GKE Deployment & Architecture Guide
Technical documentation for provisioning the Bounded Agentic AI Workflow Engine on Google Kubernetes Engine (GKE).
Sovereign Enterprise Deployment
The Bounded Agentic AI Workflow Engine is delivered as a secure, containerized application for customer-controlled GKE private clusters. The default architecture is single-tenant and customer-hosted. Model weights, prompts, workflow policies, traces, and governance metadata remain strictly inside the customer’s Google Cloud project and VPC boundary.
Managed Lifecycle and Bounded Execution
Our neuro-symbolic engine acts as a deterministic policy enforcement layer between an upstream AI proposal and downstream execution. It evaluates AI-assisted outputs, tool-use proposals, and workflow actions against approved business-process rules before execution.
Provisioning via GCP Marketplace
The product deploys directly from Google Cloud Marketplace into your GKE environment. Containers are delivered through Artifact Registry. Runtime execution occurs inside your private cluster, with AI workloads running securely on GPU node pools.
# Authenticate with Google Cloud
gcloud auth login
gcloud config set project [YOUR_PROJECT_ID]
# Configure Docker to authenticate with GCP Artifact Registry
gcloud auth configure-docker [REGION]-docker.pkg.dev
# Pull the Bounded Agentic AI Workflow Engine deployer image
docker pull [REGION]-docker.pkg.dev/golem-tech-public/marketplace/bounded-agentic-ai-workflow-engine:latest
# Apply the Kubernetes manifests to your private GKE cluster
kubectl apply -f deployment.yaml