Elotl receives investment from Cisco Investments to accelerate AI-ready Infra for Multi-Cloud Era

We are excited to announce an investment from Cisco Investments to accelerate AI-ready Infra for Enterprise AI platform teams!

AI software stacks have standardized on top of Kubernetes. Elotl’s enterprise-grade battle-tested Luna provisions just-in-time right-sized compute for Kubernetes. Luna prevents wasted GPU spend for AI workloads along with simplifying operations.

Enterprise AI must meet response time SLAs before going live. Since expensive accelerators like GPUs are in short supply, waiting to source compute from a single region/datacenter/hyperscaler/neocloud would jeopardize AI business SLAs. Kubernetes platform teams need to dynamically source compute from multiple regions and cloud providers to be AI ready. This calls for a federated compute fabric spanning across on-prem datacenters, hyperscalers, and neoclouds. Elotl Nova is a policy-driven federated compute fabric that commoditizes Kubernetes clusters across regions and cloud providers.

As AI workloads scale, the need for robust, secure, and scalable networking becomes just as critical as compute. Through the acquisition of Isovalent in 2024, Cisco added the industry standard for Kubernetes networking and security, including technologies like Cilium and Tetragon, to its solutions for enterprise AI and cloud-native environments. These technologies are now foundational for enterprises running cloud-native and AI workloads on Kubernetes, providing the networking, security, and observability capabilities needed to support dynamic, distributed environments.
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At Elotl, we’re committed to helping enterprises focus on building AI solutions while we take care of infrastructure complexity. With Cisco’s investment and the strength of its industry-leading technologies, organizations can accelerate innovation and confidently run AI across multi-cloud environments. Here is a demo of cloud bursting AI workloads from on-prem datacenter to Azure using Nova, Cilium Cluster Mesh, and Hubble:

​If you are interested in using Luna and/or Nova for your self-hosted training/inference/batch initiatives, please reach out at [email protected]

Author: Madhuri Yechuri