We purchased the Enclave product which was really well-suited for us because it let us run the hosts in our own Google cloud account (at our pricing with Google), and thus didn't require us to transfer any data out which was well-aligned with our security stance. It provided light-touch deployment and observability services that we lacked and helped us bootstrap quickly and with minimal investment. The Vespa search backend itself provided a good match to our requirements of near-real time hybrid search, combining nearest neighbor embedding search with attribute filters, in a distributed and highly scalable way. Our target installation comprised >12TB of memory across 24 hosts and held O(1B) vector embeddings.

I like the open-source and free 300 dollar cloud credits for hosting the live applications.

I can create recommendation applications and deploy real-time machine learning inference using this stack. Such a level of functionality is what we need for our large scale search applications.