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Add support to RAG application to create a cluster for the user, or allow them to bring their own cluster #264

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merged 2 commits into from
Feb 29, 2024

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umeshkumhar
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@umeshkumhar umeshkumhar commented Feb 29, 2024

  • Create a cluster with appropriate nodepools/other config on behalf of the user
  • Still allow bringing your own cluster
  • Update marketplace blueprints with cluster creation options

@imreddy13 imreddy13 changed the title create cluster flow for rag application for marketplace usecase. Add support to RAG application to create a cluster for the user, or allow them to bring their own cluster Feb 29, 2024
imreddy13
imreddy13 previously approved these changes Feb 29, 2024
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@imreddy13 imreddy13 merged commit 176103f into main Feb 29, 2024
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@artemvmin
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FYI something in this commit changed tf apply (pre-deployment) plan generation from O(seconds) to O(minutes). Unless I made a mistake, we need to solve this or revert this change.

# at HEAD (this commit):
time (tf apply -var-file workloads.tfvars)` 
...
real    5m16.797s
user    8m49.858s
sys     0m22.037s
# at `HEAD~1`
time (tf apply -var-file workloads.tfvars)` 
...
real    0m20.667s
user    0m26.451s
sys     0m3.219s

artemvmin added a commit to artemvmin/ai-on-gke that referenced this pull request Mar 5, 2024
A recent change (GoogleCloudPlatform#264) introduced a regression, increasing local `tf plan` (a.k.a. `tf apply` pre-deployment step) time from 26s to 8m49s. This is not and acceptable latency for local development.

Change: GoogleCloudPlatform#264
artemvmin added a commit to artemvmin/ai-on-gke that referenced this pull request Mar 5, 2024
A recent change (GoogleCloudPlatform#264) introduced a regression, increasing local `tf plan` (a.k.a. `tf apply` pre-deployment step) time from 26s to 8m49s. This is not and acceptable latency for local development.

Change: GoogleCloudPlatform#264
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3 participants