NVIDIA / NVIDIA/cuvs

[EXAMPLE] End-to-end workflow for deploying cuVS build on serverless architectures

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doc example exploration
Dominant language
Cuda
Stars
854
Forks
236
Avg merge
3d 3h
Merged PRs (30d)
62

Description

Ideally this would build on cuVS' Docker "microservice" layer and would provide a reasonably realistic end-to-end example demonstrating how a user would deploy this in practice. This could be really helpful for both applications developers and vector database developers alike.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing cuVS's Docker "microservice" layer and determine which serverless architecture the example should target. Done means providing a realistic end-to-end deployment workflow that application and vector database developers can follow in practice.

Written by the indexing model from the issue text.

Assessment

Tech stack
docker
Domain
cloud, devops
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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