Resize an Azure Virtual Machine

Lab Overview

In this lab, you’ll learn how to resize an existing Azure Virtual Machine using the Azure portal. Resizing a VM is a critical task when you need to adjust the resources allocated to your virtual machine, such as increasing or decreasing CPU and memory to match workload requirements.

The lab will guide you through the process of selecting a different size, applying filters to find the appropriate VM size, and resizing the VM.

By the end of this lab, you’ll understand how to effectively resize a virtual machine to optimize its performance or cost.

Learning Objectives

Understand how to initiate the resizing process for an Azure Virtual Machine.

Learn how to filter and select appropriate VM sizes based on CPU and resource requirements.

Gain hands-on experience resizing a VM to a smaller size.

Learn how to verify and confirm that the VM has been resized successfully.

Understand the potential impact and downtime associated with resizing a virtual machine.

Exam Relevance

The skills you learn in this lab are necessary to pass the following Azure certification exams:

AZ-104
AZ-305

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Azure VM Scale Sets — Quick Reference

Fast lookup for orchestration modes, autoscaling, load balancing, updates & CLI.

Core Benefits

Create & manage groups of identical or heterogeneous VMs.
Automatic scaling based on demand or schedule.
Load balance traffic across instances.
HA across fault domains & availability zones.
Pay only for VMs; no charge for scale set itself.

Scale sets can handle up to 1,000 VMs (Marketplace/Gallery images).

Orchestration Modes

Mode	Profile	Best For
Flexible	Standard Azure VMs	New workloads (default)
Uniform	Identical VMs	Legacy large-scale workloads

Flexible: Full standard VM APIs, dynamic mixing (Spot+on-demand), 1,000 VMs. Uniform: Locked after creation; up to 1,000 VMs (Marketplace) or 600 (custom images).

Orchestration Comparison

Feature	Flexible	Uniform
Standard VM APIs	Yes	No
Mix instance types	Yes	No
RBAC per VM	Yes	No
Azure Backup	Yes	No
Site Recovery	Yes	No
Fault domains	1–3	1–5

Autoscaling Metrics

Host metrics: CPU, memory, disk (no agent needed).
Guest metrics: Custom counters (Azure Diagnostics Extension).
App Insights: Application-level performance metrics.
Rules: Min/max capacity, scale-out/in thresholds, cooldown periods.

Autoscale rules use metrics from Load Balancer, Diagnostics, or App Insights.

Load Balancing

Type	Layer	Best For
Internal LB	L4	Backend pools
Public LB	L4	External traffic
App Gateway	L7	HTTP/HTTPS + WAF

Large scale sets (>100 VMs) require Load Balancer Standard SKU.

Availability & Zones

Single zone: All VMs in one availability zone.
Zone-redundant: VMs spread across 1, 2, or 3 zones in region.
Zone balance: Auto-spread VMs evenly across zones (±1 VM).
Fault domains: 1–3 per zone for best-effort resilience.

Use availability zones for datacenter-level failure protection.

Upgrade Policies (Uniform)

Policy	Rollout	Use
Automatic	Batch	App can tolerate disruption
Rolling	Controlled	Gradual, managed updates
Manual	On-demand	Full control; explicit API calls

Flexible mode uses standard VM updates; no built-in rolling.

Application Deployment

Custom image: Preinstall app; faster provisioning.
Custom Script Extension: Download & run scripts post-deploy.
Azure VM Applications: Package & manage centrally (new).
PowerShell DSC: Desired State Configuration for consistency.

Custom images: 600 VMs max; Marketplace images: 1,000 VMs.

Planned Maintenance & Health

Azure Patch Manager: Automated guest OS patching.
Application Health Extension: Monitor app heartbeat; auto-replace unhealthy.
Health probes (Uniform): Monitor via load balancer.
Platform updates coordinated; typically brief interruption.