AI/ML

    Deploy OpenThinker 7B on GCP: Best Practices for AI Model Hosting


    Introduction

    Deploying OpenThinker 7B on Google Cloud Platform (GCP) allows for scalable, secure, and cost efficient hosting of the model. GCP provides various services such as Google Kubernetes Engine (GKE), Cloud Run and Compute Engine (GCE) for deployment.

    In this guide, we will focus on deploying OpenThinker 7B using Google Kubernetes Engine (GKE), which provides managed Kubernetes infrastructure for deploying and scaling containers.

    Key Benefits of Deploying OpenThinker 7B on GCP

    • Scalability: Auto-scaling for high-demand workloads
    • Cost Optimization: Pay for compute resources as needed
    • Managed Kubernetes: Simplifies deployment and scaling
    • Security: Integrated IAM and VPC networking

     

    Step 1: Prerequisites

    Before starting, ensure you have:

    • A Google Cloud account with billing enabled
    • Google Cloud SDK (gcloud CLI) installed and authenticated
    • Docker installed on your local machine
    • A pre-built Docker image of OpenThinker 7B
    • Kubernetes command-line tool (kubectl) installed

    Step 2: Push the Docker Image to Google Container Registry (GCR)

    Enable GCR API and Authenticate Docker

    Enable Google Container Registry (GCR):

    gcloud services enable containerregistry.googleapis.com

    Authenticate Docker to push images to GCR:

    gcloud auth configure-docker

     

    Tag the Docker Image

    Retrieve your GCP project ID:

    gcloud config get-value project

    Tag the image for GCR (replace <project-id> and <region> with your actual values):

    docker tag openthinker-7b gcr.io/<project-id>/openthinker-7b:latest

    Push the Image to GCR

    docker push gcr.io/<project-id>/openthinker-7b:latest

    Once completed, the image will be stored in Google Container Registry (GCR).

     

    Step 3: Create a GKE Cluster

    We will use Google Kubernetes Engine (GKE) to deploy the model.

    Enable GKE API

    gcloud services enable container.googleapis.com

    Create a GKE Cluster

    gcloud container clusters create openthinker-cluster \ --zone us-central1-a \ --num-nodes 2 \ --machine-type n1-standard-4

     

    This command creates a 2-node cluster in us-central1-a using n1-standard-4 instances.

    Connect to the Cluster

    gcloud container clusters get-credentials openthinker-cluster --zone us-central1-a

    Step 4: Deploy OpenThinker 7B on GKE

    Create a Kubernetes Deployment YAML File

    Create a new file called openthinker deployment.yaml:

    apiVersion: apps/v1kind: Deploymentmetadata: name: openthinker-deploymentspec: replicas: 1 selector: matchLabels: app: openthinker template: metadata: labels: app: openthinker spec: containers: - name: openthinker image: gcr.io/<project-id>/openthinker-7b:latest ports: - containerPort: 11434 resources: limits: memory: "8Gi" cpu: "2"

     

    Apply the Deployment

    kubectl apply -f openthinker-deployment.yaml

    Step 5: Expose the Deployment

    To allow external access to OpenThinker 7B, create a Kubernetes Service.

    Create a Service YAML File

    Create a new file called openthinker-service.yaml:

     

    apiVersion: v1kind: Servicemetadata: name: openthinker-servicespec: type: LoadBalancer selector: app: openthinker ports: - protocol: TCP port: 80 targetPort: 11434

     

    Apply the Service

    kubectl apply -f openthinker-service.yaml

     

    This command exposes OpenThinker via a LoadBalancer, which assigns a public IP.

    Step 6: Verify Deployment

    Check Running Pods

    kubectl get pods

     

    Ensure the pod is running.

    Get the External IP

    kubectl get service openthinker-service

     

    Look for the EXTERNAL IP field. Once assigned, you can access OpenThinker using:

    curl http://<external-ip>

     

    Expected output:

    {"message": "Model is up and running"}

     

    Step 7: Scaling the Model (Optional)

    To handle high traffic, increase the number of replicas:

    Update the Replica Count

    kubectl scale deployment openthinker-deployment --replicas=3

     

    Enable Auto Scaling

    kubectl autoscale deployment openthinker-deployment --cpu-percent=70 --min=1 --max=5

     

    This scales the model dynamically based on CPU usage.

    Step 8: Cleaning Up Resources (If Needed)

    To delete the Kubernetes deployment:

    kubectl delete deployment openthinker-deploymentkubectl delete service openthinker-service

     

    To delete the GKE cluster:

    gcloud container clusters delete openthinker-cluster --zone us-central1-a

     

    Conclusion

    Deploying OpenThinker 7B on Google Cloud Platform (GCP) using GKE allows for scalable, managed deployment. By leveraging Google Kubernetes Engine (GKE), Google Container Registry (GCR) and Load Balancers, the model runs efficiently with minimal manual intervention.

     

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    Experts in AI, ML, and automation at OneClick IT Consultancy

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    AI Force at OneClick IT Consultancy pioneers artificial intelligence and machine learning solutions. We drive COE initiatives by developing intelligent automation, predictive analytics, and AI-driven applications that transform businesses.

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