Groundcover Acquires Kubernetes Optimization Startup Wand in First Acquisition

Groundcover’s platform collects telemetry from applications and infrastructure. Under a bring-your-own-cloud model, the resulting production history stays inside each customer’s own cloud account. Engineers and artificial intelligence agents use that data to investigate problems and identify what changed. Wand’s technology adds the ability to make and carry out decisions about live Kubernetes clusters based on how workloads actually behave.

Wand targets the processor and memory requests Kubernetes asks engineers to set in advance, usually before a workload has run under real load. An overestimate wastes capacity across every replica and node. A request set too low risks throttling and outages when traffic shifts. Even a correct setting drifts out of date as services change.

Kubernetes autoscalers already handle parts of that job. According to groundcover, vertical, horizontal and cluster-level autoscalers typically run independently of one another. A tighter resource request pushes measured utilization up, for example, and the horizontal autoscaler may respond by adding replicas that are not needed. Workload packing on nodes then shifts, along with the cluster autoscaler’s behavior.

Wand’s software sits inside the cluster and makes all three kinds of scaling decisions at once. Engineers are not left with a queue of right-sizing recommendations to work through later, because CPU and memory allocations change on live infrastructure as demand moves. Wand said it tunes a cluster for performance and availability first, with cost savings following once unneeded headroom is stripped out.

Shon Lev-Ran, Wand’s co-founder and chief executive, said right-sizing “assumes we know the future.” Infrastructure changes continuously, he said, and joining groundcover gives Wand a much deeper view of what is happening across production.

Groundcover’s case for the deal rests on that deeper view. A workload can look overprovisioned when judged on the past hour and still be sized correctly for the traffic that arrives every Monday morning, the company said. Production data is kept at high fidelity on its platform, so teams do not have to decide ahead of time what to sample or throw away.

Groundcover co-founder and Chief Executive Shahar Azulay said production data is increasingly the context AI agents rely on to build, fix and run software. “For infrastructure to become autonomous, systems also need to act safely on what they know,” Azulay said. “Wand has spent years building exactly that capability for Kubernetes.”

The company plans to use Wand’s technology in two places. The first is groundcover’s own platform, which runs inside customer cloud accounts. Whatever it consumes shows up on those customers’ cloud bills, and a leaner footprint should make it cheaper for them to keep more telemetry at full fidelity. The second is putting Wand’s Kubernetes resource optimization directly in the hands of groundcover customers. No timeline was given.

Groundcover is a venture capital-backed startup that has raised $160 million to date, including a $100 million Series C round led by One Peak in July. Other investors include Morgan Stanley Expansion Capital, Zeev Ventures, Angular Ventures, Heavybit and Jibe.