Scaling Kubernetes for Less with Amazon EC2 Spot Instances: Best Practices

we’ll explore how to leverage Spot Instances in Kubernetes clusters, saving costs while maintaining high availability.

Understanding Amazon EC2 Spot Instances

Amazon EC2 provides customers with on-demand compute capacity, allowing instances to be launched and terminated with ease. To efficiently utilize spare capacity, AWS offers Spot Instances. Unlike on-demand instances, Spot Instances are priced at up to a 90% discount, based on long-term supply and demand trends. The misconception of Spot pricing being based on bidding is outdated. AWS now provides a two-minute warning before Spot Instances are reclaimed, allowing applications to handle interruptions gracefully.

Spot Capacity Pools

Spot Instances are grouped into Spot capacity pools, with each instance type in every availability zone being a separate pool. Price and capacity fluctuate independently, making it essential to be flexible with instance types. Configuring this flexibility is simple using EC2 Auto Scaling groups.

Implementing Instant Flexibility Best Practices

EC2 Auto Scaling groups offer a Mixed Instance Policy, allowing you to define a portion of your group for on-demand capacity and another for Spot Instances. Multiple instance types can be configured within these groups, providing the flexibility to tap into various capacity pools. The capacity-optimized allocation strategy is recommended for optimal resource utilization.

Leveraging EC2 Spot Instances in Kubernetes

Containerized workloads, often fault-tolerant and stateless, can run on Spot Instances with minimal effort. Amazon EKS (Elastic Kubernetes Service) simplifies Kubernetes management and supports Spot Instances. Managed node groups with EC2 Auto Scaling provide easy provisioning and management of instances, even with Spot Instances.

Managing Node Groups with Spot Instances

Amazon EKS now supports Spot Instances within managed node groups, offering the same automation and ease of use as on-demand instances. Multiple instance types can be configured, ensuring flexibility and adherence to Spot Instances best practices. Capacity Rebalancing is a feature that proactively manages Spot Instance interruptions, improving reliability.

Controlling Pod Scheduling

Nodes within managed node groups are labeled to distinguish between on-demand and Spot Instances. You can use node affinity rules to ensure critical services or applications run on specific instance types, maintaining a balance between reliability and cost-efficiency.

Scaling Application and Infrastructure

Horizontal Pod Autoscaler (HPA) scales pod replicas based on metrics like CPU utilization, ensuring resource availability. Kubernetes Cluster Autoscaler manages the underlying EC2 Auto Scaling groups, scaling capacity up or down based on demand. Tagging Auto Scaling groups correctly enables Cluster Autoscaler to discover and manage them effectively.

Going Large Scale with Multiple Node Groups

For large-scale deployments, creating multiple node groups with homogeneous instance types ensures tapping into more capacity pools. Cluster Autoscaler intelligently scales Auto Scaling groups, further reducing the likelihood of interruptions.

Running Kubernetes on EC2 with Spot Instances

If you’re managing Kubernetes on EC2 without EKS, the same Spot Instances best practices apply. Using AWS node termination handler and Queue Processor, you can proactively handle Spot Instance interruptions, even taking advantage of Capacity Rebalancing.


Leveraging Amazon EC2 Spot Instances in Kubernetes clusters is a powerful way to reduce costs without compromising availability. Whether you’re using Amazon EKS or self-managing Kubernetes on EC2, following these best practices and utilizing AWS features can lead to significant cost savings and optimized infrastructure utilization. As containerized workloads become increasingly cloud-native, Spot Instances provide an excellent opportunity to make your architecture more efficient and cost-effective.

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