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ACA vs AKS vs ACI: Which Is Best For Containers in Azure?

When you move away from virtual machines (VMs) to containers, you must decide between available container services.

Microsoft Azure, as one of the leading cloud providers, offers many technologies and services to help you build, run, and manage containerised applications such as:

Azure Container Apps (ACA)
Azure Kubernetes Service (AKS)
Azure Container Instances (ACI)

In this article, we’ll compare them so you can pick the right service and start building containerised apps in Azure.

Author

Niels Kroeze IT Business Copywriter

Reading time 14 minutes Published: 18 September 2025

ACA vs AKS vs ACI Comparison

The table below gives you a quick side-by-side look at the key differences between Azure Container Apps (ACA), Azure Container Instances (ACI), and Azure Kubernetes Service (AKS) to help you compare the key features and use cases.

Feature	Azure Container Apps (ACA)	Azure Kubernetes Service (AKS)	Azure Container Instances (ACI)
Complexity	Low – Abstracts Kubernetes complexity for a simplified experience	Moderate to high – Full control over Kubernetes environment with complexity	Very Low – No orchestration, run containers directly
Scalability	Autoscaling based on events, scales to zero	Granular scaling options, supports custom metrics, scales large workloads	Simple scaling based on container resource needs
Management	Fully managed, serverless, no cluster management required	Requires management of cluster nodes, updates, and scaling	Fully managed, but lacks orchestration and advanced management
Control	Limited – No access to underlying infrastructure or Kubernetes settings	Extensive – Full control over Kubernetes clusters, networking, and security	Minimal – Basic control over container configuration
Pricing	Serverless pricing model, pay for CPU and memory usage	Costs include underlying VM resources, higher for complex workloads	Pay-as-you-go for container runtime, per-second billing for CPU and memory
Billing	Based on container instances or requests	Per-second billing	Per-second billing
Features	Built-in ingress, autoscaling with KEDA, integrates with DAPR for microservices	Supports service mesh, load balancing, custom resource definitions	Basic container execution without orchestration
Security	Basic security features, suitable for most common scenarios	Advanced security features, including network policies and RBAC	Minimal security options
Ecosystem & integrations	Good integration with Azure services, but limited extensibility	Broad ecosystem, integrates with many third-party tools and services	Limited ecosystem, focused on running containers
Best for	Developers needing simplicity, microservices, and event-driven workloads	Enterprises needing full Kubernetes capabilities for large-scale, complex deployments	Short-lived tasks, simple jobs, or isolated workloads

Each of these technologies has its own use cases, benefits, and trade-offs, depending on your needs and preferences.

Let’s briefly go through them:

Azure Container Apps

Azure Container Apps (ACA) is a fully managed serverless container platform for running microservices and containerised apps. ACA runs on top of AKS, but is fully managed (the infrastructure) by Microsoft.

Since ACA is one of Microsoft’s fully managed PaaS services, you don’t get direct access to the Kubernetes API like you do in AKS. This makes it ideal if you’re not fluent in Kubernetes but still want the benefits of container-based deployment.

ACA handles medium-complexity apps, supports integration and scaling, and removes the overhead of infrastructure management.

Use cases of ACA

Microservices architectures: Microservices requiring scaling, integration, and state management.
Event-driven apps: Event-driven apps with Logic Apps as well as Event Hub, where the on-demand containers can be run based on different events.
Web applications: Deploy web apps with features like custom domains, TLS, routing, and built-in authentication, which are all managed and configured for you.
Background processing: Run worker processes or other background tasks continuously, without the overhead of full VMs or Kubernetes setup.
Hosting APIs: You can expose public API endpoints with ACA, making your services accessible over the internet with built-in scaling and traffic management.

