Why VMs provide compute flexibility in Azure - Visual Breakdown

Process Flow - Why VMs provide compute flexibility

User needs compute power

↓

Choose VM size and specs

↓

Deploy VM on cloud

↓

Run applications

↓

Adjust VM resources anytime

↓

Scale up/down or stop/start VM

↓

Pay only for what you use

This flow shows how users select, deploy, and adjust virtual machines to match their compute needs flexibly.

Execution Sample

Azure

Create VM with 2 CPUs and 4GB RAM
Start VM
Run app
Scale VM to 4 CPUs and 8GB RAM
Stop VM

This sequence shows creating a VM, running an app, scaling resources, and stopping the VM to save costs.

Process Table

Step	Action	VM CPU	VM RAM (GB)	VM State	Effect
1	Create VM	2	4	Stopped	VM created with initial specs, not running
2	Start VM	2	4	Running	VM is powered on and ready for use
3	Run app	2	4	Running	Application runs using allocated resources
4	Scale VM	4	8	Running	Resources increased without downtime
5	Stop VM	4	8	Stopped	VM powered off, no compute charges

💡 VM stopped to save costs; user can restart or resize anytime

Status Tracker

Variable	Start	After Step 1	After Step 2	After Step 4	After Step 5
VM CPU	N/A	2	2	4	4
VM RAM (GB)	N/A	4	4	8	8
VM State	N/A	Stopped	Running	Running	Stopped

Key Moments - 2 Insights

Why can we change VM CPU and RAM while it is running?

Because cloud VMs support dynamic scaling, allowing resource adjustment without downtime, as shown in step 4 of the execution_table.

Does stopping the VM delete it or just pause it?

Stopping the VM pauses it and stops compute charges but keeps the VM and its data intact, as seen in step 5.

Visual Quiz - 3 Questions

Look at the execution_table, what is the VM state after step 2?

A Deleted

B Stopped

C Running

D Paused

💡 Hint

Check the 'VM State' column in row for step 2 in execution_table

At which step does the VM get more CPU and RAM?

A Step 1

B Step 4

C Step 3

D Step 5

💡 Hint

Look for resource changes in 'VM CPU' and 'VM RAM' columns in execution_table

If the VM was never stopped, what would be the VM state after step 5?

A Running

B Stopped

C Deleted

D Suspended

💡 Hint

Refer to 'VM State' changes in variable_tracker and execution_table

Concept Snapshot

VMs let you pick CPU and RAM sizes to match your needs.
You can start, stop, and change VM resources anytime.
Scaling up or down is quick and flexible.
You pay only for running VMs, saving money when stopped.
This flexibility helps run apps efficiently in the cloud.

Full Transcript

Virtual Machines (VMs) provide compute flexibility by allowing users to select the CPU and RAM resources they need. Users create a VM with chosen specs, start it to run applications, and can adjust resources like CPU and RAM dynamically without downtime. Stopping the VM pauses it to save costs but keeps the VM intact for later use. This flexibility means users only pay for what they use and can scale resources up or down as needed.

Practice

1. Why do virtual machines (VMs) provide flexibility in computing resources?

easy

A. Because they only run one fixed operating system

B. Because they require physical hardware upgrades for changes

C. Because they cannot be stopped once started

D. Because you can easily change their CPU, memory, and storage sizes

Solution

1. Step 1: Understand VM resource allocation

   VMs allow you to assign CPU, memory, and storage resources flexibly without changing physical hardware.

2. Step 2: Compare with fixed hardware

   Unlike physical machines, VMs can be resized or reconfigured quickly to meet changing needs.

