Overview

Learn how to deploy additional microservices for specialized Prisme.ai applications such as Custom Code, Crawler, and Knowledges

Prisme.ai’s architecture includes specialized microservices that support specific applications like Custom Code, Crawler, Search Engine … This guide explains how to deploy these additional microservices in your self-hosted environment.

License Requirement

The microservices discussed in this guide are available based on your subscription license. Ensure your license includes access to these components before proceeding with deployment.

Access Requirements

You will need valid GitLab credentials to access the Docker images for these microservices. If you don’t have them yet, please contact [e-mail] to obtain a GitLab username and token.

These credentials are typically provided as a GitLab Deploy Token with appropriate permissions to pull the required images.

Deployment Strategy

We will deploy the apps microservices in the same Kubernetes cluster as the core microservices. However, for better resource isolation and management, we recommend using a separate namespace for these additional services.

Prerequisites

Each microservice has specific requirements that must be fulfilled before deployment. Review the prerequisites for each service you plan to deploy:

• prismeai-crawler - Web crawling and indexing service
• prismeai-functions - Custom code execution environment
• prismeai-searchengine - Search functionality for crawled content

Deployment Process

Follow these steps to deploy the apps microservices in your Kubernetes cluster:

1. Retrieve the Helm Charts

   You have two options for accessing the required Helm charts:

   Option 1: Download the charts directly

   helm repo add prismeai https://helm.prisme.ai/charts
   helm pull prismeai/prismeai-apps
   ls
   

   Extract the archive to access the chart files.

   Option 2: Add as a Helm repository

   helm repo add prismeai https://helm.prisme.ai/charts
   helm repo update
   

   Then generate a values file template:

   helm show values prismeai/prismeai-apps > ./values.yml
   
2. Configure Values File

   Edit the values.yaml file to include connection details and credentials for external services:

   Key configuration areas include:

   • Container registry credentials: Your GitLab access details
   • Service-specific settings: Configuration for each microservice
   • Database configurations: Connection details for required databases
   • Resource allocations: CPU, memory, and storage requirements
   • Network settings: Service endpoints and ports

   Refer to each service’s documentation for specific configuration requirements.

3. Create Namespace

   Create a dedicated namespace for the apps microservices:

   kubectl create namespace apps
   

   This separation provides better resource isolation and management compared to deploying everything in the default namespace.

4. Deploy using Helm

   Choose the appropriate deployment command based on how you retrieved the charts:

   If you downloaded the charts (Option 1):

   # From the root of the extracted directory
   helm install apps . --namespace apps -f values.yaml
   

   If you added the repo (Option 2):

   helm install apps prismeai/prismeai-apps --namespace apps -f values.yaml
   

   The deployment will create all necessary Kubernetes resources in the apps namespace.

5. Verify Deployment

   Check that all pods are running correctly:

   kubectl get pods -n apps
   

   Ensure all services show Running status and are ready (e.g., 1/1 for readiness).

   You can get more detailed information about any pod with:

   kubectl describe pod [pod-name] -n apps
   

Testing the Microservices

After deployment, test each microservice to ensure it’s functioning correctly:

prismeai-crawler and prismeai-searchengine

Typical tests include:

• Creating a crawl job for a test website
• Verifying content is properly indexed
• Testing search functionality with simple queries
• Checking crawler logs for any errors

prismeai-functions

Key validation steps:

• Executing a simple function through the API
• Verifying resource limits are properly enforced
• Testing error handling for invalid code
• Checking integration with other Prisme.ai components

prismeai-llm

Important tests include:

• Testing model inference with a simple prompt
• Verifying token counting functionality
• Checking integration with supported models
• Validating logging and monitoring features

Troubleshooting Common Issues

Image Pull Errors

Symptom: Pods show ImagePullBackOff status

Possible causes:

• Invalid GitLab credentials
• Incorrect image repository URL
• Network connectivity issues

Resolution steps:

1. Verify your GitLab credentials are correct
2. Check the image repository URL in your values file
3. Create a Kubernetes secret with your credentials:
   kubectl create secret docker-registry gitlab-registry \
     --docker-server=registry.gitlab.com \
     --docker-username=YOUR_USERNAME \
     --docker-password=YOUR_TOKEN \
     --namespace apps
   
4. Update your deployment to use this secret

Configuration Errors

Symptom: Pods start but quickly crash or enter CrashLoopBackOff

Possible causes:

• Missing or incorrect environment variables
• Invalid database connection details
• Insufficient permissions or resources

Resolution steps:

1. Check pod logs for specific error messages:
   kubectl logs [pod-name] -n apps
   
2. Verify database connectivity from within the cluster
3. Ensure all required environment variables are set
4. Check resource allocations match the service requirements

Service Connectivity Issues

Symptom: Services start but can’t communicate with each other

Possible causes:

• Incorrect service names or ports
• Network policies blocking traffic
• DNS resolution problems

Resolution steps:

1. Verify service endpoints using:
   kubectl get services -n apps
   
2. Test connectivity using a debug pod:
   kubectl run debug-pod --rm -it --image=nginx:alpine -- sh
   # Inside the pod
   wget -O- http://service-name.apps.svc.cluster.local:port/health
   
3. Check network policies that might be restricting traffic
4. Ensure CoreDNS is functioning properly

Upgrading Microservices

When new versions of the apps microservices become available:

1. Update Helm Repository

   If using the Helm repository approach:

   helm repo update
   
2. Check for Changes

   Review the changes in the new version:

   helm show values prismeai/prismeai-apps > ./new-values.yml
   diff values.yaml new-values.yml
   

   Update your values file as needed to accommodate any new configuration options.

3. Perform the Upgrade

   Upgrade the deployment with:

   helm upgrade apps prismeai/prismeai-apps --namespace apps -f values.yaml
   

   Or if using the downloaded chart:

   helm upgrade apps . --namespace apps -f values.yaml
   
4. Verify Upgrade

   Check that all pods are running the new version:

   kubectl get pods -n apps
   

   And verify functionality using the testing procedures mentioned above.

Next Steps

After successfully deploying the apps microservices:

Custom Code App

Set up the use custom code capabilities

Set Up Web Crawling

Configure crawling & search services

Configure LLM Access

Set up access to various local language models

For any issues or questions during the deployment process, contact [e-mail] for assistance.