Understanding Linked Services in Azure for Data Integration

Linked services in Azure are a crucial part of data integration, allowing you to connect to various data sources and sinks.

A linked service is essentially a connection to a data source or sink, such as a database, storage account, or API. This connection is used to read from or write to the data source.

In Azure, linked services are used to connect to various data sources, including Azure Blob Storage, Azure SQL Database, and Azure Data Lake Storage. This enables you to read data from and write data to these sources.

By using linked services, you can simplify your data integration workflows and reduce the complexity of connecting to multiple data sources.

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Linked Services are a crucial component of Azure Data Factory, defining the connection information needed for Data Factory to connect to external data sources.

They act as a bridge, allowing seamless integration with various data stores and compute services.

Discover more: What Is Azure Data Factory

By leveraging Linked Services, you can configure and manage connections to multiple data sources, simplifying the process of data integration.

Linked Services support a wide range of data stores and compute services, making it easier to integrate different systems and applications.

They enable secure and efficient data movement, which is essential for maintaining data consistency and reliability across different platforms.

Here are the key features of Linked Services:

Linked services in Azure are a crucial component of Azure Data Factory, enabling seamless data integration and transformation.

Azure Storage Linked Service is a type of linked service that connects to Azure Blob Storage, Azure Data Lake Storage, and Azure Queue Storage for efficient data storage and retrieval.

Azure SQL Database Linked Service facilitates connections to Azure SQL Database and Azure SQL Data Warehouse, providing robust data management and querying capabilities.

The HTTP Linked Service allows integration with web services and REST APIs, making it possible to pull data from various online sources and services.

A different take: Sql Azure Linked Server

Here are the different types of linked services available in Azure Data Factory:

By leveraging these connections, businesses can streamline their data workflows, ensure data consistency, and enhance overall operational efficiency.

Creating Linked Services in Azure Data Factory involves setting up connections to various data stores and computing services. You can do this by navigating to the Azure Data Factory portal and selecting the "Manage" tab.

To create a new linked service, click on "New" under the "Connections" section and choose the type of data store or compute service you wish to connect to. This could be Azure Blob Storage, Azure SQL Database, or an external service like ApiX-Drive.

You'll need to provide the necessary connection details, such as server name, database name, and authentication method, depending on the service you're connecting to. Make sure to test the connection to ensure the details are correct.

Here are the key properties you'll need to specify when creating a linked service:

Note that some linked services, like Azure SQL Database, support System Assigned Managed Identity, which allows you to log in using the user credentials of ADF itself, eliminating the need to specify users or passwords.

Creating Linked Services involves defining the parameters that will be used to connect to external data sources or services.

The name of the Synapse Linked Service is a required parameter, which cannot be changed without creating a new Linked Service.

You'll also need to specify the Synapse Workspace ID, which is another required parameter. This ID is used to associate the Linked Service with the Synapse Workspace.

The type of data store being connected to Synapse is also a required parameter, and it determines the properties that will be used to connect to the data store.

Here are the required parameters for creating a Synapse Linked Service:

In addition to these required parameters, you can also specify additional properties, annotations, description, integration runtime, and parameters.

Managing linked services in Azure Data Factory is crucial for seamless data integration across diverse platforms. You need to configure and maintain connections to various data sources and destinations.

Proper authentication and authorization are essential to ensure each connection is secure. This involves setting up credentials, connection strings, and other necessary parameters.

Regular monitoring and updating of these connections are crucial to maintain data flow integrity. This helps prevent issues and ensures data is flowing correctly.

To simplify the process, you can utilize tools like ApiX-Drive. This service offers a user-friendly interface and robust features that streamline the integration of various data sources.

Here are the key steps to manage linked services effectively:

Linked Services in Azure are a connection configuration to external data sources or services, including endpoint URLs, connection strings, and authentication credentials. They support various data stores and platforms, such as databases, file systems, and more.

