Overview
Learn how to deploy additional microservices for specialized Prisme.ai applications such as Custom Code, Crawler, and AI Knowledge
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 support@prisme.ai 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:
Retrieve the Helm Charts
You have two options for accessing the required Helm charts:
Option 1: Download the charts directly
Download the Helm chart from the following URL:
Extract the archive to access the chart files.
Option 2: Add as a Helm repository
Then generate a values file template:
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.
Create Namespace
Create a dedicated namespace for the apps microservices:
This separation provides better resource isolation and management compared to deploying everything in the default namespace.
Deploy using Helm
Choose the appropriate deployment command based on how you retrieved the charts:
If you downloaded the charts (Option 1):
If you added the repo (Option 2):
The deployment will create all necessary Kubernetes resources in the apps
namespace.
Verify Deployment
Check that all pods are running correctly:
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:
Testing the Microservices
After deployment, test each microservice to ensure it’s functioning correctly:
Troubleshooting Common Issues
Upgrading Microservices
When new versions of the apps microservices become available:
Update Helm Repository
If using the Helm repository approach:
Check for Changes
Review the changes in the new version:
Update your values file as needed to accommodate any new configuration options.
Perform the Upgrade
Upgrade the deployment with:
Or if using the downloaded chart:
Verify Upgrade
Check that all pods are running the new version:
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 support@prisme.ai for assistance.
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