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Installation

Introduction

You can install Prisme.ai on any platform using Docker.
You can also follow one of our guides to install Prisme.ai on popular hosting platforms, these installations are often more production oriented.

We recommend using Kubernetes with Helm while deploying our platform.
Also, before deploying our platform, we strongly advise to familiarize yourself with it's architecture in order to understand the different microservices required as well as the different types of databases needed.
The architecture can be reviewed here.

General considerations

Provision required cloud provider resources :

  • A load balancer with ingress controller capabilities. Other load balancing methods might be used but are not documented here
  • A minimal Kubernetes cluster for Prisme.ai should have at least 3 nodes 4vCPU / 16GB, this configuration is suitable to run a smooth core installation. If your installation includes microservices from the enterprise features you may need more depending on the additional microservices.
  • External services such as Elasticsearch, Redis or MongoDB can either be self-hosted or managed. We recommend using a managed solution, if you want to self-host those services, please check their official documentation.
  • Services workspaces and runtime requires one of these document/object storage :
    • Filesystem (either through a local directory or a Kubernetes PVC)
    • S3 compatible object storage
    • Azure Blob storage

Offline environments

If the installation environment does not have access to internet, ensure that the following prerequisites are always met :

  • If using app microservices, prismeai-functions need access to a NPM registry. If the default https://registry.npmjs.org/ is not available, you must configure your own npm registry using NPM_CONFIG_REGISTRY environment variable inside prismeai-functions microservice
    • Depending on your NPM proxy, it might require additional configuration for authentication
  • If using internal / self-signed TLS certificates, they must be configured inside almost all microservices to avoid HTTPS errors
    • prismeai-searchengine and prismeai-crawler are Python microservices : once mounted, the certificate file location can be configured with REQUESTS_CA_BUNDLE
    • prismeai-llm does not need the custom certificate
    • Every other prismeai-* services are NodeJS : once mounted, the certificate file location can be configured with NODE_EXTRA_CA_CERTS
  • While importing our workspaces and apps (enterprise installation) some assets can be missing as for the moment those are only registered as URL.
    We are working into streamlining this process, however, here is a workaround for the time being:
    • Blocks : some workspaces can contain their own custom blocks (Custom Code, Popover, Dialog Box, Charts) you will have to replace the blocks url and upload yourself the blocks (which are JavaScript files) from the Prisme.ai interface. The files shall be provided by the Prisme.ai team.
    • Images : workspaces images will be unreachable, you might want to replace them with your own using the Prisme.ai interface.

Available guides

Currently available guides :