Book Image

Azure Data Engineering Cookbook - Second Edition

By : Nagaraj Venkatesan, Ahmad Osama
Book Image

Azure Data Engineering Cookbook - Second Edition

By: Nagaraj Venkatesan, Ahmad Osama

Overview of this book

The famous quote 'Data is the new oil' seems more true every day as the key to most organizations' long-term success lies in extracting insights from raw data. One of the major challenges organizations face in leveraging value out of data is building performant data engineering pipelines for data visualization, ingestion, storage, and processing. This second edition of the immensely successful book by Ahmad Osama brings to you several recent enhancements in Azure data engineering and shares approximately 80 useful recipes covering common scenarios in building data engineering pipelines in Microsoft Azure. You’ll explore recipes from Azure Synapse Analytics workspaces Gen 2 and get to grips with Synapse Spark pools, SQL Serverless pools, Synapse integration pipelines, and Synapse data flows. You’ll also understand Synapse SQL Pool optimization techniques in this second edition. Besides Synapse enhancements, you’ll discover helpful tips on managing Azure SQL Database and learn about security, high availability, and performance monitoring. Finally, the book takes you through overall data engineering pipeline management, focusing on monitoring using Log Analytics and tracking data lineage using Azure Purview. By the end of this book, you’ll be able to build superior data engineering pipelines along with having an invaluable go-to guide.
Table of Contents (16 chapters)

Configuring high availability for a self-hosted IR

A self-hosted IR is a critical component for transferring data from on-premises data sources or data sources in virtual networks to Azure. Configuring additional nodes for a self-hosted IR ensures there is no single point of failure and provides high availability. Having additional nodes makes the self-hosted IR function as usual even when one of the nodes is under maintenance. Configuring additional nodes also allows load sharing with multiple data transfer jobs being executed in parallel on different nodes.

In the following recipe, we will install an IR on an additional machine to provide high availability and load-sharing capabilities.

Getting ready

Perform the following steps before working on this recipe:

  1. Log in to https://portal.azure.com using your Azure credentials.
  2. You will need an existing Data Factory account. If you don’t have one, create one by executing the following PowerShell script. Open...