I've heard from the industry that the issue with GSA was that it just wasn't that good. It tried to adapt Google's core search into a box, but Google's algorithm is only great because of scale. The box doesn't have as much of an opportunity to learn from user interactions and thus fails to meet expectations.
The GSA "just worked". Also having the name recognition for public search did a lot to drive its enterprise popularity. It didn't have a lot of bells/whistles, but it addressed the commodity search problem well.
Agreed relevancy is a problem. PageRank works well for public content but internal search has plenty of relevancy problems. Having little control over this certainly hurt.
Managing on-prem hardware/appliances is a difficult business. I don't fault them for moving to a more scaleable model.
This is a trend for AWS. The building blocks (S3, EBS, EC2, Lambda, Dynamo) are priced at cost + margin, and prices tend to improve.
The more niche/higher level services like kendra are priced based on the value to a medium to large company.
They don’t expect individual developers to use this, or build anything on top of it. They expect a partner or employee of the company to do a pilot on the developer pricing, then convert to the enterprise pricing.
It’s a somewhat annoying trend but imo Google Cloud is a much worse offender here, everything new from them seems to be on prem “call sales for pricing” aimed at the enterprise.
But for the AWS offering, you get less than one mean query per second (capped per day). I would think ElasticSearch on the same hardware would offer a couple orders of magnitude more throughput.
The AWS pages talk about "document scanning," so perhaps this product is poised more towards replacing an office full of humans and filing cabinets, which most definitely costs more than $7/hr. This is the gateway product to wanting ElasticSearch.
