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Eliminate Over-Provisioning
Dynamic resource scaling based on actual workload needs
Pay for what you use. Not what you think you’ll need.
MicroVMs adjust CPU and memory in real time based on actual workload behavior. This eliminates idle capacity and reduces unnecessary cloud spend.
The Challenge
The Challenge
Overprovisioning for peaks wastes resources
Challenge
- Most teams size infrastructure for worst-case scenarios.
- This leads to idle CPUs, unused memory, and wasted spend.
Static resources can’t match real workloads
Challenge
- Traditional resource allocation is fixed at deployment.
- It doesn’t adapt to changes in usage patterns, leading to overprovisioning during idle periods and throttling during spikes.
The Solution
Real-time scaling without restarts
Solution
- Resource allocations adapt dynamically based on real usage.
- No restarts. No redeployments. No Helm or Terraform tuning.
Deep integration with runtime-level control
Solution
- A privileged agent runs as a DaemonSet on each node, updating resource limits through containerd’s gRPC API.
- This bypasses the Kubernetes control plane and enables in-place resizing across Kubernetes versions.
Elastic Compute for Burstable Workloads
We provide flexible, runtime-level compute scaling for CPU and memory. Workloads scale up with demand and scale down during idle time, improving efficiency without compromising performance.
Dynamic Resource Scaling
Resource allocation adjusts in real time based on actual usage. Static CPU and memory requests are replaced with runtime-based scaling. No restarts, redeployments, or API calls.
- Real-time metrics collection with cAdvisor
- In-place resizing through containerd
- Operates outside the Kubelet and control plane
Live Migration
When a workload exceeds the limits of its current node, it is automatically snapshotted and resumed on a new host. Migration happens without disruption and maintains application state.
- Real-time metrics collection with cAdvisor
- In-place resizing through containerd
- Operates outside the Kubelet and control plane
Cost and Resource Observability
Gain visibility into CPU, memory, and pressure metrics alongside real-time cost data. Understand where resources are overprovisioned and where savings can be reclaimed.
- Fine-grained usage data collected via cAdvisor
- Visualize request vs. actual usage deltas per workload
- Estimate cloud spending tied to resource utilization
Reduce Your Cloud Spend with Live Rightsizing MicroVMs
Run workloads in secure, right-sized microVMs with built-in observability and dynamic scaling. Just a single operator and you are on the path to reducing cloud spend.
Get full visiiblity and pay only for what you use.
Get full visiiblity and pay only for what you use.
A Kubernetes platform for using microVMs to cut your cost across any cloud. Pay for what you use. Not for what you think you'll need.
