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With platforms like Scaleway that has an API and provide not only macOS infrastructure but a more generic one. We can add builtin functionality that will scale Orchard workers up and down based on the demand.
There are couple things to consider:
Orchard Auto-Scaler can configure workers automatically via SSH. Our Ansible roles are not that hard to replicate in scripts.
Auto-scaler should be aware of the 24 hours minimum limit of that we can rent hosts for.
I think the initial algorithm version should be super simple. There should be just couple configurations:
maximumWorkers/minimumWorkers - range to scale workers within.
upscaleSpeed - percentage to which upscale in one iteration. For example, if there are 10 unschedulable VMs in the queue and speed in 50% then the auto-scaler will create 3 nodes to fit 5 VMs.
upscaleInterval - duration to wait before the next upscale attempt.
Similar downscaleSpeed / downscaleInterval
Something else?
In case of auto-scaling we should also consider changing scheduling algorithm for maximum utilization -- prefer to schedule as many VMs on the same host as possible before going to the next one.
The text was updated successfully, but these errors were encountered:
With platforms like Scaleway that has an API and provide not only macOS infrastructure but a more generic one. We can add builtin functionality that will scale Orchard workers up and down based on the demand.
There are couple things to consider:
I think the initial algorithm version should be super simple. There should be just couple configurations:
maximumWorkers
/minimumWorkers
- range to scale workers within.upscaleSpeed
- percentage to which upscale in one iteration. For example, if there are 10 unschedulable VMs in the queue and speed in 50% then the auto-scaler will create 3 nodes to fit 5 VMs.upscaleInterval
- duration to wait before the next upscale attempt.downscaleSpeed
/downscaleInterval
In case of auto-scaling we should also consider changing scheduling algorithm for maximum utilization -- prefer to schedule as many VMs on the same host as possible before going to the next one.
The text was updated successfully, but these errors were encountered: