Update dependents and fix frontend issues #287
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umeshkumhar
commented
Mar 5, 2024
•
umeshkumhar
commented
- introduce namespace helm module to prepare namespace before actual module, earlier this was done using depends_on = kuberay_operator
- optmise frontend module to read endpoint from module output and remove addtional data sources.
- set l4 node-locations default to us-central1-a for less quota or stockout issues.
- disable IAP as default option.
- tf plan reduced to 40s to 8s
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/gcbrun |
imreddy13
reviewed
Mar 5, 2024
| @@ -193,8 +198,7 @@ module "frontend" { | |||
| create_service_account = var.create_rag_service_account | |||
| google_service_account = var.rag_service_account | |||
| namespace = var.kubernetes_namespace | |||
| inference_service_name = module.inference-server.inference_service_name | |||
| inference_service_namespace = module.inference-server.inference_service_namespace | |||
| inference_service_endpoint = module.inference-server.inference_service_endpoint | |||
| db_secret_name = module.cloudsql.db_secret_name | |||
| db_secret_namespace = module.cloudsql.db_secret_namespace | |||
| @@ -24,6 +24,7 @@ kubernetes_namespace = "rag" | |||
| create_gcs_bucket = true | |||
| gcs_bucket = "rag-data-xyzu" # Choose a globally unique bucket name. | |||
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| cloudsql_instance = "pgvector-instance" | |||
| output "inference_service_endpoint" { | ||
| description = "Endpoint of model inference service" | ||
| value = kubernetes_service.inference_service.status != null ? (kubernetes_service.inference_service.status[0].load_balancer != null ? "${kubernetes_service.inference_service.status[0].load_balancer[0].ingress[0].ip}" : "") : "" |
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why do we need these conditions?
| @@ -171,7 +157,7 @@ resource "kubernetes_deployment" "rag_frontend_deployment" { | |||
| name = "DB_PASSWORD" | |||
| value_from { | |||
| secret_key_ref { | |||
| name = data.kubernetes_secret.db_secret.metadata.0.name | |||
| name = var.db_secret_name | |||
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did you test this? is the secret name the same as the value of "kubernetes_secret.db_secret.metadata.0.name"?
can you please make sure this works E2E? you will need to run the notebook to load data into the cloud sql instance, then launch the frontend and make a query.
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+1 and please verify with Autopilot. Instructions for deploying AP cluster in the README.
artemvmin
reviewed
Mar 5, 2024
| @@ -142,14 +148,14 @@ module "jupyterhub" { | |||
| url_domain_name = var.jupyter_url_domain_name | |||
| members_allowlist = var.jupyter_members_allowlist | |||
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| depends_on = [module.kuberay-operator, module.gcs] | |||
| depends_on = [module.namespace, module.gcs] | |||
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This makes way more sense, thank you. This will also improve apply time, since both kuberay-operator and jupyterhub take O(minutes) to deploy.
artemvmin
reviewed
Mar 5, 2024
| @@ -16,20 +16,6 @@ data "google_project" "project" { | |||
| } | |||
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| data "kubernetes_service" "inference_service" { | |||
artemvmin
approved these changes
Mar 5, 2024
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