Install QuodAI helm chart

  1. Create namespace quod-ai

    kubectl create namespace quod-ai
  2. Create tls secret for quod-ai

    kubectl create secret tls quod-ai-tls\\ --namespace quod-ai \\ --cert=path/to/cert/file.crt \\ --key=path/to/key/file.key
  3. Copy on-prem-values-secret.template.yaml to on-prem-values-secret.yaml and update the values based on your configuration

  4. Install quod-ai on-prem with 16GB of ram cluster

    bash on-prem/install.sh

    If install failed with error Error: timed out waiting for the condition

    • It may be because the cluster hasn't provision enough node in times, you should create the cluster with at least 10 nodes for fast deploying, you can try to run bash on-prem/upgrade.sh to redeploy the cluster

    • Different error, please run kubectl get event --namespace quod-ai and check for any error.

  5. Mapping domain to correct ingress endpoint (fo-web.company.com, fo-api.company.com, matomo.company.com, kibana.company.com, etc). To query ingress endpoint, run

    kubectl get svc quod-ai-ingress-nginx-controller -n quod-ai -o json | jq '.status.loadBalancer.ingress[0].hostname' -r
  6. Go to fo-web url (fo-web.company.com) and start setting up the organization

Install using different repositories

  1. Check for the list of all repositories in on-prem-values.yaml

  2. Upload above repositories to your repositories

  3. Modify on-prem-images.yaml with your new repositories, eg change below image docker to your repositories (keep the image name and tag), eg [326348232034.dkr.ecr.ap-southeast-1.amazonaws.com/on_premise/de/quod_ai_es_on_prem:21.10.2](<http://326348232034.dkr.ecr.ap-southeast-1.amazonaws.com/on_premise/de/quod_ai_es_on_prem:21.10.2>) to YOUR_REPOSITORIES_URL/quod_ai_es_on_prem:21.10.2

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