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Nesta página, você vai encontrar as práticas recomendadas para usar o Datastream. Isso inclui práticas recomendadas gerais ao usar o Datastream.
Mudar o banco de dados de origem de um fluxo
Em alguns casos, talvez seja necessário mudar o banco de dados de origem de um stream. Por exemplo, talvez seja necessário modificar o stream para replicar de uma réplica em vez da instância de banco de dados principal.
O painel do Datastream contém muitas informações. Essas informações podem ser úteis para fins de depuração. Mais informações podem ser encontradas nos registros, que estão disponíveis no Cloud Logging.
Alertas do Datastream
Não há um alerta padrão configurado para o Datastream. Por exemplo, é possível criar uma política de alertas para a métrica Atualização de dados clicando no link Criar política de alertas na guia Visão geral. Para as métricas restantes, siga estas etapas:
No console Google Cloud , acesse a página notificationsAlertas:
Recomendamos criar alertas para as seguintes métricas do Datastream:
Atualização de dados
Transmitir contagem de eventos sem suporte
Latências totais do stream
Um alerta em qualquer uma dessas métricas pode indicar um problema com o stream ou com o banco de dados de origem.
Quantas tabelas uma única transmissão pode processar?
Recomendamos que um único fluxo inclua até 10.000 tabelas. Não há limite para o tamanho das tabelas. Se você precisar criar um stream com mais tabelas, ele poderá entrar em um estado de erro. Para evitar isso, divida a fonte em vários fluxos.
[[["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\u003eThis page covers best practices for using Datastream, including modifying a stream's source database and creating custom alerts.\u003c/p\u003e\n"],["\u003cp\u003eTo change a stream's source database, create a connection profile for the replica instance, start a new stream with historical backfill disabled, and then pause the original stream.\u003c/p\u003e\n"],["\u003cp\u003eDatastream offers a dashboard for debugging, and custom alerting policies can be set up for key metrics like data freshness, stream unsupported event count, and stream total latencies.\u003c/p\u003e\n"],["\u003cp\u003eFor optimal performance, it is recommended that a single Datastream stream includes no more than 10,000 tables, with consideration for the impact on the source database if multiple streams are used.\u003c/p\u003e\n"]]],[],null,["# General best practices when using Datastream\n\nIn this page, you'll find best practices for using Datastream. These include general best practices when using Datastream.\n\nChange a stream's source database\n---------------------------------\n\nIn some cases, you may have to change the source database of a stream. For example, you may have to modify the stream to replicate from a replica instead of from the primary database instance.\n\n1. [Create a connection profile](/datastream/docs/create-connection-profiles) for the replica instance.\n2. [Create a stream](/datastream/docs/create-a-stream), using the connection profile for the replica that you created and the existing connection profile for the destination.\n3. [Start the stream](/datastream/docs/run-a-stream#startastream) with historical backfill disabled. When the stream is started, it will bring only the data from the binary logs.\n4. Optional. After the stream is running, [modify it](/datastream/docs/modify-a-stream) to enable automatic backfill.\n5. [Pause the stream](/datastream/docs/run-a-stream#pauseastream) that's reading from the primary instance.\n6. Optional. [Delete the stream](/datastream/docs/delete-a-stream) that was streaming data from the primary instance.\n7. Optional. [Delete the connection profile](/datastream/docs/delete-a-connection-profile) for the primary instance.\n\nAlert and monitor in Datastream\n-------------------------------\n\nThe Datastream dashboard contains a great deal of information. This information can be helpful for debugging purposes. Additional information can be found in the logs, which are available in Cloud Logging.\n| **Tip:** Use [Google Cloud Monitoring](/monitoring) to create a custom dashboard to suit your business needs.\n\n### Datastream alerts\n\nThere's no default alert set up for Datastream. For example, you can create an alerting policy for the **Data freshness** metric by clicking the *Create alerting policy* link in the **Overview** tab. For the remaining metrics, follow these steps:\n\n1. In the Google Cloud console, go to the *notifications* **Alerting** page:\n\n [Go to **Alerting**](https://console.cloud.google.com/monitoring/alerting)\n2. Click **Create policy**.\n\n3. Click the **Select a metric** drop-down.\n\n4. In the filter field, enter `Datastream`.\n\n5. Optional: You might need to disable the **Active** filter to view all available metrics.\n\n6. Search for the metric that you want to monitor under **Datastream Stream**.\n\n7. Click **Apply**.\n\n8. Optional: Enter the required details in the **Add filters** and **Transform data** sections. Click **Next**.\n\n9. Enter the required information in the **Configure alert trigger** section. Click **Next**.\n\n10. Configure your notifications in the **Configure notifications and finalize alert** section.\n\n11. Review your alert and click **Create policy** when ready.\n\n For detailed information about how to complete each of these steps, see\n [Create alerting policy](/monitoring/alerts/using-alerting-ui#create-policy).\n\nWe recommend creating alerts for the following Datastream[metrics](/datastream/docs/monitor-a-stream#monitorstreams):\n\n- Data freshness\n- Stream unsupported event count\n- Stream total latencies\n\nAn alert on any of these metrics can indicate a problem with either the stream or the source database.\n\nHow many tables can a single stream handle?\n-------------------------------------------\n\nWe recommend that a single stream includes up to 10,000 tables. There's no limit to the size of the tables. If you need to create a stream with more tables, then the stream might enter an error state. To avoid this, consider splitting the source into multiple streams.\n| Keep in mind the impact on the source database. Each stream will have its own limit on the number of connections and simultaneous tasks, so combining multiple streams could overwhelm the database."]]