Features and Limitations of ACA

Features	Limitations
Container Apps environment: ACA apps run inside an isolated environment, allowing you to deploy apps into the same virtual network (or bring your own VNet), share logging via a single Log Analytics workspace, and choose between public (external) or internal-only endpoints.	No support for Windows containers: ACA supports only Linux containers for now. If your workload needs Windows containers or legacy apps, ACA won’t move the needle.
Revision-based deployment: Changing settings like container image or scaling creates a new, immutable revision. You can run multiple revisions and route traffic for blue-green deployments or A/B testing.	Cold starts: As with many container services, ACA also has cold starts. There are workarounds, like setting your replicas to one or more. Mind you, this will incur costs.
Multiple scaling options: Scale by using triggers such as HTTP, Events, CPU or Memory usage or KEDA based triggers (no knowledge required).	Resource constraints: If you have GPU requirements or need more intensive compute, ACA won’t be a good fit.
Scale to zero: When there's no traffic to your application, and you're fine with some kind of delay, you can scale down to zero to avoid costs, as nothing is running.	No direct access to Kubernetes API: You don’t get direct access to the Kubernetes API. That limits advanced customisation and direct control over Kubernetes-native resources like CRDs, namespaces, or custom networking policies.
Scaling and ingress: Supports multi-replica scaling per revision with automatic load balancing. Offers full Ingress features: custom domains, HTTPS, TLS termination, and advanced routing.	Manual Application Insights setup required: There’s no built-in support for auto-instrumenting your code. Instead, you must manually add and configure Application Insights SDKs in your apps.
Secrets and Identity: Supports managed identity to access Azure Key Vault. Direct secret sync from Key Vault isn’t supported but you can store secrets as key-value pairs.	No third-party log shipping: Exporting logs isn’t supported yet.
Integrated monitoring and observability: Provides log streaming, container console access, Azure Monitor metrics and logs, alerts, and OpenTelemetry tracing.

ACA Pricing

Azure Container Apps has two pricing plans: Consumption plan and Dedicated plan.

Consumption plan: You get charged per second based on the virtual CPU and the memory your apps use, plus the number of requests, which is $0.40 per million requests. You get 180,000 vCPU-seconds, 360,000 GiB-seconds, and 2 million requests free monthly. After that, you only pay for what you use.
Serverless GPU: Similar to Consumption Plan, but with GPU support (e.g. NC T4 v3, NC A100 v4). You get billed per-second for GPU usage + standard vCPU/memory rates.
Idle usage pricing: You can set autoscaling to zero so you’re not charged when idle.
Dedicated plan: You get charged per hour based on the virtual CPU and memory.

Azure Kubernetes Service (AKS)

Azure Kubernetes Service (AKS) is a fully managed Kubernetes service that provides full Kubernetes orchestration for Azure. Meaning that, you have full control over the underlying infrastructure. In AKS, Microsoft manages the control plane while you have to manage and deal with the entire cluster.

Use cases of AKS

Enterprise-grade applications: Deploy multi-tiered microservices with full control over networking, security policies, and integration. Especially great for enterprise-grade applications with high complexity.
Service discovery and load balancing: AKS is an excellent fit for scenarios needing service discovery and load balancing
Hybrid cloud deployment: Integrate clusters from on-prem or other clouds and run AKS alongside on-prem or other cloud environments using tools like Azure Arc.
Compliance and regulatory requirements: When you require complete control over data location, audit logs, and network policies or require private clusters for sensitive workloads, AKS is the best choice.
GPU and high-performance computing (HPC): Need GPU acceleration for ML, AI, or compute-heavy tasks? AKS supports GPU node pools with autoscaling for high-performance workloads.
Migrating existing apps: Run Windows containers alongside Linux in the same cluster using Windows-compatible node pools – ideal for migrating legacy apps.

