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Architecture ​

Thalamus is a Kubernetes-native LLM inference stack.

It requires an AI-enabled Kubernetes cluster, for example one provided by Gardener. The underlying hardware lifecycle is managed via metal-api and wire-api. Model weights are stored in an object store, container images in an OCI registry. Thalamus' Custom Resource Definitions bundle these together as a model catalog. Operations tooling is built in via industry-standard exporters and custom extensions.

High-level architecture

Inference API ​

A single OpenAI-compatible HTTP endpoint serves all clients. Routing to the correct model and replica is handled inside the cluster by the Gateway API Inference Extension and the llm-d Endpoint Picker. See Request flow for a step-by-step walkthrough.

Kubernetes AI runtime ​

Gateway API Inference Extension ​

Model-aware HTTP routing built on the Kubernetes Gateway API. Each model is served by an InferencePool; requests are routed to the right pool based on the requested model.

llm-d + vLLM ​

Model servers run vLLM behind llm-d, which provides KV-cache aware load balancing across the replicas of a model.

NVIDIA / AMD / Intel GPU Operator ​

Vendor GPU operators install drivers and expose accelerators to the cluster as schedulable resources.

GardenLinux ​

The host operating system on the cluster nodes.

metal-api and wire-api ​

The bare-metal and network-fabric APIs that manage the lifecycle of the physical machines and data-center network underneath Kubernetes.

Platform services ​

Keppel ​

The OCI registry that hosts container images and the LLM catalog referenced by Thalamus' Custom Resource Definitions.

Ceph ​

The object store that holds model weights.

Cortex ​

GPU scheduling, including gang scheduling for multi-GPU model instances.

Gardener ​

Managed Kubernetes. Provisions and operates the AI-enabled clusters Thalamus runs on.

Operations ​

Metrics, logs, and traces flow through Prometheus, OpenSearch, and OpenTelemetry. Infrastructure and inference signals are surfaced through industry-standard exporters and custom extensions:

  • nvidia-smi exporter: GPU utilization, memory, temperature, power
  • node-exporter: host-level CPU, memory, disk, network
  • redfish exporter: hardware/BMC metrics
  • custom exporters: inference-specific metrics

Multi-vendor hardware ​

Thalamus runs on commodity server hardware from multiple vendors with accelerators from NVIDIA, AMD, and Intel.

Confidential computing ​

For workloads that require strong data isolation, Thalamus supports GPU confidential computing. Model weights are sealed inside an attested GPU boundary, isolated from the operator and co-tenants. Customer prompts and context are processed inside the same boundary. This enables:

  • Partner weight protection. Proprietary weights can be deployed to infrastructure the model owner does not control.
  • Restricted-data inference. Data that cannot leave a controlled boundary can still be processed.

Deployment topologies ​

The same stack runs in two topologies:

  • Datacenter. Full stack co-located in a managed Kubernetes cluster.
  • Satellite. Air-gapped subset of the stack at the edge. The satellite carries its own OCI registry, inference gateway, model instances, and monitoring; the central datacenter retains the source-of-truth registry, object store, model catalog, and identity provider.