3. Final Answer:

   Because you can easily change their CPU, memory, and storage sizes -> Option D

4. Quick Check:

   VM resource flexibility = changing CPU, memory, storage [OK]

Hint: VMs let you resize resources without hardware changes [OK]

Common Mistakes:

• Thinking VMs run only one OS
• Believing VMs can't be stopped or changed
• Confusing physical hardware upgrades with VM changes

2. Which of the following is the correct way to specify a VM size in Azure CLI?

easy

A. az vm create --type Standard_DS1_v2

B. az vm create --size Standard_DS1_v2

C. az vm create --memory 4GB

D. az vm create --cpu 2

Solution

1. Step 1: Identify correct VM size parameter

   Azure CLI uses the --size parameter to specify VM size like Standard_DS1_v2.

2. Step 2: Check other options

   --type, --memory, and --cpu are not valid parameters for VM size in this command.

3. Final Answer:

   az vm create --size Standard_DS1_v2 -> Option B

4. Quick Check:

   VM size uses --size parameter [OK]

Hint: Use --size to set VM size in Azure CLI commands [OK]

Common Mistakes:

• Using --type instead of --size
• Trying to set memory or CPU separately in create command
• Confusing VM size with VM type

3. Given this Azure VM scale set configuration snippet, what happens when demand increases?

{
  "sku": { "capacity": 2, "name": "Standard_DS1_v2" },
  "upgradePolicy": { "mode": "Manual" }
}

medium

A. The VM scale set stays at 2 VMs until manually changed

B. The VM scale set automatically adds more VMs to handle demand

C. The VM scale set deletes VMs when demand increases

D. The VM scale set changes VM size automatically

Solution

1. Step 1: Analyze the capacity and upgrade policy

   The capacity is set to 2, and upgrade mode is Manual, meaning no automatic scaling.

2. Step 2: Understand scaling behavior

   Since no autoscale is configured, the VM count stays fixed at 2 until manually changed.

3. Final Answer:

   The VM scale set stays at 2 VMs until manually changed -> Option A

4. Quick Check:

   Manual upgrade means no auto scaling [OK]

Hint: Manual mode means no automatic VM count changes [OK]

Common Mistakes:

• Assuming automatic scaling with Manual mode
• Thinking VM size changes automatically
• Confusing scale set with single VM behavior

4. You tried to resize an Azure VM but got an error. Which of these is the most likely cause?

medium

A. The VM size you chose does not exist in your region

B. You forgot to specify the VM name in the command

C. The VM is running and needs to be stopped before resizing

D. The VM is already the smallest size possible

Solution

1. Step 1: Check VM resize requirements

   VMs can be resized only to sizes available in the region where they run.

2. Step 2: Identify common resize errors

   If the chosen size is unavailable in the region, Azure returns an error.

3. Final Answer:

   The VM size you chose does not exist in your region -> Option A

4. Quick Check:

   Resize errors often due to unavailable sizes in region [OK]

Hint: Check VM size availability in your region before resizing [OK]

Common Mistakes:

• Assuming VM must be stopped for all resize types
• Ignoring region availability of VM sizes
• Forgetting to specify VM name causes different errors

5. You want to optimize costs by automatically adjusting VM resources based on workload. Which Azure feature should you use to achieve compute flexibility?

hard

A. Azure Active Directory for VM access control

B. Azure Blob Storage for VM backups

C. Azure VM Scale Sets with autoscaling rules

D. Azure Virtual Network peering

Solution

1. Step 1: Identify cost optimization via resource adjustment

   Automatically adjusting VM count or size based on workload is done by autoscaling.

2. Step 2: Match feature to autoscaling

   Azure VM Scale Sets support autoscaling rules to add or remove VMs dynamically.

3. Step 3: Exclude unrelated features

   Blob Storage, Virtual Network peering, and Active Directory do not manage VM compute scaling.

4. Final Answer:

   Azure VM Scale Sets with autoscaling rules -> Option C

5. Quick Check:

   Autoscaling VM Scale Sets = compute flexibility and cost saving [OK]

Hint: Use VM Scale Sets autoscaling to adjust resources automatically [OK]

Common Mistakes:

• Confusing storage or network features with compute scaling
• Thinking access control manages resource scaling
• Ignoring autoscaling capabilities of VM Scale Sets