Adaptive pod placement
Group unevictable pods that block consolidation to reduce fragmentation, improve node utilization, and lower compute costs while maintaining application availability.
Trusted by the best to optimize at scale
Reduce fragmentation
Group unevictable pods on the minimum number of nodes to reduce fragmentation, while still distributing them to avoid single-node failure risk.
Free up node capacity
Gradually evict pods to free capacity, while respecting PodDisruptionBudgets to maintain application availability and enable node consolidation.
Works with your existing autoscaler
Compatible with Cluster Autoscaler, Karpenter, and any other node autoscalers running in your environment.
Built-in safe eviction mechanism
Respects Jobs and CronJobs. Follows your PDBs or configurable thresholds, and takes actions gradually to ensure stability.
Pod Placement that keeps your clusters optimized
Increase node utilization
Group unevictable pods to reduce fragmentation and free capacity for node consolidation and higher utilization.
Reduce infrastructure costs
Run the same workloads on fewer nodes and scale down unused compute capacity.
Maintain application performance
Relocate evictable pods safely with gradual evictions and PDB safeguards, to keep workloads stable during optimization.
Optimize at every layer
PV autoscaling
Automatically rightsize persistent volumes based on usage to reduce costs and maintain availability.
Azure Commitment Optimization
Continuously align commitments with usage to maximize coverage and minimize lock-in risk.
FastScaler
Reduce app startup time by up to X5 to absorb spikes without throttling or OOMs.
Multi-dimensional Autoscaling
Optimize pod resources and replica counts to maximize performance and cost efficiency.
Compute cost visibility
Analyze workload costs, identify waste, and automate with clear data-driven insights.
AWS Commitment Optimization
Continuously align commitments with usage to maximize coverage and minimize lock-in risk.
