What Is Azure Kubernetes Service (AKS)?
Azure Kubernetes Service (AKS) is a fully managed Kubernetes container orchestration service offered by Microsoft Azure. It enables customers to deploy, manage and scale containerized applications in a cluster of virtual machines (VMs) running on Azure.
AKS simplifies the deployment and management of Kubernetes clusters by handling many of the complex tasks such as provisioning, scaling, and patching of the infrastructure. AKS integrates with other Azure services, including Azure Active Directory, Azure Container Registry, Azure Monitor, and Azure Policy, to provide a comprehensive solution for deploying and managing containerized applications.
With AKS, users can create and manage Kubernetes clusters in just a few clicks, and then deploy and manage containerized applications in those clusters using the Kubernetes command-line interface (CLI) or a web-based dashboard. AKS also offers features such as automatic scaling, self-healing, and rolling updates, making it easy for customers to manage the availability and scalability of their applications.
In this article:
- Azure Kubernetes Service Pricing Model Explained
- Optimizing Azure Kubernetes Service Costs
Azure Kubernetes Service Pricing Model Explained
Azure Kubernetes Service offers a flexible pricing model that allows users to choose the best pricing option for their workloads.
AKS offers a free tier that is suitable for small-scale testing and development, and it includes access to basic features such as automatic updates, monitoring, and logging. This tier is available for up to 12 months and includes a free grant of $200 credit to use within 30 days. When users exhaust this credit, they move onto the pay-as-you-go pricing model.
The free tier is useful for trialing or starting out with AKS, but is not suitable for large, long-term projects. For that, users may need to look into the pricing in the Standard tier or the other options outlined below.
AKS also offers a pay-as-you-go pricing model, where users pay only for the resources they use. This model is suitable for workloads that have variable resource requirements or are deployed for short periods. Users are charged based on the number of nodes and the virtual machine (VM) size, as well as for any additional services they use, such as Azure Load Balancer or Azure Virtual Network.
Azure offers a service level agreement (SLA) guaranteeing 99.95% uptime for clusters in an Availability Zone and 99.9% for other clusters. The fee is $0.10 per hour per cluster. Despite its flexibility, this option is the most expensive pricing plan in Azure, so it is only useful for unpredictable workloads and short-term spikes.
Reserved instance pricing allows users to commit to a one-year or three-year term for their AKS resources, in exchange for a lower price. Users can save over 72% compared to pay-per-use pricing by committing to reserved instances. This model is suitable for workloads that have predictable resource requirements over a long period.
For example, users who know in advance how many VMs and storage resources they’ll need over the next three years can purchase reserved instances. However, this model isn’t suitable for workloads with unknown or changeable requirements, as it could lock the user into paying for unnecessary resources.
Spot virtual machines (VMs) are a cost-saving option for AKS users that allow them to run workloads on spare Azure capacity at a discounted price. Spot VMs are available at up to a 90% discount compared to pay-as-you-go pricing. However, the availability of spot VMs is not guaranteed and may be interrupted at any time if Azure needs the capacity for other workloads. Spot VMs are suitable for workloads that are not critical and can tolerate interruptions.
The main drawback with Spot capacity is that Azure can terminate the spot virtual machine instances at any time with short notice (just 30 seconds). Thus, if used for production workloads, there should be an automation mechanism in place to handle disruptions.
Azure Savings Plans were introduced in late 2022 and are available for a variety of compute services, including Azure Kubernetes Service. With Savings Plans, customers commit to spending a fixed hourly amount for one or three years. Compared to pay-as-you-go pricing, Savings Plans can help organizations save up to 65% on their compute spend.
One particular advantage of Savings Plans is that they maximize flexibility by allowing customers to apply the commitment across multiple services. In other words, that spend can be used for AKS or for other types of compute, such as virtual machines, Azure SQL Database, Azure Cosmos DB, and more.
