
Spot Optimization
Safely Run More Pods on Spot Instances. Automatically.
Increase Spot adoption and cut cloud costs by up to 70% more by intelligently shifting more workloads to Spot instances without any downtime or disruptions. ScaleOps automatically detects your workloads and manages the optimal policy for each one.










Granular, Pod-Level Spot Optimization
ScaleOps optimizes workloads at the pod-level by automatically distributing replicas across Spot and On-Demand instances. Real-time rebalancing drives maximum cost savings while maintaining performance and reliability, even when Spot Instances are interrupted.
Centralized, Policy-Driven Spot Management
Eliminate manual tuning and developer intervention with centralized Spot policies for your entire cluster. Clearly define workload behavior: replica ratios between Spot and On-Demand, automatic fallback, and minimum On-Demand capacity.
Maximize Spot Usage. Minimize Cloud Spend.
Automated Policy Detection
ScaleOps uses application context-awareness to analyze workload behavior using historical data and real-time demand, automatically assigning the optimal policy to each workload so that you safely maximize Spot usage and cloud cost savings.














