Study Guide on AZ-900 Exam: Core Azure Service

The Core Azure Services section, which constitutes 30-35% of the AZ-900 exam, covers the foundational services offered by Microsoft Azure. Understanding these services is essential for passing the exam and for effectively using Azure. Below is a detailed breakdown of the core areas within this section:

Key Points:

1. Core Azure Components: Regions, Availability Zones, Resource Groups, and ARM are key architectural components.
2. Core Services: Focus on compute (VMs, App Service, AKS), networking (VNets, Load Balancer), storage (Blob, Disk, Files), and databases (SQL Database, Cosmos DB).
3. Solutions: Understand the capabilities of IoT, AI, Machine Learning, and DevOps solutions.
4. Big Data and Analytics: Learn about tools like Azure Synapse, HDInsight, and Data Lake for handling large-scale data.

1. Core Azure Architectural Components

a) Azure Regions

• Regions are physical locations around the world where Azure data centers are located. Azure has over 60 regions globally.
• Each region consists of multiple data centers and provides services that are region-specific.
• Key Concept: When deploying resources, you choose a region, and this affects latency, compliance, and availability.

b) Availability Zones

• Availability Zones are unique physical locations within an Azure region that are made up of one or more data centers equipped with independent power, cooling, and networking.
• They are designed to protect your applications and data from data center failures by providing high availability.
• Use Case: Deploying critical services such as VMs or SQL Databases across multiple zones ensures that even if one zone goes down, your application continues running.

c) Azure Resource Groups

• Resource Groups are containers that hold related Azure resources. All resources like VMs, databases, and storage accounts must be placed in a resource group.
• Key Features:
  • Allows for grouping, management, and deployment of resources together.
  • Resources in a group can share the same lifecycle (e.g., deleting a resource group deletes all resources within it).

d) Azure Resource Manager (ARM)

• Azure Resource Manager is the deployment and management service for Azure. It provides a consistent management layer that allows you to manage resources through PowerShell, Azure CLI, REST API, and the Azure Portal.
• Key Concept: All resources are managed as a logical group via ARM, and ARM templates (JSON-based files) can be used to automate deployments.

2. Core Azure Services and Products

a) Azure Compute Services

Azure offers several services that provide compute power (e.g., to run applications, host websites, or perform data processing).

• Azure Virtual Machines (VMs):
  • VMs are IaaS services that allow you to create and run a virtualized operating system (Windows or Linux).
  • Use Case: Run traditional server workloads, host applications, or extend on-premises workloads to the cloud.
• Azure App Service:
  • A fully managed PaaS service for hosting web applications, RESTful APIs, and mobile backends.
  • Key Features: Auto-scaling, load balancing, and managed security updates.
• Azure Kubernetes Service (AKS):
  • A managed service that allows you to run and manage containers using Kubernetes.
  • Use Case: Ideal for microservices architecture and automating deployment, scaling, and operations of containerized applications.
• Azure Functions:
  • A serverless computing service that allows you to run code without provisioning or managing servers. Functions automatically scale and are event-driven.
  • Use Case: Use for small pieces of code, such as processing real-time data, automating tasks, or responding to HTTP requests.
• Azure Virtual Machine Scale Sets:
  • An IaaS service that allows you to deploy and manage a group of VMs together. It automatically scales the number of VMs based on demand.
  • Use Case: Used for large-scale applications that require high availability and automatic scaling.

b) Azure Networking Services

Networking services in Azure help connect, secure, and manage resources across the cloud and on-premises.

• Azure Virtual Network (VNet):
  • Enables Azure resources like VMs to securely communicate with each other, the internet, and on-premises networks.
  • Use Case: Establish private IP addresses and control traffic flow using subnets and network security groups.
• Azure Load Balancer:
  • Distributes incoming traffic across multiple resources (e.g., VMs) to ensure high availability.
  • Use Case: Use it to balance traffic between web servers for reliability and fault tolerance.
• Azure Application Gateway:
  • A web traffic load balancer that works at Layer 7 (application layer). It can handle things like SSL offloading, URL-based routing, and WAF (Web Application Firewall).
  • Use Case: Protects web applications from common threats and optimizes traffic routing.
• Azure VPN Gateway:
  • Allows you to establish secure, encrypted connections (VPNs) between an Azure Virtual Network and on-premises or other Azure networks.
  • Use Case: Hybrid cloud scenarios where you need secure communication between cloud and on-premises systems.

c) Azure Storage Services

Azure offers scalable, durable, and secure storage solutions for structured and unstructured data.

