Kubernetes AI Job Support — Production AI, Agentic Systems, LLM Inference & GPU Infrastructure

It is real-time, hands-on help from experienced platform and AI-infrastructure engineers during your working hours — on your actual cluster. We help with LLM inference serving, GPU scheduling and Dynamic Resource Allocation, agent runtimes and sandboxes, MCP servers and gateways, autoscaling and scale-to-zero, AI observability, AI security, and cost/FinOps. It is delivered live, confidentially, and same-day where needed, anywhere in the world.

The focus is operating production AI and autonomous agents — not "what is Kubernetes". That means GPU and accelerator scheduling (DRA, MIG, topology-aware placement, gang scheduling for multi-node inference and training), LLM-serving platforms (vLLM, KServe/LLMInferenceService, Ray Serve, NVIDIA Dynamo with disaggregated prefill/decode and KV-aware routing), agent execution isolation and sandboxes, MCP security, inference-specific observability (TTFT, TPOT, tokens/sec, KV-cache utilisation), and the FinOps of idle GPUs and cold starts.

Yes. We provide dedicated Kubernetes AI production support — GPU Pods Pending, CUDA and OOMKilled errors, device-plugin failures, vLLM OOM and KV-cache exhaustion, high TTFT, inference timeouts, model-loading failures, autoscaling failures, agent loops, MCP failures, and RAG/vector-DB latency — with an engineer on the call. See our Kubernetes AI production support page.

Amazon EKS, Azure AKS, Google GKE, Red Hat OpenShift / OpenShift AI, Rancher/RKE2, SUSE, VMware Tanzu, and bare-metal / on-prem Kubernetes — including air-gapped, sovereign, and private-AI deployments. We advise honestly on when a managed agent runtime or managed inference service is a better fit than self-hosting on Kubernetes.

Yes. This cluster reflects the verified ecosystem state through September/October 2026 — Kubernetes v1.37 "Garhwal" (DRA extended-resource support GA; Workload/PodGroup gang scheduling and Workload-Aware Preemption in Beta and disabled by default; the new CompositePodGroup API; in-place pod resize), NVIDIA Dynamo with its Kubernetes Operator, GKE Inference Gateway GA and GKE Agent Sandbox, KServe LLMInferenceService, and OpenShift AI with llm-d. We verify version-sensitive status before advising and never assume GA where a feature is Beta or preview.

Message us on WhatsApp with your cluster and cloud, your situation (job support, production incident, interview, or profile), and your timeline. We match you with the right expert — usually the same day. Every engagement is confidential and NDAs are available on request.