Hey all,
I have looked for some more in depth performance metrics/scaling information about LL and haven't found much. Does anyone have any tips, tricks or things I should watch out for when migrating a decent sized LP setup to LL? I wrote a LP based bot in like 2017/18 and it's been sitting for a long time, finally porting it to a solution I can scale out with and don't want to write one myself. LL will be running on a k8s node with 16gb of ram and 6 xeon e-2697v2 cores.
For reference my LL usage metrics are expected to be:
- 200-500 active streams at any given time, depending on time of day
- 30-40k track loads per day, balanced across a couple /64 ranges
- Expecting 30+ qps to the api at peak
- Even though I haven't touched the bot in years voice usage is growing ~20% MoM, so I want to plan for a lot more down the line. For when I don't have time to work on it, it hopefully wont run into issues.
I would imagine this scale is fine for a one node setup for now, I already ported everything to LL and hoping to roll out this week. Does LL seem to like scaling up, out or either? Eventually I am going to at the least spin up basic low spec nodes in each major region. I also typically ran a larger than defualt (800ms - 2000ms) JDA-NAS buffer to help against stuttering, in LL how does that effect resource usage? I would imagine just minimal RAM impact.
Thanks for the help and wisdom :)