Book Image

Azure for Architects - Third Edition

By : Ritesh Modi, Jack Lee, Rithin Skaria
Book Image

Azure for Architects - Third Edition

By: Ritesh Modi, Jack Lee, Rithin Skaria

Overview of this book

Thanks to its support for high availability, scalability, security, performance, and disaster recovery, Azure has been widely adopted to create and deploy different types of application with ease. Updated for the latest developments, this third edition of Azure for Architects helps you get to grips with the core concepts of designing serverless architecture, including containers, Kubernetes deployments, and big data solutions. You'll learn how to architect solutions such as serverless functions, you'll discover deployment patterns for containers and Kubernetes, and you'll explore large-scale big data processing using Spark and Databricks. As you advance, you'll implement DevOps using Azure DevOps, work with intelligent solutions using Azure Cognitive Services, and integrate security, high availability, and scalability into each solution. Finally, you'll delve into Azure security concepts such as OAuth, OpenConnect, and managed identities. By the end of this book, you'll have gained the confidence to design intelligent Azure solutions based on containers and serverless functions.
Table of Contents (21 chapters)
20
Index

9. Azure Big Data solutions

In the previous chapter, you learned about the various security strategies that can be implemented on Azure. With a secure application, we manage vast amounts of data. Big data has been gaining significant traction over the last few years. Specialized tools, software, and storage are required to handle it. Interestingly, these tools, platforms, and storage options were not available as services a few years back. However, with new cloud technology, Azure provides numerous tools, platforms, and resources to create big data solutions easily. This chapter will detail the complete architecture for ingesting, cleaning, filtering, and visualizing data in a meaningful way.

The following topics will be covered in this chapter:

  • Big data overview
  • Data integration
  • Extract-Transform-Load (ETL)
  • Data Factory
  • Data Lake Storage
  • Tools ecosystems such as Spark, Databricks, and Hadoop
  • Databricks