Comparison of AKS Pricing Options
Here is a basic comparison between the AKS pricing tiers:
|Savings Compared to Pay-As-You-Go
|Offers basic features and includes a free grant of $200 credit for 30 days.
|Small-scale testing and development.
|Not suitable for large, long-term projects.
|Users pay only for the resources they use, based on the number of nodes, VM size, and additional services.
|Workloads with variable resource requirements or short-term deployments.
|Most expensive option.
|Users commit to a one-year or three-year term for AKS resources in exchange for a lower price.
|Workloads with predictable resource requirements over a long period.
|Not suitable for workloads with unknown or changeable requirements.
|Run workloads on spare Azure capacity at a discounted price.
|Non-critical workloads that can tolerate interruptions.
|Up to 90%
|Availability not guaranteed, VMs can be terminated at any time with short notice.
|Commit to spend a fixed hourly amount for 1 or 3 years and unlock lower prices until you reach your hourly commitment.
|Dynamic workloads while accommodating for planned or unplanned changes.
|Up to 65%
|Might not offer the level of discount that RIs can offer for more predictable workloads.
Here is an overview of the cost-saving options available for AKS:
|1-Year Reserved Instances
|3-Year Reserved Instances
|Predictable costs, monthly payments available. Suitable for consistent usage requirements.
|Useful for long-term, continuous workloads.
|Leverage Azure’s unused capacity. Suitable for interruptible workloads like batch processing and machine learning.
|Fixed hourly spend over one or three years, useful for dynamic workloads where pay-as-you-go pricing would result in fluctuating costs.
|Approximately 50% savings compared to pay-as-you-go
|Approximately 65% savings compared to pay-as-you-go
|Up to 90% savings compared to pay-as-you-go
|Up to 65% savings compared to pay-as-you-go
5 Ways to Optimizing Azure Kubernetes Service Costs
Here are some tools and features that can help optimize costs on AKS.
1. Rightsizing Resources
Rightsizing pods or containers is the process of adjusting the resources allocated to a container to match its actual resource requirements. This optimization can reduce AKS costs by avoiding overprovisioning and allowing for more efficient use of resources. By monitoring container resource usage and adjusting the container limits and requests accordingly, users can prevent waste and optimize resource utilization, leading to cost savings in the long run.
2. Dynamic Autoscaling
Dynamic autoscaling is a feature of AKS that allows the automatic adjustment of the number of nodes in a cluster based on resource utilization. Fine-tuning Horizontal Pod Autoscaler (HPA) and cluster autoscaling can help reduce costs by ensuring that the cluster is scaled up or down efficiently to match the workload demands, preventing overprovisioning and reducing idle resources.
3. Selecting the Rights VM Types
Azure offers various VM types, including:
- General Purpose
- Compute Optimized
- Memory Optimized
- Storage Optimized
- High-Performance Compute
Choosing the right VM type can help optimize Azure costs by matching the resource requirements of the workload to the capabilities of the VM. A VM type with a lower cost-per-performance ratio can also help reduce costs.
4. AKS Node Pools
Node pools are logical groupings of Azure Virtual Machines (VMs) that are used to run your Kubernetes nodes. You can create multiple node pools with different VM sizes to meet the needs of your applications. By using node pools, you can scale your infrastructure according to the needs of your applications and optimize your costs by using the most cost-effective VM sizes.
5. AKS Cost Management Tools
Azure provides several cost management tools that you can use to monitor and optimize your AKS costs. These tools include Azure Cost Management and Azure Advisor. Azure Cost Management provides cost analysis and optimization recommendations for your AKS resources, while Azure Advisor provides best practices and recommendations for optimizing your AKS infrastructure.
Ensure availability and optimize AKS with Spot by NetApp
Spot by NetApp’s portfolio provides hands-free Kubernetes optimization. It continuously analyzes how your containers are using infrastructure, automatically scaling compute resources to maximize utilization and availability utilizing the optimal blend of spot, reserved, and pay-as-you-go compute instances as well as Savings Plans.
- Dramatic savings: Access spare compute capacity for up to 91% less than pay-as-you-go pricing
- Cloud-native autoscaling: Effortlessly scale compute infrastructure for both Kubernetes and legacy workloads
- High-availability SLA: Reliably leverage Spot VMs without disrupting your mission-critical workloads
Learn more about how Spot supports all your Kubernetes workloads.