How to Deploy Multi-Cloud Kubernetes Applications on Azure Cloud: A Comprehensive Guide

Table of Contents

Introduction

Thanks to the industry’s transition to the cloud, business strategies increasingly involve a multi-cloud strategy to gain more flexibility, resilience, and performance. Deploying multiple cloud platforms ensures vendor lock, reduces downtime risk, and exploits best-of-breed from each provider.
Fittingly, one of the core instruments for enabling multi-cloud strategies is Kubernetes, the #1 leader in container orchestration. Suppose your enterprise wants to deploy multi-cloud Kubernetes applications on Azure Cloud across various clouds. In that case, Azure Kubernetes Service (AKS) is the robust integration with Kubernetes that makes it a top choice.
This comprehensive guide will walk through a step-by-step process to deploy multi-cloud Kubernetes applications on Azure.

Why Multi-Cloud for Kubernetes?

Deploying Kubernetes across multiple clouds offers several distinct advantages. Below are key reasons why businesses embrace multi-cloud strategies:

• Disaster Recovery and Redundancy: Multi-cloud means your applications can fail over to another cloud provider, so service halts are not a problem.
• Data Sovereignty and Compliance: Under the regulations, businesses must sometimes store data in certain geolocations. However, businesses can meet these compliance requirements using multiple cloud providers.
• Performance Optimization: Cloud providers don’t guarantee better performance; they may offer better performance in some regions or workloads. For businesses, it makes sense to distribute their applications across the cloud to optimize performance and cost.
• Avoid Vendor Lock-In: By restricting to a single cloud provider, flexibility is reduced, and costs are increased. With this strategy, workloads are distributed in multiple providers to prevent this.

However, managing a multi-cloud Kubernetes approach brings networking, security, and management issues. Now, let’s explore the best ways to overcome these challenges when your primary goal is to deploy Kubernetes applications on Azure.

Prerequisites

To deploy Kubernetes applications on Azure, you must check for specific prerequisites like some tools and configurations:

• Azure Kubernetes Service (AKS): To simplify cluster management, you must have access to Azure’s managed Kubernetes service.
• Docker: Access to the Docker tool is mandatory for containerizing applications that you intend to deploy across the cloud.
• kubectl: A specific prerequisite to this command line tool is necessary to manage Kubernetes clusters efficiently.
• Azure CLI: Interacting with Azure resources is mandatory when you want to deploy Kubernetes applications on Azure, and Azure CLI is the tool that makes it happen. Ensure you have access to it.
• Networking Configuration: You’ll need VPN or secure network setups for communication between Azure and other cloud environments (AWS, GCP, etc.).

Tools Setup:

1. Install Azure CLI: Azure CLI Installation Guide
2. Install kubectl: Install kubectl
3. Install Docker: Docker Installation Guide

These tools and configurations ensure a smooth deployment process, setting you up for the multi-cloud Kubernetes environment.

Setting Up Your Azure Environment

First, configure your Azure Kubernetes Service (AKS) environment, making it easier to deploy multi-cloud Kubernetes applications on Azure cloud. Then, I’ll walk you through the step-by-step process of creating an AKS cluster and a few basic configuration parameters you would need for node scaling, network setup, and the little extra pulling in security.

Step 1: Log in to Azure

● Start by logging into your Azure account using the Azure CLI.



az login

● This command will prompt you to open a browser and authenticate with your Azure credentials.

Step 2: Create a Resource Group

● To have all the associated resources first, an AKS cluster requires you to create a resource group. Here is the command that will help you create a resource group:



az group create --name myResourceGroup --location eastus

➱ In this code
● --myResourceGroup represents the resource group, and
● --eastus represents the region.

Step 3: Create an AKS Cluster

● Now, create the AKS cluster. During cluster creation, you can specify node scaling, networking, and security settings. Here’s a basic command to create a 3-node AKS cluster:



az aks create \
    --resource-group myResourceGroup \
    --name myAKSCluster \
    --node-count 3 \
    --enable-addons monitoring \
    --generate-ssh-keys

--node-count 3: Sets up a cluster with three nodes.
--enable add-ons monitoring: Adds Azure Monitor to monitor the cluster.
--generate-ssh-keys: Creates SSH keys to connect to the cluster securely.
For advanced networking options, you can specify additional parameters, such as configuring Virtual Network (VNet) integration:



az aks create \
    --resource-group myResourceGroup \
    --name myAKSCluster \
    --node-count 3 \
    --network-plugin azure \
    --vnet-subnet-id "/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Network/virtualNetworks/{vnetName}/subnets/{subnetName}" \
    --enable-private-cluster \
    --generate-ssh-keys

--network-plugin azure: For configuring CNI networking plugin of Azure.
--vnet-subnet-id: Get idle specification for the subnet for your VNet.
--enable-private-cluster: To limit public access by enabling private AKS cluster.