You can create a Linked Service for each type of source system, such as a Storage Account, SQL Server, or Oracle, via the GUI. The JSON code for the Linked Service will look like this:

```

{

"name": "StorageAccountLinkedService",

"properties": {

"type": "AzureBlobStorage",

"typeProperties": {

"connectionString": {

"type": "SecureString",

"value": "DefaultEndpointsProtocol=https;AccountName=myaccount;AccountKey=mykey;"

}

}

}

}

```

You can also use parameters in Linked Services, which can be retrieved from the Key Vault.

Broaden your view: Azure Service Bus Connection String

HDInsight is a fully managed cloud service that allows you to process and analyze large datasets using the Hortonworks Data Platform. You can create an on-demand HDInsight cluster, which is automatically created and removed by the service after a job is submitted to process data.

In an on-demand HDInsight cluster, the computing environment is fully managed by the service, and the cluster is created in the same region as the storage account associated with the cluster. This storage account must be a general-purpose standard Azure Storage account.

You can use a Script Action with the Azure HDInsight on-demand linked service, but provisioning an Azure HDInsight cluster on demand typically takes 20 minutes or more.

To create an Azure HDInsight linked service, you need to specify the type as HDInsight, the URI of the HDInsight cluster, the username, and the password. You also need to specify the name of the Azure Storage linked service that refers to the Azure blob storage used by the HDInsight cluster.

Discover more: Azure Data Factory Linked Service

Here are the properties required to create an Azure HDInsight linked service:

Databricks is a powerful tool for running workloads, and you can create an Azure Databricks linked service to register your Databricks workspace.

You can use a Databricks linked service to run notebook, jar, and python workloads.

This type of linked service supports Instance pools for scalable resources.

It also supports System-assigned managed identity authentication for secure access.

Azure SQL Database is a powerful linked service that allows you to invoke stored procedures from your pipeline.

You can create an Azure SQL linked service and use it with the Stored Procedure Activity to invoke a stored procedure.

This linked service is detailed in the Azure SQL Connector article, which is a great resource to check out for more information.

With Azure SQL Database, you can easily connect to your SQL Server and execute stored procedures directly from your pipeline.

For your interest: Azure Managed Database

Synapse Analytics offers two types of linked services: Azure Synapse Analytics linked service and Azure Synapse Analytics (Artifacts) linked service. The former is used with the Stored Procedure Activity to invoke a stored procedure from a pipeline.

Curious to learn more? Check out: Azure Synapse Link for Dataverse

You can create an Azure Synapse Analytics (Artifacts) linked service and use it with the Synapse Notebook Activity and Synapse Spark job definition Activity. This type of linked service requires several properties, including name, description, annotations, type, endpoint, authentication, workspaceResourceId, and connectVia.

Here are the required properties for an Azure Synapse Analytics (Artifacts) linked service:

Synapse Analytics can also be configured in Terraform with the resource name azurerm_synapse_linked_service.

Azure Synapse offers a range of related resources to help you manage and secure your linked services.

Azure Synapse Firewall Rule is a key resource for controlling access to your linked services, allowing you to specify which IP addresses can connect to your resources.

Azure Synapse Integration Runtime Azure and Azure Synapse Integration Runtime Self Hosted are two options for running your linked services, with Azure Synapse Integration Runtime Azure providing a fully managed service and Azure Synapse Integration Runtime Self Hosted allowing you to run your services on your own infrastructure.

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Azure Synapse Managed Private Endpoint provides a secure way to connect to your linked services, using a private IP address to reduce the risk of data breaches.

Azure Synapse Private Link Hub is a centralized service for managing private links to your linked services, making it easier to control access and monitor usage.

Azure Synapse Role Assignment is an essential resource for managing access to your linked services, allowing you to assign roles and permissions to users and groups.

Azure Synapse Spark Pool and Azure Synapse SQL Pool are two types of pools that can be used to run your linked services, with Spark Pool optimized for big data analytics and SQL Pool optimized for relational database workloads.

Azure Synapse SQL Pool Extended Auditing Policy and Azure Synapse SQL Pool Security Alert Policy are two resources for monitoring and securing your SQL Pool, with Extended Auditing Policy providing detailed auditing and Security Alert Policy providing real-time security alerts.

Here are the related resources listed: