High availability design patterns in Azure - Mini Project: Build & Apply

High Availability Design Patterns in Azure

📖 Scenario: You are working for a company that wants to ensure their web application is always available to users, even if one part of the system fails. They want to use Azure services to build a highly available architecture.

🎯 Goal: Build a simple Azure infrastructure setup that uses high availability design patterns including multiple virtual machines behind a load balancer and availability sets.

📋 What You'll Learn

Create a resource group named HighAvailabilityRG

Create two virtual machines named vm1 and vm2 in an availability set

Create an availability set named AppAvailabilitySet

Create a load balancer named AppLoadBalancer that distributes traffic to both VMs

💡 Why This Matters

🌍 Real World

High availability design patterns are essential for business-critical applications to avoid downtime and provide continuous service to users.

💼 Career

Cloud architects and infrastructure engineers use these patterns to design resilient systems that meet uptime requirements.

1

Create the resource group and availability set

Create a resource group called HighAvailabilityRG in the eastus region. Then create an availability set called AppAvailabilitySet inside this resource group.

Azure

# Your code here to create resource group and availability set

Hint

Use az group create to create the resource group and az vm availability-set create to create the availability set.

2

Create two virtual machines in the availability set

Create two virtual machines named vm1 and vm2 inside the HighAvailabilityRG resource group. Both VMs must be part of the AppAvailabilitySet availability set. Use the UbuntuLTS image and size Standard_B1s.

Azure

az group create --name HighAvailabilityRG --location eastus
az vm availability-set create --resource-group HighAvailabilityRG --name AppAvailabilitySet --platform-fault-domain-count 2 --platform-update-domain-count 2
# Your code here to create vm1 and vm2 in the availability set

Hint

Use az vm create with the --availability-set option to place VMs in the availability set.

3

Create a load balancer to distribute traffic

Create a public load balancer named AppLoadBalancer in the HighAvailabilityRG resource group. Configure it to distribute incoming HTTP traffic on port 80 to both vm1 and vm2.

Azure

az group create --name HighAvailabilityRG --location eastus
az vm availability-set create --resource-group HighAvailabilityRG --name AppAvailabilitySet --platform-fault-domain-count 2 --platform-update-domain-count 2
az vm create --resource-group HighAvailabilityRG --name vm1 --image UbuntuLTS --size Standard_B1s --availability-set AppAvailabilitySet --admin-username azureuser --generate-ssh-keys
az vm create --resource-group HighAvailabilityRG --name vm2 --image UbuntuLTS --size Standard_B1s --availability-set AppAvailabilitySet --admin-username azureuser --generate-ssh-keys
# Your code here to create and configure the load balancer

Hint

Use az network lb create to create the load balancer and az network lb rule create to add a rule for HTTP traffic.

4

Associate virtual machines' network interfaces with the load balancer backend pool

Associate the network interfaces of vm1 and vm2 with the backend address pool AppBackendPool of the AppLoadBalancer load balancer.

Azure

az group create --name HighAvailabilityRG --location eastus
az vm availability-set create --resource-group HighAvailabilityRG --name AppAvailabilitySet --platform-fault-domain-count 2 --platform-update-domain-count 2
az vm create --resource-group HighAvailabilityRG --name vm1 --image UbuntuLTS --size Standard_B1s --availability-set AppAvailabilitySet --admin-username azureuser --generate-ssh-keys
az vm create --resource-group HighAvailabilityRG --name vm2 --image UbuntuLTS --size Standard_B1s --availability-set AppAvailabilitySet --admin-username azureuser --generate-ssh-keys
az network public-ip create --resource-group HighAvailabilityRG --name AppPublicIP --allocation-method Static --sku Standard
az network lb create --resource-group HighAvailabilityRG --name AppLoadBalancer --frontend-ip-name LoadBalancerFrontEnd --backend-pool-name AppBackendPool --public-ip-address AppPublicIP
az network lb rule create --resource-group HighAvailabilityRG --lb-name AppLoadBalancer --name HTTPRule --protocol Tcp --frontend-port 80 --backend-port 80 --frontend-ip-name LoadBalancerFrontEnd --backend-pool-name AppBackendPool
# Your code here to associate vm1 and vm2 NICs with the backend pool

Hint

Use az network nic ip-config address-pool add to add each VM's network interface to the load balancer backend pool.

Practice

1. Which Azure service is primarily used to distribute incoming traffic across multiple virtual machines to ensure high availability?

easy

A. Azure Functions

B. Azure Blob Storage

C. Azure Load Balancer

D. Azure Cosmos DB

Solution

1. Step 1: Understand the role of Azure Load Balancer

   Azure Load Balancer distributes incoming network traffic across multiple VMs to prevent any single VM from becoming a bottleneck.

2. Step 2: Compare with other services

   Azure Blob Storage stores data, Azure Functions run code, and Cosmos DB is a database service; none distribute traffic.

3. Final Answer:

   Azure Load Balancer -> Option C

4. Quick Check:

   Traffic distribution = Azure Load Balancer [OK]

Hint: Load Balancer spreads traffic to VMs for uptime [OK]

Common Mistakes:

• Confusing storage or compute services with traffic distribution
• Choosing Azure Functions for load balancing
• Selecting database services for availability patterns

2. Which of the following is the correct syntax to create an Azure VM Scale Set using Azure CLI for high availability?

easy

A. az vm create --name MyScaleSet --resource-group MyResourceGroup --image UbuntuLTS --instance-count 3

B. az vm create --name MyScaleSet --resource-group MyResourceGroup --image UbuntuLTS --count 3

C. az vmss deploy --name MyScaleSet --group MyResourceGroup --image UbuntuLTS --instances 3

D. az vmss create --name MyScaleSet --resource-group MyResourceGroup --image UbuntuLTS --instance-count 3

Solution

1. Step 1: Identify the correct Azure CLI command for VM Scale Set creation

   The command to create a VM Scale Set is az vmss create, not az vm create.

