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So the problem is that the quality of its products would fall dramatically and then everyone would move to products offered by other large tech companies…

Regarding the "Durable Queueing Tradeoffs", doesn't Kafka prove you can be both durable and highly performant?

Well yes but with native annotations the linter you’re already using can do a lot of the type checking work so for many teams it’s not worth it to add Pytype or mypy

Pytype was cool before Python type annotations became widespread. It seems to me like the industry is naturally moving toward native type annotations and linters and away from static analyzers like Pytype and mypy.

Isn't Styra like a company of like 50-100 people? Seems like it'd be a bummer to be an employee at the company that gets left behind.

By switch I mean that all new projects use Valkey instead of Redis, and we've invested hundreds of hours into those new projects. We've also tried stuff with the Valkey Glide client.

By switch I mean that all new projects use Valkey instead of Redis, and we've invested hundreds of hours into those new projects.

Why would PaaS providers switch back to offering Redis? They've clearly all already invested a lot in Valkey (AWS, GCP, Heroku).

Our company made the switch over to Valkey, and we've invested hundreds of engineering hours into it already. I don't see us switching back at this point especially when it's clear Redis could easily pull the bait-and-switch again.

That makes sense! Thanks for the clarification

I'm having trouble in my head understanding how these workflows are actually executed in the open-source version. Are there workers somewhere? How do we provision those and scale those up and down?