CoreDNS VS groupcache

CoreDNS supports this via the bind plugin.

I'd like to use Cloudflare's 1.1.1.1 and 1.0.0.1 nameservers in Kubernetes, alongside DNS over TLS. It looks like I can do it using core-dns. I need to setup the following somehow:

Shamless plug for CoreDNS. Much better DNS server than classic bind9. And of course there's already a nice container image for it.

But another approach that could work in Kubernetes, because the DNS servers are within the cluster itself, would be to work directly with the DNS server pods. In most Kubernetes clusters, whether standalone or managed (GKE, AKS, EKS), the cluster DNS is either coredns or kube-dns. That was great to minimize how much configuration options we’d need to support. We realized we could edit the coredns or kube-dns configmap resources to enable their log option, which would make them log all the queries they handle. We’ll cover exactly how it’s done in more detail below.

CoreDNS has an ectd plugin, so your service could add entries to a database, which is used as record source. Not the same mechanism as you have described, but it will get the job done. Also this is what Kubetnetes does for incluster dns records.

nevermind there's caddy builtin upgrade method https://github.com/coredns/coredns/issues/6034

Coredns can be spun up in a docker container, just starting to get into it myself

CoreDNS is a pretty good DNS server.

Core DNS (https://coredns.io).

As shown in the title, DREAMEMO is a distributed cache with out-of-the-box, high-scalability, modular-design features.The groupcache implementation is referenced, and re-structured, specific module differentiation is as follows:

I remember one of the first real-world uses of Go being the groupcache package: https://github.com/golang/groupcache (to serve Chrome downloads, IIRC?)

> comes with a cache filling mechanism. Whereas memcached just says "Sorry, cache miss", often resulting in a thundering herd of database (or whatever) loads from an unbounded number of clients (which has resulted in several fun outages), groupcache coordinates cache fills such that only one load in one process of an entire replicated set of processes populates the cache, then multiplexes the loaded value to all callers.

I read that group cache (https://github.com/golang/groupcache) can be used to sync servers around a key.

I've not tried this myself, but I've seen it suggested to use groupcache (https://github.com/golang/groupcache) to sync your servers.

https://github.com/golang/groupcache is managing distributed caching that addresses thundering herd problem of memcache.

How it goes sometimes. Check out https://github.com/golang/groupcache and of course the AWS golang SDK.

There is also groupcache, written by the same author as memcached, but better.