2. Step 2: Check the parameters

   Parameters like --name, --resource-group, --image, and --instance-count are correctly used in az vmss create --name MyScaleSet --resource-group MyResourceGroup --image UbuntuLTS --instance-count 3.

3. Final Answer:

   az vmss create --name MyScaleSet --resource-group MyResourceGroup --image UbuntuLTS --instance-count 3 -> Option D

4. Quick Check:

   VM Scale Set creation uses az vmss create [OK]

Hint: Use 'az vmss create' for VM Scale Sets [OK]

Common Mistakes:

• Using 'az vm create' instead of 'az vmss create'
• Incorrect parameter names like --count instead of --instance-count
• Mixing resource group parameter names

3. Consider this Azure Load Balancer configuration snippet:

frontendIPConfiguration:
  name: LoadBalancerFrontEnd
  publicIPAddress:
    id: /subscriptions/xxx/resourceGroups/rg/providers/Microsoft.Network/publicIPAddresses/myPublicIP
backendAddressPools:
  - name: BackendPool
loadBalancingRules:
  - name: HTTPRule
    frontendIPConfiguration: LoadBalancerFrontEnd
    backendAddressPool: BackendPool
    protocol: Tcp
    frontendPort: 80
    backendPort: 80
    enableFloatingIP: false
    idleTimeoutInMinutes: 4
    loadDistribution: Default

What will happen if one VM in the backend pool becomes unhealthy?

medium

A. Traffic will automatically stop going to the unhealthy VM

B. Traffic will continue to be sent to the unhealthy VM

C. Load Balancer will restart the unhealthy VM

D. Load Balancer will redirect traffic to a different port

Solution

1. Step 1: Understand Azure Load Balancer health probe behavior

   Azure Load Balancer requires health probes configured to detect unhealthy VMs and stop sending traffic to them. This snippet does not show health probes configured, but in practice, health probes are necessary for proper load balancing.

2. Step 2: Analyze the effect of missing health probes

   Without health probes, the Load Balancer cannot detect unhealthy VMs, so it continues sending traffic to all VMs in the backend pool. However, best practice is to configure health probes to avoid this.

3. Final Answer:

   Traffic will automatically stop going to the unhealthy VM -> Option A

4. Quick Check:

   Health probes detect unhealthy VMs and stop traffic [OK]

Hint: Configure health probes to avoid sending traffic to bad VMs [OK]

Common Mistakes:

• Assuming Load Balancer auto-detects unhealthy VMs without probes
• Thinking Load Balancer restarts VMs
• Confusing port redirection with load balancing

4. You have configured an Active-Passive high availability setup using Azure Traffic Manager. However, during failover, users experience downtime. What is the most likely cause?

medium

A. Traffic Manager is set to Performance routing with multiple active endpoints

B. Traffic Manager is set to Priority routing but health probes are misconfigured

C. Azure Load Balancer is not configured with a public IP

D. VM Scale Set has only one instance

Solution

1. Step 1: Understand Active-Passive with Traffic Manager Priority routing

   Priority routing sends traffic to the primary endpoint unless it is unhealthy, then fails over to secondary.

2. Step 2: Identify impact of misconfigured health probes

   If health probes are misconfigured, Traffic Manager cannot detect endpoint health and will not failover properly, causing downtime.

3. Final Answer:

   Traffic Manager is set to Priority routing but health probes are misconfigured -> Option B

4. Quick Check:

   Priority routing + bad probes = failover fails [OK]

Hint: Check health probes when failover fails in Priority routing [OK]

Common Mistakes:

• Confusing routing methods in Traffic Manager
• Blaming Load Balancer or VM Scale Set for Traffic Manager failover
• Ignoring health probe configuration

5. You want to design a geo-redundant high availability solution for a web app in Azure that must remain available even if an entire Azure region fails. Which combination of Azure services and design patterns best achieves this?

hard

A. Deploy the app in two regions with Azure Traffic Manager using Performance routing and Azure SQL Geo-Replication

B. Deploy the app in one region with Azure Load Balancer and VM Scale Sets, and use Azure Backup for disaster recovery

C. Deploy the app in two regions with Azure Traffic Manager using Priority routing and VM Scale Sets in each region

D. Deploy the app in one region with Azure Application Gateway and use Azure Blob Storage for static content

Solution

1. Step 1: Understand geo-redundancy requirements

   To survive a full region failure, the app must be deployed in multiple regions with traffic routed between them.

2. Step 2: Evaluate options for traffic routing and data replication

   Performance routing in Traffic Manager directs users to the closest healthy region. Azure SQL Geo-Replication ensures database availability across regions.

3. Step 3: Compare with other options

   Priority routing is for Active-Passive, not best for geo-load balancing. Single region deployments cannot survive region failure. Application Gateway is regional and does not provide geo-failover.

4. Final Answer:

   Deploy the app in two regions with Azure Traffic Manager using Performance routing and Azure SQL Geo-Replication -> Option A

5. Quick Check:

   Geo-redundancy needs multi-region + performance routing + geo-replication [OK]

Hint: Use multi-region + Traffic Manager Performance + Geo-Replication [OK]

Common Mistakes:

• Choosing Priority routing for geo-load balancing
• Relying on single region with backup for high availability
• Confusing Application Gateway with global traffic routing