| > I should have just used on-disk mode from the start, but only now know better. Yeah, I saw the recent post about reducing rqlite disk space usage. Using the on-disk sqlite as both the FSM and the Raft snapshot makes a lot of sense here. I'm curious whether you've had concerns about write amplification though? Because we have only the periodic Raft snapshots and the FSM is in-memory, during high write volumes we're only really hammering disk with the Raft logs. > Do you find it in the field much with Nomad? I've managed to introduce new Raft Entry types very infrequently during rqlite's 10-years of development, only once did someone hit it in the field with rqlite. My understanding is that rqlite Raft entries are mostly SQL statements (is that right?). Where Nomad is somewhat different (and probably closer to the OP) is that the Raft entries are application-level entries. For entries that are commands like "stop this job"[0] upgrades are simple. The tricky entries are where the entry is "upsert this large deeply-nested object that I've serialized", like the Job or Node (where the workloads run). The typical bug here is you've added a field way down in the guts of one of these objects that's a pointer to a new struct. When old versions deserialize the message they ignore the new field and that's easy to reason about. But if the leader is still on an old version and the new code deserializes the old object (or your new code is just reading in the Raft snapshot on startup), you need to make sure you're not missing any nil pointer checks. Without sum types enforced at compile time (i.e. Option/Maybe), we have to catch all these via code review and a lot of tedious upgrade testing. > it requires discipline on the part of the end-users too. Oh for sure. Nomad runs into some commercial realities here around how much discipline we can demand from end-users. =) [0] https://github.com/hashicorp/nomad/blob/v1.8.2/nomad/fsm.go#...
[1] https://github.com/hashicorp/nomad/blob/v1.8.2/nomad/fsm.go#... |
I mean, yes, the more disk IO rqlite has to make to more write performance will be affected. However the advantages of running with an on-disk SQLite database are worth it I believe. In addition rqlite supports storing the SQLite database file on a memory-backed filed system if users really want that[1]. That can help squeeze more write throughput out of rqlite.
>My understanding is that rqlite Raft entries are mostly SQL statements (is that right?).
That's right, rqlite does statement-based replication, though I'm currently looking into extending it so it also does changeset[2] replication where it makes sense.
[1] https://rqlite.io/docs/guides/performance/#use-a-memory-back...
[2] https://www.sqlite.org/sessionintro.html