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Azure Virtual Machines

Introduction

Azure Virtual Machines (VMs) provide on-demand, scalable computing resources in the cloud. VMs allow you to run applications and services, providing the same user experience as a physical computer. You can select from a variety of operating systems and configurations to suit your needs.

Key Points

  • Azure VMs are part of the Infrastructure as a Service (IaaS) model.
  • They can run Windows or Linux operating systems.
  • VMs are highly scalable and can be adjusted based on workload requirements.
  • Azure provides various sizes and types of VMs for different use cases.

Step-by-Step Process to Create an Azure Virtual Machine

Follow these steps to create a Virtual Machine in Azure:


graph TD;
    A[Start] --> B[Log in to Azure Portal];
    B --> C[Click on Create a Resource];
    C --> D[Select Virtual Machine];
    D --> E[Configure Basic Settings];
    E --> F[Choose Size];
    F --> G[Configure Networking];
    G --> H[Review + Create];
    H --> I[Click Create];
    I --> J[VM is Deployed];
            

Best Practices

Consider the following best practices when using Azure VMs:

  • Regularly update and patch your VM OS for security.
  • Use Azure Resource Manager (ARM) templates for deployment consistency.
  • Monitor performance and resource utilization to optimize costs.
  • Consider using Managed Disks for better performance and reliability.

FAQ

What is the difference between Azure VMs and Azure App Services?

Azure VMs offer full control over the operating system and resources, allowing you to run any application. Azure App Services, on the other hand, is a platform-as-a-service (PaaS) offering that abstracts the infrastructure management, making it easier to deploy web applications.

Can I scale Azure VMs?

Yes, Azure VMs can be scaled vertically (by changing the size of the VM) or horizontally (by adding more VM instances). Azure also supports auto-scaling features.

What types of Azure VMs are available?

Azure provides various VM types optimized for different tasks, including General Purpose, Compute Optimized, Memory Optimized, Storage Optimized, and GPU instances.