• Azure Blob Storage:
  • A service optimized for storing massive amounts of unstructured data, such as text or binary data.
  • Use Case: Store documents, media files, backups, and archives.
• Azure Disk Storage:
  • Provides persistent, high-performance storage for Azure VMs. It comes in different tiers based on performance (Standard HDD, Standard SSD, Premium SSD).
  • Use Case: Attach it to VMs to store operating system and application data.
• Azure Files:
  • Provides fully managed file shares in the cloud, accessible via the SMB protocol.
  • Use Case: File sharing for cloud or on-premises applications.
• Azure Queue Storage:
  • Used for decoupling and asynchronous messaging between application components.
  • Use Case: Use it to build reliable distributed systems by allowing one part of your application to send a message to a queue, and another part to process it later.

d) Azure Databases

• Azure SQL Database:
  • A fully managed relational database service based on Microsoft SQL Server. It provides PaaS capabilities such as automatic patching, backups, and scaling.
  • Use Case: For relational databases where you don’t want to manage infrastructure.
• Azure Cosmos DB:
  • A globally distributed, multi-model database service designed for high availability and low latency.
  • Key Features: Offers multiple consistency models and supports NoSQL databases.
  • Use Case: Ideal for applications that require high throughput and low latency (e.g., IoT, gaming).
• Azure Database for MySQL/PostgreSQL:
  • Managed databases for MySQL and PostgreSQL that handle backups, patching, scaling, and high availability.
  • Use Case: For users who want to use open-source relational databases but don’t want to manage the underlying infrastructure.

e) Azure Big Data and Analytics Services

• Azure Synapse Analytics:
  • An analytics service that brings together big data and data warehousing. It enables querying data using serverless or provisioned resources at scale.
  • Use Case: For real-time big data analytics and querying large data sets.
• Azure HDInsight:
  • A fully managed Apache Hadoop service that can run popular open-source frameworks like Hadoop, Spark, and Kafka.
  • Use Case: For big data processing and analytics at scale.
• Azure Data Lake:
  • A service that allows you to store and analyze massive amounts of data using the Hadoop ecosystem.
  • Use Case: To store structured and unstructured data in one place and process it using a variety of tools.

f) Internet of Things (IoT)

• Azure IoT Hub:
  • A service for connecting, monitoring, and managing IoT devices. It provides secure communication between IoT devices and Azure.
  • Use Case: For building IoT solutions that require reliable, bi-directional communication between millions of IoT devices.

3. Azure Solutions

Azure provides solutions for a wide range of use cases, including IoT, AI, Machine Learning, DevOps, and more.

a) Internet of Things (IoT)

• Azure IoT Central:
  • A managed IoT application platform that helps you build IoT solutions quickly.
  • Use Case: For organizations needing an end-to-end solution to manage IoT devices and data.

b) Artificial Intelligence (AI)

• Azure Machine Learning:
  • A cloud-based platform that enables you to build, deploy, and manage machine learning models.
  • Use Case: For building predictive analytics solutions and automating business processes with AI.
• Cognitive Services:
  • A collection of AI APIs that enable developers to integrate vision, speech, language, and decision-making capabilities into applications.
  • Use Case: For adding AI-driven features like text analysis, speech recognition, and image processing to apps.

c) Azure DevOps

• Azure DevOps:
  • A suite of tools that allows developers to plan, develop, test, and deploy applications using continuous integration (CI) and continuous delivery (CD) practices.
  • Use Case: For managing code repositories, automating builds, testing applications,
  and deploying to production.