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Comment by randerson | Hacker News Reader

And the former is the one you want your Load Balancers to be checking. With a deep health check, even a brief database outage will cause every web server to be taken out of rotation, and then you're completely down for at least as many health check intervals as it takes for the LB to consider a host healthy again. Same goes for any other shared resource that is likely to affect all web servers if it becomes unavailable.

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Presumably your service would not be in a very useful state anyway if the main data store it needs to function is out, so which kind of health-check you use will depend on the failure mode you want to expose to your users.

Or you just have smarter load balancers, that realize when all of their servers are acting funky and stop taking servers out of rotation.

Or to riff on this idea further: You make the concept of a node's "relative stability" part of the load-balancer logic the same way that "relative idleness" is a factor.

Then if all 100/100 nodes get taken down by some shared problem, the system simply degenerates into picking the idle-est of the 100.

That's not necessarily true. In kubernetes, for example, you have Liveness and Readiness probes, which can both have a period, timeout, initial delay and importantly a number of failures before you kill the service and spawn a new one.

This allows you to have less frequent checks that are more in-depth, and basic ones that are just the `return true` type.

I guess you're correct that you can have a widespread db outage that makes many of them fail, but then there should be new ones coming very fast, as you can set the deployment minimum for services taking requests. I think you can get very close to stability even in this circumstance.

https://kubernetes.io/docs/tasks/configure-pod-container/con...

Databases are 10-100x as reliable as the application tier in my experience

Although the OP didn't describe as such, but health checks that do a simple query are also testing the connectivity to the db. Someone might have hardcoded a db address in an environment variable, or there are connection pooling issues.

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