UC Berkeley Launches SkyPilot To Help Navigate Soaring Cloud Costs
SkyPilot developer and postdoctoral researcher Zongheng Yang said in a blog post that the growing trend of multi-cloud and multi-region strategies led the team to build SkyPilot, calling it an “intercloud broker.” He notes that organizations are strategically choosing a multi-cloud approach for higher reliability, avoiding cloud vendor lock-in, and stronger negotiation leverage, to name a few reasons. To save costs, SkyPilot leverages the large price differences between cloud providers for similar hardware resources. Yang gives the example of Nvidia A100 GPUs, and how Azure currently offers the cheapest A100 instances, but Google Cloud and AWS charge a premium of 8% and 20% for the same computing power. For CPUs, some price differences can be over 50%. […]
The project has been under active development for over a year in Berkeley’s Sky Computing Lab, according to Yang, and is being used by more than 10 organizations for use cases including GPU/TPU model training, distributed hyperparameter turning, and batch jobs on CPU spot instances. Yang says users are reporting benefits including reliable provisioning of GPU instances, queueing multiple jobs on a cluster, and concurrently running hundreds of hyperparameter trials.
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