Deploy AKS Automatic (Preview): A Beginner’s Guide

Introduction

Azure Kubernetes Service (AKS) Automatic (Preview) offers a streamlined, highly automated way to deploy and manage Kubernetes clusters suited for cloud-native applications. Designed for practitioners like Sreekantha Gujjar’s community of DevOps engineers, this guide walks you through creating a production-ready AKS cluster with minimal manual setup, leveraging its fully managed node pools, integrated monitoring, and automation features.

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Why Choose AKS Automatic (Preview)?

AKS Automatic simplifies your Kubernetes management by handling node provisioning, scaling, upgrades, and security out-of-the-box. It aligns with future-ready cloud-native strategies by promoting automation, optimal resource utilization, and built-in safeguards.

Prerequisites

• Azure CLI installed (version supporting AKS 2.36+)
• An Azure account with permissions to create resources
• Basic understanding of Kubernetes concepts

Step 1: Create an AKS Automatic Cluster

Azure offers a quickstart to deploy your first AKS Automatic cluster:

az aks create --resource-group <ResourceGroup> --name <ClusterName> \
  --enable-managed-identity \
  --kubernetes-version latest \
  --enable-addons monitoring \
  --nodepool-name default \
  --node-count 3 \
  --auto-upgrade-channel rapid \
  --enable-cluster-autoscaler \
  --min-count 1 \
  --max-count 10 \
  --enable-AKS-Auto

Key points:

• Managed identity: Handles permissions securely.
• Monitoring: Uses integrated Prometheus, Grafana, and Container Insights.
• Auto-upgrade & autoscaling: Clusters auto-upgrade on update channels, with seamless scaling based on workload.

Step 2: Leverage Fully Managed Node Pools

AKS Automatic key feature is nodes managed via Node Autoprovisioning:

• Node pools are auto-created, scaled, and replaced without manual intervention.
• Autoscaling (Horizontal Pod Autoscaler, KEDA, VPA) intelligently adjusts workloads.

Example: Enable autoscaling during creation:

--enable-cluster-autoscaler --min-count 1 --max-count 10

You can also configure the cluster for automatic node repairs and scheduled maintenance for minimal disruptions.

Step 3: Configure Integrated Monitoring and Logging

Monitoring is preset using Azure Monitor tools:

• Container Insights offers logs, metrics, and health insights.
• Managed Prometheus collects detailed metrics.
• Grafana dashboards are available for visualization.

To verify setup:

az aks browse --resource-group <ResourceGroup> --name <ClusterName>

This opens the observability dashboard, giving you visibility into cluster health and workload metrics.

Step 4: Minimal Manual Configuration for Production-Ready Environment

AKS Automatic (Preview) presets many best practices:

• Secure workload identity with Entra Workload ID.
• Use Azure RBAC for fine-grained permissions.
• Configure ingress controllers such as managed NGINX with Azure DNS integration.
• Set up egress via managed NAT gateway for outbound traffic.
• Use policies for deployment safeguards ensuring best practices.

Advanced configurations include private clusters with API server virtual network integration, custom virtual networks, or Istio for service mesh features, which can be enabled as per your needs.

Conclusion

Deploying an AKS cluster using Automatic (Preview) offers a robust, automated foundation for cloud-native applications. It reduces manual overhead, promotes best practices, and ensures your environment is scalable, secure, and future-ready. This guide provides foundational steps, with an emphasis on leveraging automation features for real-world production workflows.

By adopting AKS Automatic, Sreekantha Gujjar’s community of practitioners and DevOps engineers can focus on innovating rather than managing infrastructure, aligning perfectly with modern DevOps and cloud-native objectives.

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Explore more: For detailed commands and feature configurations, visit Azure AKS docs.