What do you mean by this part? tailetc is a library used by the client of etcd.
Running an etcd cluster is much easier than running an HA PostgreSQL or MySQL config. (I previously made LiveJournal and ran its massively sharded HA MySQL setup)
The typical workflow is do do all of your "reads" out of the keyspace, attempt to apply Etcd transactions, and (if needed) block until your keyspace has caught up such that you read your write -- or someone else's conflicting write.
It also doesn't wrap transactions -- you use the etcd client directly for that.
The Nagel delay it implements helps quite a bit with scaling, though, while keeping the benefits of a tightly packed sorted keyspace. And you can directly access / walk decoded state without copies.
I guess Go package discovery remains an unsolved problem.
Or did you just not really search, like most of us excited to DIY? :-D
Godoc is pretty good, the package shows up for the searches I'd probably do in a similar situation.
Oh. Since they have a full cache of the database I thought it was intended to be used as a separate set of servers layered in front of etcd to lessen the read load. But you're actually using it directly? Interesting. What's the impact on memory usage and scalability? Are you not worried that this will not scale over time since all clients need to have all the data?
So architecturally it's:
3 or 5 etcd (forget what we last deployed) <--> 1 control process <--> every Tailscale client in the world
The "Future" section is about bumping "1 control process" to "N control processes" where N will be like 2 or max 5 perhaps.
The memory overhead isn't bad, as the "database" isn't big. Modern computers have tons of RAM.
Given that the goals seem to be improving performance over serializing a set of maps to disk as JSON on every change and keeping complexity down for fast and simple testing, a KV library would seem to accomplish both with less effort, without introducing dependence on an external service, and would enable the DB to grow out of memory if needed. Do you envision going to 2+ control processes that soon?
Any consideration given to running the KV store inside the control processes themselves (either by embedding something like an etcd or by integrating a raft library and a KV store to reinvent that wheel) since you are replicating the entire DB into the client anyway?
Meanwhile I'm working with application-sharded PG clusters with in-client caches with coherence maintained through Redis pubsub, so who am I to question the complexity of this setup haha.
What if you used one of the managed RDBMS services offered by the big cloud providers? BTW, if you don't mind sharing, where are you hosting the control plane?
We could (and likely would, despite the costs) but that doesn't address our testing requirements.
The control plane is on AWS.
We use 4 or 5 different cloud providers (Tailscale makes that much easier) but the most important bit is on AWS.
Curious: Was running DynamoDB with DAX (DynamoDB Accelerator) in front ever in contention? If not, is it due to vendor lock-in (for example, not being able to migrate out) or because tailscale doesn't feel the need to use managed offerings especially for core infrastructure?
> What if you used one of the managed RDBMS services offered by the big cloud providers?
Yeah, AWS RDS "multi-AZ" does a good job of taking care of HA for you. (Google Cloud SQL's HA setup is extremely similar.) But you still get 1-2 minutes of full unavailability when hardware fails.
I haven't operated etcd in production myself, but I assume it does better because it's designed specifically for HA. You can't even run less than three nodes. (The etcd docs talk about election timeouts on the order of 1s, which is encouraging.)
For many use cases, 1-2 minutes of downtime is tolerable. But I can imagine situations where availability is paramount and you're willing to give up scale/performance/features to gain another 9.