Running Containers on Azure – All Options Explained

When you think “containers on Azure,” Kubernetes often comes to mind fast. But Azure offers multiple options — some lighter, some more powerful. Let’s walk through them so you can choose wisely.

Why multiple container options matter

Every application has different operational needs.

Some run well as a single container. Others grow into dozens or hundreds of services. Choosing the wrong container platform can lead to excessive overhead — or insufficient capabilities.

Below, I group Azure’s container offerings into two categories:

• Standalone runtimes — you manage many details, but gain flexibility
• Orchestration / serverless models — Azure handles more of the plumbing

Let’s begin with the simpler end of the spectrum.

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Standalone container runtimes

Virtual Machines (VMs)

You can host Docker (or containerd, etc.) inside an Azure VM (Linux or Windows).

• Pros: Full control of OS, runtime, tools, networking
• Cons: You manage patching, scaling, high-availability, monitoring

Best for: dev/test, edge cases, middleware or legacy systems that don’t need orchestration.

Azure Container Instances (ACI)

Azure’s serverless container service. You provide the container image, and Azure runs it without you having to manage VM infrastructure. Billing is per-second for vCPU + memory.

• Fast startup, minimal infrastructure overhead
• Easy scaling and usage
• Less control over network, custom scheduling, or lower-level orchestration

ACI supports container groups, so you can run tightly coupled containers together (sharing network, storage, lifecycle).

Best for: burst workloads, scheduled jobs, lightweight microservices, or when traffic is unpredictable.

Azure App Service for Containers

Azure’s PaaS offering lets you host web apps and APIs using containers.

• Built-in features: scaling, SSL, deployment slots, monitoring
• You don’t manage VM infrastructure
• Focused on HTTP / web workloads, not ideal for all background or compute tasks

Best for: containerized web frontends, APIs, or migrating existing web apps into containers with minimal changes.

Azure Batch

When your workload is many independent, parallel tasks, Azure Batch can run containers as jobs across a pool of VMs.

• Massive scale, use of spot / low-priority VMs
• Good for stateless, partitioned workloads
• Not suited for long-lived services or tightly integrated applications

Best for: rendering, simulations, large-scale data processing, or other batch compute jobs.

Azure Functions with Custom Containers

You can package your function logic inside a container and deploy under Azure Functions.

• Lets you use custom runtimes and dependencies
• Retains event-driven scaling and pay-per-execution model
• Bound by limits of function apps (timeouts, resource limits)

Best for: event-driven microservices, background tasks, or specialized runtime needs.

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Orchestration & serverless container models

When your architecture grows, you need coordination: routing, service discovery, scaling, health checks, etc.

Azure Kubernetes Service (AKS)

Azure’s managed Kubernetes offering. You set node pools and versions; Azure manages the control plane infrastructure (upgrades, patching, etc.).

• Full Kubernetes ecosystem, high flexibility
• Excellent for microservices, complex workloads, networking control
• Steeper learning curve, operational concerns (monitoring, security, cost)

Best for: production-grade microservices, multi-environment parity, container-based enterprises.

Azure Container Apps

Container Apps fits between ACI and AKS: you gain orchestration without needing to manage Kubernetes itself.

• Scale to zero, event-driven scaling, HTTP ingress, Dapr integration
• You don’t manage nodes or Kubernetes control plane
• Less low-level control (custom scheduling, deep networking)

Container Apps is ideal for APIs, background processes, microservices without the overhead of full cluster management.

Azure Service Fabric

A mature distributed systems platform from Microsoft, able to host both containers and native services.

• Supports stateful services, lifecycle management, internal infrastructure
• Good for hybrid workloads combining containers and non-container microservices
• More niche in new container-first workloads, steeper learning curve

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How to pick in practice

Also consider:

• Cost behaviour — serverless/container runtimes often allow scale-to-zero; orchestration options may incur baseline costs.
• Operational overhead — how much do you want to manage (updates, monitoring, security)?
• Control vs simplicity — more control usually means more operational burden.

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How LDS IT Consultancy supports you

At LDS IT Consultancy, our goal is to reduce your operational risk and accelerate your cloud adoption.

• Visit our Tools page — we publish utilities, scripts, and accelerators you can use in your Azure container projects.
• Our Managed Services cover deployment, monitoring, upgrades, security, scaling, and ongoing support.

Whether you're just starting with containers or scaling a microservices architecture, we can help you pick the right Azure container model, design your environment, and operate it reliably. Reach out to us to see how we can assist.