Features and Limitations of AKS

Features	Limitations
Full access and control to the Kubernetes API: Deploy, manage, and customize clusters, including namespaces and resource allocation.	Complexity: You must understand the main components and how they work, which may take some time to learn.
Endless scaling possibilities: You can scale with the Horizontal Pod Autoscaler (HPA), set minimum and maximum limits for node pools, use the cluster autoscaler, KEDA scaling, etc.	Operational overhead: You’re responsible for node pools, upgrades, bringing your own ingress, networking, scaling rules, and availability settings. AKS handles the control plane, but the rest is yours.
Free control plane: In AKS, you can make use of the free control plane (without SLA, not suited for production environments).	Cold starts on scale-out: Scaling takes time, especially if you're using VM node pools. Pods won’t be instantly available under high load.
Unmatched integrations with Azure Services: Unmatched integrations with other Azure services. Integration with storage, networking, monitoring and security is flawlessly integrated within Kubernetes.	Networking complexity: Private clusters, custom VNETs, and secure ingress/egress configurations often require deep Azure networking expertise.
Private and public cluster support: You can deploy in either a private environment where all nodes run in an Azure VNet or in public clusters via the internet.
Plenty of monitoring and observability tools: There are many monitoring and observability tools in AKS such as the built-in Container Insights, plus support for Prometheus and Grafana for detailed metrics, logs, and live events.

AKS Pricing

In AKS, pricing is based on the pay-as-you-go model. Also, you can buy reservations using either an Azure Savings Plan or Azure Reservations (since the virtual machines are involved for the worker nodes). For non-critical workloads, you can achieve significant savings using Azure Spot VMs.

For the control plane:

Cluster per hour: $0.10 (Standard tier)
Premium tier: ~$0.60

You also pay for the virtual machines for the worker nodes. Learn more about AKS Pricing.

Azure Container Instances (ACI)

ACI is the simplest way to deploy a container in Azure. Using this service, you can spin up on-demand containers quickly.

Azure Container Instances (ACI) is a serverless container service that allows you to run your containers without managing the underlying infrastructure. Microsoft handles the underlying infrastructure, including secure isolation.

ACI Use Cases

Data processing jobs: ACI is a solid choice for short-lived or batch jobs, tasks and automation. For instance, scheduled nightly processing tasks that don’t require an always-on infrastructure.
Event-driven workloads: Pair ACI with services like Azure Logic Apps to trigger containers in response to events; perfect for occasional or ad-hoc jobs.
Bursting from AKS: When your AKS cluster hits capacity, ACI can step in to handle the overflow. This elastic bursting lets you meet demand without overprovisioning your AKS cluster.
In scripts or DevOps pipelines: ACI is widely used in scripts or DevOps pipelines (Azure Bicep or PowerShell) where it spins up just long enough to do a job and then shuts down.

Features and Limitations of ACI

Features	Limitations
No orchestrator needed: No need to manage Kubernetes. You just point to your container image, say where the image is coming from, and Azure will spin up the container in seconds.	No support for native autoscaling: Although technically you can deploy multiple containers for scale, you’ll still have to orchestrate it by yourself.
Live logs: Once ACI is running, you can check live logs. If your application outputs logs to STDOUT, you’ll see them directly in the portal, making troubleshooting pretty easy.	No built-in features: Think about certificate management, ingress controllers, DNS handling, or reverse proxies.
Interactive shell access: You can connect to the container from the portal, run commands, and interact as needed.	Missing built-in features: Lacks built-in support for ingress controllers, certificate management, DNS, and reverse proxies—features typically found in AKS or ACA.
Hyper-V Isolation: Each container instance runs in a lightweight Hyper-V VM, which gives process-level and kernel-level isolation.	Limited deployment capabilities: There’s no support for revision control, versioning, or environment separation, making ACI less suitable for complex or long-running applications.
Fast start-ups: Can pull and run your container image quickly, and you can access its endpoint immediately once it’s up. If you’re using it for API endpoints, websites, or other live workloads, it’ll be accessible right away.
Flexible sizing: You can define exactly how many CPUs and how much memory the container instance should use (like if it’s 2 vCPUs and 4 GB of RAM or another configuration).
Languages: Orchestrate container creation and deletion on the fly using Azure CLI, PowerShell, or SDKs in almost any language; C#, Java, Python – whatever your pipeline supports.
Persistent storage options: If you need to retain data, you can connect it to an Azure Storage Account, access a blob or mount external volumes to keep static data outside the container.

