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  • Luna
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Luna provisions just-in-time right-sized cost-effective compute for your app when your app starts and terminates the compute when the app terminates.
Usecases
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ML

ML workloads like Ray are bursty and use GPU devices which are expensive to waste - this makes them a great fit for Luna. Check out our CNCF blogpost to see how Luna powering a GPU Ray cluster with a GPU-enabled Ray Head reduced elapsed time by 61%, computing cost by 54%, and idle Ray cluster cost by 66%, while retaining the performance quality of the AutoML results and reducing operational complexity.  

CI

Build/test workloads are bursty in nature and require predictable resources. Luna is a great fit for CI since it eliminates wait times during unexpected spikes and prevents wasted spend on unused capacity during downtimes (ex: nights, weekends). Luna works seamlessly with any CI orchestrator (Buildkite, CircleCI, GitHub Actions, Jenkins, etc).

Mobile CI

The availability of mac1.metal instances on AWS is a game-changer in consolidating Mac workloads on the cloud. Luna eliminates DevOps overhead associated with:
  • maintaining Mac footprint on a third party vendor (MacStadium, Flow.Swiss, etc),
  • setting up networking plumbing between Mac vendor and your primary cloud provider,
  • maintaining security best practices for communications between Mac vendor and AWS,
  • manual capacity management of expensive Mac compute on AWS with quirky 24 hour billing cycles.
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