n level.\n\n[Jobs list](/dataflow/docs/guides/jobs-list)\n: A list of all running Dataflow jobs and all jobs run within the\n last 30 days, along with their status, region, elapsed time, and other\n information.\n\n[Job graph](/dataflow/docs/guides/job-graph)\n: A graphical representation of a pipeline. The job graph also provides a job\n summary, a job log, and information about each step in the pipeline.\n\n[Execution details](/dataflow/docs/concepts/execution-details)\n: Shows the execution stages of a job, data freshness for streaming jobs, and\n worker progress for batch jobs.\n\n[Job metrics](/dataflow/docs/guides/using-monitoring-intf)\n: Charts that display metrics over the duration of a job.\n\n[Estimated cost](/dataflow/docs/guides/estimated-cost)\n: The estimated cost of your Dataflow job, based on resource\n usage metrics.\n\n[Recommendations](/dataflow/docs/guides/recommendations)\n: Recommendations for improving job performance, reducing cost, and\n troubleshooting errors.\n\n[Autoscaling](/dataflow/docs/guides/autoscaling-metrics)\n: A set of charts that help you to understand the autoscaling behavior of\n streaming jobs.\n\n[Pipeline logs](/dataflow/docs/guides/logging)\n: Logs emitted by your pipeline and by the Dataflow service.\n\n[Data sampling](/dataflow/docs/guides/data-sampling)\n: A tool that lets you observe sampled data at each step of a pipeline.\n\nWhat's next\n-----------\n\n- Use [Cloud Monitoring](/dataflow/docs/guides/using-cloud-monitoring) to create alerts and view Dataflow metrics, including custom metrics\n- Learn more about [building production-ready data pipelines](/architecture/building-production-ready-data-pipelines-using-dataflow-monitoring)\n- Learn how to [troubleshoot your pipeline](/dataflow/docs/guides/troubleshooting-your-pipeline?)"]]
