Kubernetes and Container Orchestration on Azure AKS and AWS EKS

Container orchestration has moved from the cutting edge to the mainstream. According to the CNCF Annual Survey 2024, 84% of organisations are now using or evaluating Kubernetes in production, up from 58% just three years ago. For Australian businesses looking to modernise application delivery, Kubernetes on managed platforms like Azure Kubernetes Service (AKS) and AWS Elastic Kubernetes Service (EKS) offers the scalability, resilience, and operational efficiency that monolithic architectures simply cannot match.

But Kubernetes is not a magic bullet. It introduces complexity that, if mismanaged, can erode the very benefits it promises. This guide provides a practical, Australian-focused overview of container orchestration -- from fundamentals through to production-ready deployment strategies, security hardening, and cost optimisation.

Container Fundamentals: Why Containers Matter

Before diving into orchestration, it is worth grounding the discussion in what containers actually solve. A container packages an application and all its dependencies -- runtime, libraries, configuration files -- into a single, portable unit that runs consistently across any environment.

Unlike virtual machines, containers share the host operating system kernel, making them dramatically lighter. A single server that might run 10-15 virtual machines can comfortably host hundreds of containers. This density translates directly into cost savings of 40-60% on compute resources, according to Gartner's 2024 Infrastructure and Operations report.

Docker remains the most widely used container runtime, though alternatives like containerd and CRI-O are gaining traction in production Kubernetes environments. The key benefits of containerisation include:

• Consistency across environments -- Eliminate "it works on my machine" problems by packaging applications identically for development, staging, and production
• Rapid deployment -- Containers start in seconds rather than minutes, enabling faster scaling and recovery
• Resource efficiency -- Higher density per host compared to traditional virtual machines
• Microservices enablement -- Decompose monolithic applications into independently deployable, scalable services
• Developer productivity -- Standardised build and deployment pipelines reduce friction between teams

Kubernetes Overview: The Orchestration Layer

Running a single container is straightforward. Running hundreds or thousands of containers across multiple hosts -- ensuring they are healthy, correctly networked, automatically scaled, and recoverable from failure -- requires orchestration. Kubernetes (often abbreviated as K8s) is the industry-standard platform for this purpose.

Originally developed by Google and now maintained by the Cloud Native Computing Foundation (CNCF), Kubernetes provides:

• Automated scheduling -- Places containers on the most appropriate nodes based on resource requirements and constraints
• Self-healing -- Automatically restarts failed containers, replaces unhealthy nodes, and reschedules workloads
• Horizontal scaling -- Scales container replicas up or down based on CPU, memory, or custom metrics
• Service discovery and load balancing -- Provides internal DNS and distributes traffic across container replicas
• Rolling updates and rollbacks -- Deploys new versions progressively with zero-downtime, and rolls back automatically if health checks fail
• Secret and configuration management -- Manages sensitive data and application configuration independently from container images

Cluster Architecture

A Kubernetes cluster consists of a control plane (which manages the cluster state and scheduling decisions) and worker nodes (which run the actual containerised workloads). In managed services like AKS and EKS, the cloud provider operates the control plane, freeing your team to focus on application deployment and operations rather than cluster maintenance.

Key cluster components include the API Server (the front door for all cluster operations), etcd (the distributed key-value store holding cluster state), the Scheduler (which assigns pods to nodes), and the Kubelet (which runs on each node and manages container lifecycle).

AKS vs EKS: Choosing the Right Managed Kubernetes Platform

Both Azure AKS and AWS EKS provide managed Kubernetes with automatic control plane management, but they differ in integration depth, pricing, and ecosystem alignment. For Australian organisations, the choice often comes down to existing cloud investments and identity infrastructure.

Deployment Strategies for Production Kubernetes

How you deploy updates to containerised applications directly impacts availability, risk, and rollback speed. Kubernetes supports several deployment strategies, each suited to different risk tolerances and workload types.

Rolling Deployments

The default Kubernetes strategy, rolling deployments gradually replace old pods with new ones. At no point is the application fully unavailable. You control the pace with maxSurge (how many extra pods can exist during the update) and maxUnavailable (how many pods can be offline simultaneously). This is the safest default for most workloads and requires no additional infrastructure.

Blue-Green Deployments

In a blue-green deployment, you run two identical environments -- "blue" (current production) and "green" (new version). Once the green environment passes all health checks and validation, traffic is switched from blue to green in a single operation. This provides instant rollback capability (simply switch traffic back to blue) but requires double the infrastructure during transitions. Blue-green is ideal for critical applications where zero-downtime and instant rollback are non-negotiable.

Canary Deployments

Canary deployments route a small percentage of traffic (typically 5-10%) to the new version while the majority continues on the current version. If metrics -- error rates, latency, business KPIs -- remain healthy, traffic is progressively shifted to the new version. Tools like Flagger and Argo Rollouts automate canary analysis and promotion. This is the gold standard for high-traffic applications where even brief degradation carries significant business impact.

Monitoring and Observability

Kubernetes clusters generate an enormous volume of metrics, logs, and traces. Without proper observability, troubleshooting issues in a distributed containerised environment becomes exponentially harder than in traditional infrastructure.

