Wand provides a usage‑driven automation layer for Kubernetes that continuously right‑sizes CPU and memory allocations based on real‑time pod and node metrics. By integrating with Karpenter and offering a one‑line controller deployment plus a dashboard, it eliminates noisy‑neighbor interference and reduces compute waste while keeping SLA compliance for multi‑tenant clusters.
Funding
Funding not disclosed
Founders
Product
Problem
Kubernetes clusters often rely on request‑based sizing and static scaling policies, leading to low overall utilization, noisy‑neighbor interference, and a persistent trade‑off between cost savings and performance guarantees. This results in wasted compute spend and increased operational overhead for teams managing multi‑tenant workloads.
Solution
Wand introduces Just‑In‑Time Global scaling, a usage‑driven automation layer that continuously aligns provisioned resources with actual workload demand across an entire Kubernetes environment. By ingesting real‑time metrics from pods, nodes, and Karpenter configurations, the platform dynamically right‑sizes CPU and memory allocations, eliminates noisy neighbors, and maintains SLA compliance without manual intervention. A single‑line installation deploys the controller and a lightweight dashboard, providing immediate visibility into utilization, cost savings, and risk metrics. The solution operates at both cluster and workload granularity, enabling organizations to achieve higher compute efficiency while preserving performance.
Target Audience
The primary customers are DevOps, SRE, and cloud infrastructure teams responsible for managing production Kubernetes clusters in enterprises and SaaS providers seeking to reduce compute waste while meeting performance SLAs.
Features
- Real‑time usage analytics that drive automatic scaling decisions instead of static request‑based limits
- Global correlation engine linking workload sizes, Karpenter provisioner settings, and actual demand across all clusters
- One‑liner deployment of the Wand controller with zero‑downtime rollout for existing workloads
- Granular enablement allowing selective activation on specific namespaces, node pools, or workloads
- Automated right‑sizing of CPU and memory resources to eliminate over‑provisioning and noisy‑neighbor effects
- Integrated dashboard and API exposing utilization, cost‑reduction, and SLA compliance metrics in near real‑time
- Compatibility with major managed Kubernetes services (EKS, GKE, AKS) and on‑prem clusters via standard Kubernetes APIs