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Merge pull request #262160 from v-thepet/filelist
PostgreSQL term pass - a few missing
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articles/postgresql/flexible-server/concepts-query-store-scenarios.md

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@@ -43,7 +43,7 @@ Use Query Store to compare workload performance before and after an application
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- Modifying the amount of resources granted to the server.
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- Changing any of the server parameters that affect the behavior of the server.
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- Creating missing indexes on tables referenced by expensive queries.
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- Migrating from Single Server to Flexible Server.
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- Migrating from Azure Database for PostgreSQL single server to Azure Database for PostgreSQL flexible server.
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In any of these scenarios, apply the following workflow:
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1. Run your workload with Query Store before the planned change, to generate a performance baseline.
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## Next step
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> [!div class="nextstepaction"]
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> [best practices for using Query Store](concepts-query-store-best-practices.md)
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> [Best practices for using Query Store](concepts-query-store-best-practices.md)

articles/postgresql/flexible-server/generative-ai-azure-openai.md

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INSERT INTO conference_sessions
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(title,session_abstract,duration_minutes,publish_date)
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VALUES
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('Gen AI with Azure Database for PostgreSQL'
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('Gen AI with Azure Database for PostgreSQL flexible server'
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,'Learn about building intelligent applications with azure_ai extension and pg_vector'
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, 60, current_timestamp)
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,('Deep Dive: PostgreSQL database storage engine internals'

articles/postgresql/flexible-server/howto-connect-to-data-factory-private-endpoint.md

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Choose the type that best serves your data integration capabilities and network environment requirements.
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Azure Database for PostgreSQL flexible server provides for Private Link connectivity in preview. For more information, see [this article](../flexible-server/concepts-networking-private-link.md).
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## Prerequisites
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- An Azure Database for PostgreSQL flexible server instance that's [privately networked via Azure Private Link](../flexible-server/concepts-networking-private-link.md)
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"groupId": "postgresqlServer"
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}'
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```
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> [!NOTE]
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> An alternative command to create a private endpoint in Data Factory by using the Azure CLI is [az datafactory managed-private-endpoint create](/cli/azure/datafactory/managed-private-endpoint).
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## Add a networked server data source in Data Factory
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After you provision and approve a private endpoint, you can create a connection to Azure Database for PostgreSQL flexible server by using a Data Factory connector.
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When provisioning succeeds and the endpoint is approved, you can finally create a connection to PGFlex using the Azure Database for PostgreSQL flexible server Data Factory connector.
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In the previous steps, when you selected the server for which you created the private endpoint, the private endpoint was also selected automatically.
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In the preceding steps, when you selected the server for which you created the private endpoint, the private endpoint was also selected automatically.
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1. Select a database, enter a username and password, and select **SSL** as the encryption method. The following screenshot shows an example.
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:::image type="content" source="./media/howto-connect-to-data-factory-private-endpoint/data-factory-data-source-connection.png" alt-text="Example screenshot of connection properties." lightbox="./media/howto-connect-to-data-factory-private-endpoint/data-factory-data-source-connection.png":::
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1. Select **Test connection**. A "Connection Successful" message should appear.
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1. Select **Test connection**. A **Connection successful** message should appear next to the **Test connection** button.
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## Next step
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