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Google Cloud Platform provides powerful managed services ideal for deploying Prisme.ai. This guide covers recommended infrastructure, deployment steps, and best practices for self-hosting Prisme.ai on GCP.

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GCP Prerequisites

Before starting, ensure you have:
  • A GCP account with adequate permissions.
  • Google Cloud SDK (gcloud CLI) installed and authenticated.
  • Basic knowledge of Kubernetes and essential GCP services (GKE, Cloud SQL, Memorystore, Cloud Storage).
Deploy Prisme.ai leveraging these recommended GCP-managed services:
  • Service: Google Kubernetes Engine (GKE)
  • Recommended Configuration:
    • Node pool with 3-5 nodes (e2-standard-4 or similar, 4 vCPU / 16GB RAM)
    • Enable Autoscaling and Auto-upgrade
  • Best Practices:
    • Multi-zone clusters for high availability
    • Enable Workload Identity for secure access to GCP resources
  • Deployment Command: 
    gcloud container clusters create prisme-ai-cluster \
  --zone europe-west1-b --num-nodes 3 \
  --machine-type e2-standard-4 --enable-autoscaling \
  --min-nodes 3 --max-nodes 5
  • Service:
    • Self-managed MongoDB on GKE or MongoDB Atlas integrated via VPC peering
    • Or Cloud SQL for Postgre
  • Recommended Configuration:
    • 3-node replica set
  • Best Practices:
    • Automated backups and maintenance
    • Use Cloud SQL Proxy or VPC peering for security and isolation
  • Service: Elasticsearch on Elastic Cloud or deployed via GKE-managed containers
  • Recommended Configuration:
    • Elasticsearch cluster with at least 3 nodes (8GB RAM per node)
  • Best Practices:
    • Snapshot regularly to Cloud Storage
    • Secure using private networking and access controls
  • Service: Google Cloud Memorystore for Redis
  • Recommended Configuration:
    • Standard tier, 3-node configuration
    • High availability and auto-failover enabled
  • Best Practices:
    • Regular monitoring and alerting
    • Set maintenance windows for updates
  • Service: Google Cloud Storage
  • Recommended Configuration:
    • Buckets configured for private uploads, public assets, and model storage
  • Best Practices:
    • Lifecycle management rules
    • CDN integration with Cloud CDN for public assets
  • Service: Google Cloud Filestore
  • Recommended Configuration:
    • Standard or Premium tier based on performance needs
  • Best Practices:
    • Mount Filestore as a Persistent Volume Claim (PVC) in Kubernetes
    • Regularly snapshot via scheduled tasks

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GCP Deployment Steps

1

Create Project & Enable APIs

Create a GCP project and enable required APIs:
gcloud projects create prisme-ai
gcloud services enable container.googleapis.com \
  sqladmin.googleapis.com redis.googleapis.com file.googleapis.com storage.googleapis.com
2

Deploy GKE Cluster

Provision a Kubernetes cluster with GKE:
gcloud container clusters create prisme-ai-cluster --zone europe-west1-b
3

Provision Databases & Storage

  • Deploy MongoDB via MongoDB Atlas or self-host on GKE or Cloud SQL for Postgre.
  • Set up Redis via Memorystore.
  • Provision Elasticsearch via Elastic Cloud or Kubernetes.
  • Create Cloud Storage buckets and Filestore instances.
4

Configure DNS & Networking

Set up Google Cloud DNS or external DNS:
  • api.yourdomain.com
  • studio.yourdomain.com
  • *.pages.yourdomain.com
5

Deploy Prisme.ai via Helm

Deploy Prisme.ai using Helm to your GKE cluster:
helm repo add prismeai https://helm.prisme.ai/charts
helm install prisme-core prismeai/prismeai-core --namespace prisme -f values.yaml
6

Ingress & SSL Setup

Configure Kubernetes Ingress via GKE’s built-in Ingress Controller:
kubectl apply -f ingress.yaml
Use Google-managed SSL certificates for secure HTTPS access.

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Security Best Practices

Workload Identity

  • Use GKE Workload Identity for secure and granular permissions between Kubernetes and Google Cloud services.

Private VPC

  • Configure a private VPC for your cluster.
  • Use Cloud NAT for controlled egress internet access.

Secrets & Configuration

  • Store sensitive configurations securely in Google Secret Manager.
  • Implement regular key rotation policies.

Monitoring & Logging

  • Integrate with Google Cloud Operations Suite (Cloud Monitoring and Cloud Logging).
  • Set alerts for abnormal resource usage.

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Next Steps

Helm Deployment

Deploy Prisme.ai using Helm on Kubernetes

Products Configuration

Configure your Prisme.ai AI products

Operations Management

Learn about scaling operations efficiently