What to arrange with your platform team, and how to run vector search in production. Start with Setup to get Query Engine access; read Security, Performance and sizing, and CI/CD and automation as you move toward production.
- Setup: What to request from your platform team for Query Engine access, a copyable request, and a check that searches work.
- Security: Which actions, row filters and column rules apply when searching vectors through the VAST Query Engine, and which don't.
- Performance and sizing: Check index state, reduce what a search reads, spread load and estimate the space a vector table uses on the cluster.
- CI/CD and automation: Create vector-indexed tables from a pipeline with the VMS REST API, vastpy, or Terraform with the Python SDK.