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You're reading from  Azure Data Engineer Associate Certification Guide

Product typeBook
Published inFeb 2022
PublisherPackt
ISBN-139781801816069
Edition1st Edition
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Newton Alex
Newton Alex
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Newton Alex

Newton Alex leads several Azure Data Analytics teams in Microsoft, India. His team contributes to technologies including Azure Synapse, Azure Databricks, Azure HDInsight, and many open source technologies, including Apache YARN, Apache Spark, and Apache Hive. He started using Hadoop while at Yahoo, USA, where he helped build the first batch processing pipelines for Yahoo's ad serving team. After Yahoo, he became the leader of the big data team at Pivotal Inc., USA, where he was responsible for the entire open source stack of Pivotal Inc. He later moved to Microsoft and started the Azure Data team in India. He has worked with several Fortune 500 companies to help build their data systems on Azure.
Read more about Newton Alex

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Exploring Azure Compute

Azure Compute is a generic term for all the compute-focused technologies in Azure. Let's explore some of the common Compute Services provided by Azure. Each of these technologies is worthy of a book, so we will just be focusing on introducing these technologies in this chapter. We will dive deeper into some of the technologies that are required for the certification later in this book.

VM Scale Sets

VM Scale Sets is a collection of load-balanced VMs that can be used to build highly scalable services. For example, we can have a set of web servers that can scale horizontally based on the load. The advantage of using VM Scale Sets as opposed to manually setting up VMs is that VM Scale Sets can be launched and managed using centralized templates. It comes with a load balancer by default, so we don't have to set it up manually. It also takes care of automatic scale out and scale in based on the load. In addition, VM Scale Sets have higher reliability as the workload is spread across multiple servers. Even if a few nodes fail, VM Scale Sets can quickly bring up additional nodes to replace the capacity. VM Scale Sets can be configured across availability zones to improve the availability even more.

You can learn more about VM Scale Sets here: https://azure.microsoft.com/en-in/services/virtual-machine-scale-sets/.

Azure App Service

Azure App Service allows you to develop and host web apps, mobile apps, and APIs using a wide selection of languages such as .NET, Java, Node.js, Python, ASP.NET, and more. These are fully managed services that provide support for the entire life cycle of apps such as development, CI/CD, releases, maintenance, debugging, and scaling. Azure App Service is backed by enterprise-grade security and compliance. There are very detailed examples, tutorials, and support available in Azure for building complete web and mobile solutions using Azure App Service.

You can learn more about Azure App Service here: https://azure.microsoft.com/en-in/services/app-service/.

Azure Kubernetes Service

Kubernetes is an open source container orchestration software. Azure Kubernetes Service (AKS) is a PaaS version of Kubernetes that's hosted on Azure. AKS provides a complete life cycle management for containerized apps, starting from development (using Visual Studio, code, and other Kubernetes tools), through to CI/CD (integration with GitHub), deployment, scaling, telemetry, logging, monitoring, and more. AKS also supports Docker images, which are widely used for containerization.

You can learn more about AKS here: https://azure.microsoft.com/en-in/services/kubernetes-service/.

Azure Functions

Azure Functions is a perfect example of a serverless technology and is a SaaS. Serverless doesn't mean that there are no servers, it just means that you don't have to deploy, maintain, or upgrade your servers (VMs); someone else is doing it for you in the background and abstracting the details from you. You can use functions to write your processing logic based on event triggers and bindings such as a transaction in a database, an IoT event, and a REST call. The blocks of code you write are called functions (no points for guessing that). All you need to do is open the Azure Functions Notebook Interface and write your logic (code) directly in it. There are function extensions available in the many languages that support integration with Development, CI/CD, and DevOps tools.

You can learn more about Azure Functions here: https://azure.microsoft.com/en-in/services/functions/.

Azure Service Fabric

Service Fabric is a very powerful cluster technology that takes care of app deployment, scaling, upgrades, and maintenance for microservice-based applications. It can take care of the entire life cycle management process for applications. This is similar to AKS but for non-containerized applications. Many of the core Azure services themselves run on top of Service Fabric. Service Fabric is an open source project and has very high reliability and availability.

You can learn more about Azure Service Fabric here: https://azure.microsoft.com/en-in/services/service-fabric/.

Azure Batch

Azure Batch is used to run large parallel processing applications or high-performance computing applications. Batch provides the necessary resource management, scheduling, and scaling support to run any traditional MPP programs. It spins up the VMs and deploys and runs your programs in a parallel manner. It can dynamically scale up and down as required to optimize the cost. Azure Batch can be used for high volume batch processing, financial modeling, video rendering, weather prediction model generation, and so on.

You can learn more about Azure Batch here: https://azure.microsoft.com/en-in/services/batch/.

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Published in: Feb 2022Publisher: PacktISBN-13: 9781801816069
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Author (1)

author image
Newton Alex

Newton Alex leads several Azure Data Analytics teams in Microsoft, India. His team contributes to technologies including Azure Synapse, Azure Databricks, Azure HDInsight, and many open source technologies, including Apache YARN, Apache Spark, and Apache Hive. He started using Hadoop while at Yahoo, USA, where he helped build the first batch processing pipelines for Yahoo's ad serving team. After Yahoo, he became the leader of the big data team at Pivotal Inc., USA, where he was responsible for the entire open source stack of Pivotal Inc. He later moved to Microsoft and started the Azure Data team in India. He has worked with several Fortune 500 companies to help build their data systems on Azure.
Read more about Newton Alex