Cloud Cost Optimization
Dynamic & Automated Optimization of Kubernetes Workloads
Why is this solution best for you?
What problems does MLOps help to solve?
Continuous & Automatic Pod Rightsizing
Automatically adjusts CPU and Mem requests of Kubernetes pods during runtime.Significantly reduce compute costs and eliminate OOM and CPU throttling by dynamically scaling resources according to workloads needs.
Optimal Node Utilization
Automatically optimize Kubernetes nodes and boost cluster efficiency by consolidating pods onto more suitable nodes and removing unnecessary ones.
Workload-Based Scaling Policies
Select from multiple pre-defined scaling policies that match your workload needs, accelerate your time to value and start saving in minutes.
Simplified Cost Visibility
Easily analyze cluster costs, set alerts for budget deviations, with a simplified cost showback dashboard.
Our employees about AI Adoption
Your workloads, for 80% less
Gain real-time recommendations, understand your cost structure, detect resource consumption anomalies, and get real-time alerts accordingly.