Step 4: Connect to the AKS Cluster

● After you are done creating the AKS cluster, use kubectl to connect it:



az aks get-credentials --resource-group myResourceGroup --name myAKSCluster

● Use this command to merge AKS clutter with your cluster credentials within the local kubectl configuration. This will make it easier to manage your clusters in the future.

Step 5: Verify the Cluster

● To ensure the AKS cluster you prepared is working fine and running smoothly, you can run the following command:



kubectl get nodes

● You should see an output listing your AKS nodes similar to this:



NAME                                STATUS   ROLES   AGE    VERSION
aks-nodepool1-12345678-vmss000000    Ready    agent   10m    v1.20.7
aks-nodepool1-12345678-vmss000001    Ready    agent   10m    v1.20.7
aks-nodepool1-12345678-vmss000002    Ready    agent   10m    v1.20.7

Step 6: Configure Node Scaling

● To enable auto-scaling for your AKS cluster, use the following command:



az aks update \
    --resource-group myResourceGroup \
    --name myAKSCluster \
    --enable-cluster-autoscaler \
    --min-count 1 \
    --max-count 5

This configuration ensures that your cluster scales between 1 and 5 nodes based on workload demands.

Need expert guidance on deploying and managing Kubernetes applications across multiple clouds?

Our Azure Consulting Services are here to simplify your journey.

Setting Up a VPN Connection Between Azure and Other Clouds

You can use a VPN Gateway to enable secure communication between your Azure environment and other cloud platforms. Here’s a high-level process for connecting Azure to AWS or GCP via VPN.

1. Create an Azure VPN Gateway

● The initial step is setting up a VPN gateway in the Azure Environment:



az network vnet create --resource-group myResourceGroup --name myVNet --address-prefix 10.0.0.0/16 --subnet-name GatewaySubnet --subnet-prefix 10.0.255.0/24

● Next, create the VPN Gateway itself:



az network vnet-gateway create --resource-group myResourceGroup --name myVpnGateway --public-ip-address myVpnPublicIp --vnet myVNet --gateway-type Vpn --vpn-type RouteBased --sku VpnGw1 --no-wait

2. Create a VPN Connection on AWS or GCP

Set up a VPN gateway on AWS or GCP to allow for secure communication. The exact steps depend on the provider, but you’ll need to configure:
● VPN Gateway (similar to Azure)
● IPsec Tunnel between the two environments
● Routing Tables to allow traffic between Azure and AWS/GCP networks

3. Establish the Connection

Now, it’s time to establish a VPN connection between Azure and other cloud service provider (for example, AWS or GCP), once you are done configuring both the VPN gateways. Here is how you do it:



az network vpn-connection create --name MyVpnConnection --resource-group myResourceGroup --vnet-gateway1 myVpnGateway --shared-key 'mySharedKey' --local-gateway2 

Above command helps in setting up VPN Connection from azure to your chosen other cloud service provider (AWS or GCP) using the provided shared key.

Configuring VPC Peering or VNet Peering

After configuring both cloud providers, VPC Peering (AWS) and VNet Peering (Azure), it becomes seamless for both the virtual networks within the same cloud to communicate easily. For multi-cloud scenarios, you will use VPC Peering in AWS and VPN connections or Hybrid Network Models if direct peering is unavailable across cloud providers.

For VNet Peering in Azure, follow these steps:

1. Create Peering Between Azure VNets

● Copy and use this command if you want the two VNets in your azure environment to communicate with each other in a flawless manner.



az network vnet peering create --name myVNetPeering --resource-group myResourceGroup --vnet-name myVNet --remote-vnet myOtherVNet --allow-vnet-access

VPC Peering in AWS

Similarly, on AWS, VPC Peering between two VPCs is set up. The general process is:
● Create a peering connection between VPCs.
● Update route tables to allow traffic between the peered networks.
● Configure security groups and network ACLs to permit traffic.

Application Deployment Across Clouds

After you have all the necessary infrastructure ready, you can deploy your app to Azure and your secondary cloud provider (AWS or Google Cloud Platform (GCP). This process has many critical steps, helping you ensure your application functions successfully in a multi-cloud environment.

