Improving Cluster Resilience with Spot Instance Diversity Management

This document outlines a feature designed to enhance Kubernetes cluster resilience when leveraging Spot instances. By intelligently distributing workloads across heterogeneous instance types, the system reduces operational risks while maintaining cost-effectiveness.

Key Features

Automated Instance Type Diversification

CloudPilot AI dynamically distributes workloads across multiple Spot instance types (e.g., m5, t3, c5) within its built-in node provision strategy. This reduces the possibility of simultaneous interruptions and improves cluster resilience even during sudden Spot market volatility.

Cost-Stability Balance

Achieves an equilibrium between Spot instance cost savings and workload reliability. CloudPilot AI adapts to real-time Spot instance market conditions without requiring manual intervention.

How It Works

The core logic is implemented in the optimizer component, which monitors the distribution and provisions diverse instance types. Here is one example:

1. Initial State Analysis The system evaluates current cluster composition. For example:

   Instance Type	Allocation
   m5.large	60%
   t3.medium	20%
   c5.xlarge	20%

2. Gradual Redistribution New workloads are redirected toward underrepresented instance types. Over time, the distribution evolves toward:

   Instance Type	Allocation
   m5.large	40%
   t3.medium	30%
   c5.xlarge	30%

The actual performance depends on real-time Spot market conditions and regional instance availability. This feature is not enabled by default. Contact the CloudPilot AI Engineering Team for activation.