Benchling's engineering team writes about Postgres migrations, React performance, and CRISPR and DNA search for its biotech software.
HN commenters call its Lambda-based CRISPR search a compelling use case, and discuss its migration and React performance posts, with one saying the migration post is too high-level.
It is, so a DOM change wouldn't occur, but in these cases you still go through a React rendering to virtual DOM phase (templating) and the DOM tree reconciliation.
Since these can be slow (although much faster than a DOM change), it makes sense to check and skip those steps when you can.
The focus of most of this article is how you can skip those steps when you're components input data is unchanged and common gotchas related to that.
Some other great posts in this vein are:
https://facebook.github.io/react/docs/optimizing-performance.html
and
http://benchling.engineering/performance-engineering-with-react/
programming in time is hard
(especially with migrations, because migrations take time)
this feels too high-level -- different migration operations can afford different guarantees (esp in the multi-node case). In particular this doesn't talk about data migrations, where you might need to lock 2 tables + join them to generate a third. not all migrations are pure-sql either, they may include app code
my favorite article about this is benchling's https://benchling.engineering/move-fast-and-migrate-things-how-we-automated-migrations-in-postgres-d60aba0fc3d4 because it talks about pre + post deploy migrations
I would be thrilled if they provided an update, but Benchling's CRISPR search is what originally got me excited about Lambda. It's an incredibly compelling use case, as it enabled one second searches at any level of demand. And, their hosting costs dropped from thousands of dollars on EC2 to $60 on Lambda.
http://benchling.engineering/crispr-aws-lambda/
I don't know the answer to how Neon would affect that, but AFAIK, you can already do this:
http://julienblanchard.com/2015/rust-on-aws-lambda/
But that uses a shell command. There's also this way to do so using FFI (article is about C++, but I'm pretty sure you could do the same with Rust):
http://benchling.engineering/crispr-aws-lambda/
maybe WRT to https://www.google.com/search?q=genome+sequencing+algorithms which would be needed to find unique patterns among billions of base pairs for CRISPR to target. it's microscopic big data :D
[1] http://benchling.engineering/dna-regex-search/?hn
[2] http://benchling.engineering/optimizing-crispr/