On the other hand, I don’t think figuring out “when” to invalidate is what makes cache invalidation hard. I shared the same view as Marc https://twitter.com/marcjbrooker/status/1534944340266864640?....
There is a trade off between coordination (in some cases with unbounded write amplification https://twitter.com/uvdn7/status/1534979480363667457?s=21&t=...) and relaxed consistency. I assumed this is a trade off that people just have to make based on their workload (hence you saw me saying in other comments about TTL; it’s about tradeoffs, when the cost of coordination/invalidate surpasses the benefit — higher hit rate, etc.)
I acknowledge that both are hard. The former can't be avoided. And the latter is easy in certain cases (if you have a simpler data model, etc.). I am not saying the latter is easy. More details in https://news.ycombinator.com/item?id=31676102
And I made the mistake of assuming the definition of “cache invalidation” as it means different things to different people. Marc’s view is a very good one https://twitter.com/marcjbrooker/status/1534944340266864640?... but it’s actually different than some people’s definition on this thread.
I will not defend myself; and you are welcome to speculate. I said it here https://twitter.com/uvdn7/status/1534978702609682432, and other places on this thread, and I will repeat it again.
I should have applied a narrower and more specific definition of cache invalidation in the blog post. The confusion it caused is not intended.
> how to implement invalidating it when you know exactly what needs invalidation
I stand by the claim that this is a hard problem, as explained in the blog post. When you deal with a cache you are inherently dealing with a distributed system (there's cache and the source of truth). And the contribution is making this aspect more manageable, which is common to all invalidation based caches.
I am trying to help.