Azure Monitor and Container Insights

For AKS clusters, Azure Monitor Container Insights provides native integration with no additional agents required. It collects container-level CPU, memory, and network metrics; node health and resource utilisation; pod restart counts and scheduling failures; and integrates with Azure Log Analytics for log querying via KQL (Kusto Query Language).

CloudWatch Container Insights and Amazon Managed Prometheus

For EKS clusters, CloudWatch Container Insights provides similar capabilities. Additionally, Amazon Managed Service for Prometheus offers a fully managed, Kubernetes-native monitoring solution compatible with the Prometheus ecosystem -- including Grafana dashboards for visualisation. This is particularly valuable for teams already familiar with Prometheus and PromQL.

Regardless of platform, we recommend implementing the three pillars of observability: metrics (Prometheus/Azure Monitor), logs (Fluentd or Fluent Bit to a centralised platform), and traces (OpenTelemetry to Jaeger, Zipkin, or Azure Application Insights).

Security: Hardening Your Kubernetes Clusters

Kubernetes security is a shared responsibility. The managed service provider handles control plane security, but workload security, network policies, and image integrity are your responsibility. The Australian Cyber Security Centre (ACSC) has published guidance on securing containerised environments that aligns with Essential 8 principles.

Pod Security Standards

Kubernetes Pod Security Standards (PSS) define three levels -- Privileged, Baseline, and Restricted. All production workloads should run at Baseline as a minimum, with sensitive workloads at Restricted. This prevents containers from running as root, accessing the host network, or escalating privileges.

Network Policies

By default, all pods in a Kubernetes cluster can communicate with all other pods. Network policies act as firewall rules within the cluster, restricting pod-to-pod traffic to only what is necessary. Implement a default-deny policy and explicitly allow required communication paths. Both Azure CNI and AWS VPC CNI support Kubernetes network policies natively.

Image Scanning and Supply Chain Security

Every container image deployed to your cluster should be scanned for known vulnerabilities. Use Microsoft Defender for Containers (AKS) or Amazon ECR image scanning (EKS) to automatically scan images in your registry. Implement admission controllers (such as OPA Gatekeeper or Kyverno) to block deployment of images with critical vulnerabilities or from untrusted registries.

Cost Optimisation for Kubernetes Workloads

Kubernetes can be surprisingly expensive if not managed carefully. The most common cost pitfall is over-provisioning -- requesting more CPU and memory for pods than they actually use. Gartner estimates that 60% of Kubernetes resources are wasted due to over-provisioning.

Practical cost optimisation strategies include:

• Right-size resource requests and limits -- Use tools like Vertical Pod Autoscaler (VPA) or Goldilocks to analyse actual resource usage and right-size pod requests
• Use spot/preemptible nodes -- For fault-tolerant workloads (batch processing, CI/CD runners, stateless services), Azure Spot VMs and AWS Spot Instances offer discounts of 60-90%
• Cluster autoscaling -- Enable the Kubernetes Cluster Autoscaler to automatically add or remove nodes based on pending pod demands, preventing idle node costs
• Namespace resource quotas -- Prevent individual teams from consuming excessive cluster resources by enforcing quotas per namespace
• Reserved instances for baseline -- Use Azure Reserved VM Instances or AWS Savings Plans for the baseline node count that runs 24/7, and spot instances for burst capacity

When Kubernetes Is Overkill

Not every workload needs Kubernetes. If your organisation runs fewer than 10 microservices, has a small development team (under 5 engineers), or operates applications with predictable, steady traffic patterns, simpler alternatives may deliver better ROI:

• Azure Container Apps or AWS App Runner -- Serverless container platforms that abstract away all cluster management. Ideal for simple web applications and APIs.
• Azure App Service or AWS Elastic Beanstalk -- Platform-as-a-Service options for web applications that do not require container-level control.
• AWS Fargate -- Serverless compute for containers without managing the underlying infrastructure. Suitable for workloads that do not need the full Kubernetes API.
• Docker Compose -- For small teams running a handful of containers on a single host, Docker Compose provides simplicity that Kubernetes cannot match.

The decision to adopt Kubernetes should be driven by operational requirements -- multi-team development, microservices at scale, multi-cloud portability, or complex deployment patterns -- not by industry hype.

How Precision IT Supports Your Container Strategy

As a Microsoft Solutions Partner and AWS Select Partner, Precision IT brings deep expertise in container orchestration across both major cloud platforms. Our container and Kubernetes services include:

• Container readiness assessments -- Evaluate which workloads benefit from containerisation and which are better served by alternative architectures
• Cluster architecture design -- Design production-ready AKS or EKS clusters with security, networking, and observability built in from day one
• CI/CD pipeline integration -- Build automated deployment pipelines with Azure DevOps, GitHub Actions, or AWS CodePipeline for containerised workloads
• Security hardening -- Implement pod security policies, network policies, image scanning, and runtime threat detection aligned with Essential 8 and ISO 27001
• 24/7 monitoring and support -- Our Australian-based operations centre provides round-the-clock monitoring, incident response, and performance optimisation for your Kubernetes environments

Whether you are containerising your first application or managing complex multi-cluster deployments, our team provides the expertise and ongoing support to ensure your container strategy delivers measurable business value.

Ready to explore container orchestration for your business? Learn more about our DevOps and automation services, or book a free consultation with our cloud-native architecture team.