ACI Pricing

Pricing in Azure Container Instances is based on the CPU and memory you allocate. Billing starts as soon as the first container image is pulled. If you run multiple containers in a container group, charges begin as soon as the first container starts. Billing stops once all containers in the group fully shut down.

ACA vs AKS vs ACI: Which one should you choose when?

Diagram comparing Azure Container Apps (ACA), Azure Kubernetes Service (AKS), and Azure Container Instances (ACI) for container usage.

When to use ACA?

ACA is a great fit if:

You don’t want to deal with the complexity of managing or securing a cluster (like in AKS)
You don’t need low-level infrastructure control

ACA is a cleaner and simpler alternative to AKS or ACI. Most of the setup is handled by Microsoft, so you only have to focus on your application. It's a strong fit for small teams, mainly composed of developers who need to build and deploy microservices without relying on an infrastructure team.

When not to use ACA?

While ACA is great for most container workloads, there are cases where it may not be the right fit. Think about:

Windows containers: Only supports Linux containers. If your app needs Windows workloads, use AKS instead.
Control and access to Kubernetes API: If you need granular control over workloads, direct access to the Kubernetes API, or want to manage custom controllers and CRDs, ACA won’t work.
Scaling limits: While it can scale fast, AKS might be better if you need high-scale workloads without replica limits.
Resource constraints: Not suitable for workloads requiring high compute power or GPU acceleration.
Limited observability: Not the best for deep monitoring or more advanced observability features.

When to use AKS?

AKS is recommended when:

Running containers across multiple platforms (cloud, on-prem)
Having complex enterprise-level apps with service mesh and load balancing
You prefer access and control to the full Kubernetes API and configuration
Custom networking is important
You have Windows workloads
You have strict compliance or security needs
You want multi-node scaling control
You need GPU workloads

As long as your team has experience working with Kubernetes as an orchestrator (and you know what you are doing), AKS is the best option available in the market because of its capabilities.

There are no limitations regarding scaling or the use of GPUs; you simply get way more flexibility in what you can do, and you can go beyond. Even better, you get full access to the Kubernetes API, which gives you granular control over deployments, configuration, and how you manage resources across your cluster.

When not to use AKS?

AKS can run workloads suited for ACA and ACI, but it introduces additional complexity and operational overhead.

Let’s say you want to use KEDA on AKS. Then, you’d have to install it by yourself. In general, if you want to scale, you must think about: “How many nodes do I have? What resources do I have? What are the options I have to scale?”.

Again, if managing the environment is a downside for you, whether because of a lack of resources or insufficient Kubernetes expertise, running AKS (yourself) might not be ideal.

But that’s where AKS control by Intercept comes in.

AKS Control: a fully managed Kubernetes solution by Intercept

We simplify your Kubernetes, enhance security, and provide expert support. From containerisation to AKS cluster management, we manage setup, scaling, and maintenance, optimising performance so you can grow your business with ease.

Learn more about AKS control!

When to use ACI?

If you're running a very basic application or event-driven application, ACI is recommended.

ACI is ideal for:

Fast, disposable workloads
Simple container jobs
Automation tasks
CI/CD integration.

When not to use ACI?

While ACI can be a quick and powerful solution, it isn’t meant for every workload. Do you need something that runs continuously or autoscaling and load balancing? Then ACI isn’t the best fit.

For those needs, Azure Kubernetes Service (AKS) or App Service might be your best bet. ACI is simply not made for 24/7 web apps or long-running frontend services. It is specifically for quick and short-lived applications.

Closing thoughts

We have discussed how different services in Azure can help you go cloud native with containers. ACA, AKS, and ACI each offer unique strengths, and the best choice depends on your workload, team expertise, and operational preferences.

Evaluate your needs carefully, and consider how each service integrates with your existing Azure ecosystem. The right choice will empower your team to build, scale, and innovate with confidence.

Get in touch with us!

Are you looking for the best containerised solution in Azure? We at Intercept, as Azure Expert MSP, can help you make the best choice. Don't hesitate to contact us!

contact@intercept.cloud +31 (0) 38 20 22 085

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