Dynamia AI Platform brings enterprise-grade GPU virtualization and AI-aware scheduling to Amazon EKS, and includes an integrated web console for multi-cluster dashboards, inventory, and policy/governance.

Core GPU & scheduling capabilities

Fractional sharing with hard limits: per-pod SM/compute throttling and VRAM caps (MB or %), preventing noisy neighbors.

VRAM overcommit with guardrails: increase cluster-level utilization while honoring per-pod safety limits.

Live VRAM vertical scaling: adjust a running pod's GPU memory without restarts for many inference workloads.

AI-purpose scheduling: binpack/spread, target by GPU model/UUID, NUMA/NVLink awareness, namespace/tenant GPU quotas; optional gang scheduling & preemption via integrations (e.g., Volcano/Koordinator).

Web console (single control plane)

Overview dashboard: multi-cluster posture, utilization, allocation, hot spots, and SLA risk hints.

Cluster dashboards: per-cluster health, GPU usage, allocation vs. requests, saturation trends.

Inventories: nodes list & detail, GPUs list & detail (model/UUID/topology/health), and workloads list & detail with GPU limits/actuals.

Governance & ops: quota management (tenant/project/namespace), storage management (volumes, classes, usage), policy enforcement and basic audit trail.

Observability: built-in DCGM metrics and prebuilt Grafana dashboards; alerting hooks.

Integrations & compatibility

Kubernetes-native (Helm/EKS add-on); no app changes required.

Works with vLLM Production Stack, SGLang, TensorRT-LLM, JupyterHub, Volcano/Koordinator.

Supports NVIDIA GPUs on Amazon EKS; optional MIG awareness; RBAC and LTS release channel.

Outcomes

Higher GPU utilization with fewer VRAM-related failures, clearer multi-tenant controls, and faster, safer rollout of AI training and inference services.