Azure Compute: Containers

This documentation provides an in-depth guide to using container technologies within Azure Compute, covering key services and best practices for deploying, managing, and scaling your containerized applications.

Overview

Containers offer a lightweight, portable, and consistent way to package and run applications. Azure provides a robust set of services to support your containerization journey, from individual container instances to full-fledged orchestrators.

Key benefits of using containers in Azure include:

• Portability: Run your applications consistently across different environments.
• Scalability: Easily scale your applications up or down based on demand.
• Efficiency: Maximize resource utilization with lightweight isolation.
• Speed: Faster deployment and iteration cycles.

Azure Kubernetes Service (AKS)

Azure Kubernetes Service (AKS) simplifies deploying, managing, and scaling containerized applications using Kubernetes on Azure. AKS abstracts away the complexity of the control plane, allowing you to focus on your applications.

Key Features of AKS:

• Managed Kubernetes control plane
• Easy integration with Azure services (Azure Monitor, Azure Policy, Azure Active Directory)
• Built-in security and compliance
• Automated updates and scaling

Getting Started with AKS:

You can create an AKS cluster using the Azure portal, Azure CLI, or Azure PowerShell. A basic cluster can be provisioned with a few commands:

az group create --name myResourceGroup --location eastus
az aks create --resource-group myResourceGroup --name myAKSCluster --node-count 1 --enable-addons monitoring --generate-ssh-keys
        

For more advanced configurations and management, refer to the official AKS documentation.

Azure Container Instances (ACI)

Azure Container Instances (ACI) is the fastest and simplest way to run a container in Azure. ACI allows you to deploy containers without managing underlying virtual machines or orchestrators. It's ideal for simple applications, task automation, and event-driven scenarios.

When to use ACI:

• Quickly testing a container image
• Running a single containerized application
• Automating tasks with containers
• Event-driven processing

Deploying a container with ACI:

Deploying a single container is straightforward:

az container create --resource-group myResourceGroup --name myContainer --image microsoft/aci-helloworld --dns-name mycontainer
        

Explore ACI documentation for advanced use cases and networking.

Container Registries

Azure Container Registry (ACR) is a managed, private Docker registry service that stores and manages your private Docker container images and related artifacts. ACR is built on Docker Registry 2.0 and integrates with other Azure services.

Key capabilities of ACR:

• Securely store and manage container images
• Integrate with Azure Kubernetes Service (AKS) and Azure Container Instances (ACI)
• Geo-replication for high availability and low latency
• Content trust and vulnerability scanning

Creating an ACR:

Provisioning a registry is done via the Azure CLI:

az acr create --resource-group myResourceGroup --name myRegistry --sku Basic --location eastus
        

Learn more about ACR features in the official ACR documentation.

Best Practices for Azure Containers

To ensure efficient, secure, and scalable container deployments on Azure, consider the following best practices:

• Optimize Docker Images: Use minimal base images, multi-stage builds, and efficient layer caching.
• Security: Regularly scan images for vulnerabilities, use Azure Security Center, and implement least privilege for container access.
• Networking: Design your container networking thoughtfully, especially for microservices architectures using AKS.
• Monitoring and Logging: Implement comprehensive monitoring using Azure Monitor and centralize logs for easier debugging.
• CI/CD Integration: Automate your build, test, and deployment pipelines using Azure DevOps or GitHub Actions.
• Resource Management: Set appropriate CPU and memory requests/limits for your containers to ensure predictable performance and efficient resource allocation.