Step 1: Create and Push Docker Images

To deploy your application, we first containerize it using Docker. It’s a portable image that encapsulates your application and its dependencies for easy running consistently across various environments.

● Build the Docker Image: Create a Docker image of your app and start with that. This image serves as the foundation for your containerized deployment.



docker build -t my-app:v1 .

● Push to Azure Container Registry (ACR): Push your created image to your cloud’s container registry. That would be the Azure Container Registry for Azure.



docker tag my-app:v1 myACRRegistry.azurecr.io/my-app:v1
docker push myACRRegistry.azurecr.io/my-app:v1

● Push to AWS Elastic Container Registry (ECR): When setting up a multi-cloud deployment, you must push the Docker image to AWS ECR. It lets your application run just fine in the AWS cloud.



aws ecr get-login-password --region us-west-2 | docker login --username AWS --password-stdin .dkr.ecr.us-west-2.amazonaws.com
docker tag my-app:v1 .dkr.ecr.us-west-2.amazonaws.com/my-app:v1
docker push .dkr.ecr.us-west-2.amazonaws.com/my-app:v1

Step 2: Kubernetes Deployment Manifests

Now that those Docker images are pushed to respective registries, it’s time to build Kubernetes deployment manifests for AKS and EKS. These manifests contain what happens when you deploy your application: the replicas count it runs and the container image you’re using.

● Deployment for Azure AKS: In the YAML file, deploy your application to Azure AKS. We will tell it that we want three replicas of our application to run.



apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      containers:
      - name: my-app
        image: myACRRegistry.azurecr.io/my-app:v1
        ports:
        - containerPort: 8080

● Deployment for AWS EKS: Code a YAML manifest referencing the image hosted in the AWS ECR for easy deployment of your app on AWS EKS.



apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      containers:
      - name: my-app
        image: .dkr.ecr.us-west-2.amazonaws.com/my-app:v1
        ports:
        - containerPort: 8080

Best Practices

• Version Control: Ensure you tag your Docker images with version numbers to maintain explicit control.
• Monitoring and Logging: Use the built-in monitoring set up for both environments to monitor and log your application’s performance and any issues that may occur.
• Configuration Management: It’s time to use Kubernetes ConfigMaps and Secrets to handle your configuration settings and sensitive information safely and efficiently.
• Automated Deployments: If you think you can reasonably save time by introducing CI/CD tools (Azure DevOps, Jenkins, and GitHub actions) and reduce the chance of human error in deploying your software to different centralized clouds, maybe.

Conclusion

When deploying to multiple clouds, a business has more flexibility, scalability, and resilience. With Azure AKS and then combining that with other cloud providers like AWS, organizations can now run high-availability, robust applications everywhere.

Whether deploying for disaster recovery, regulatory compliance, or optimizing performance, multi-cloud Kubernetes ensures you are prepared for the modern cloud-native landscape. Although it seems easy to deploy multi-cloud Kubernetes Applications on Azure cloud, getting expert help to accomplish the task is advised.

Deploy your first multi-cloud Kubernetes applications with Azure AKS—partner with us by leveraging our Kubernetes Consulting Services.

Frequently Asked Questions (FAQs)

What advantages are there to multi-cloud deployments when using Azure Kubernetes Service (AKS)?

AKS is a managed Kubernetes service, which means that the user can concentrate on the application and the tasks that need to be run on the cluster while the service manages the cluster. It is very flexible and can work well with other Azure products and clouds because it is a very versatile service. After you have created the AKS cluster, use kubectl to connect it:

Why would you consider deploying your Kubernetes in a multi-cloud environment?

Increased resilience, vendor lock-in reduction, improved performance, and regulatory compliance are advantages of a multi-cloud Kubernetes deployment that holds down the workloads in multiple cloud providers.

When would one deploy Kubernetes with multiple clouds? How can we secure the communication between the Kubernetes clusters?

To secure inter-cloud communication, configure VPN connections, use network peering, and apply encryption standards like TLS. Azure’s VPN Gateway or AWS’s VPC Peering can help maintain secure cloud connections.

What tools can I use to manage costs in a multi-cloud Kubernetes environment?

Azure Cost Management, AWS Cost Explorer, and third-party tools like Kubecost are helpful for monitoring and optimizing expenses and helping manage data transfer, API call costs, and idle resources across cloud providers.