Monetize GPUs Instantly with Mirantis k0rdent AI

Monetize GPU infrastructure rapidly — Integrate metering APIs with billing systems to automatically track usage, generate invoices, and process payments for GPU resources and services.

Maximize GPU utilization through intelligent partitioning — Allocate GPU slices across multiple tenants to avoid stranded capacity and improve hardware ROI.

Provide self-service GPU provisioning — Enable tenants to browse available GPU offerings, view transparent pricing, provision resources instantly, and track consumption through an integrated cloud portal.

Offer secure, multi-tenant infrastructure — Provide hard multi-tenancy with isolation at GPU, VM, and Kubernetes layers to meet compliance and security requirements.

Monetize infrastructure investments – Integrate metering, billing, and payment APIs seamlessly to track usage, generate invoices, and manage customer payments transparently.

Enforce data sovereignty — Use the operator console to define GPU provisioning policies that automatically enforce locality rules, ensuring workloads remain within regulatory boundaries.

Accelerate delivery of sovereign clouds – Deploy compliant multi-tenant GPU resources rapidly using declarative templates that standardize provisioning across regions.

Ensure strict tenant isolation – Enforce hard multi-tenancy across compute, storage, and networking layers, meeting regulatory requirements for data sovereignty and security compliance.

Provision GPUs with declarative automation — Deploy GPU resources using templates that standardize hardware discovery, driver installation, and slicing configuration, reducing setup time.

Govern GPU allocation through centralized control — Use the operator console to set quotas, monitor per-tenant consumption, and enforce policies that prevent overprovisioning and maximize hardware ROI.

Partition GPUs for efficient multi-tenancy — Allocate GPU slices using NVIDIA MIG, vGPU, or software-based sharing to safely run multiple teams on shared hardware while keeping performance isolation.

Rightsize resources with integrated observability — Track GPU usage patterns to identify when teams request more resources than needed, then adjust allocations to match actual workload requirements.