Running Ray Jobs on Azure

Azure

Microsoft Azure is a cloud computing platform that provides a wide range of services such as computing power, storage, and databases to businesses and individuals. Azure is known for its scalability, reliability, and security. It offers a pay-as-you-go pricing model which allows users to only pay for the services they use. Azure is used by many companies such as BMW, Samsung, and GE Healthcare.

Ray

Ray is an open-source distributed computing framework that makes it easy to build scalable and efficient applications. It was developed by a team at UC Berkeley's RISELab and has become increasingly popular over the years because of its ability to handle complex workloads with ease. Ray provides a simple API for building distributed applications, making it easy for developers to scale their applications without having to worry about the underlying infrastructure. Ray has been used for a wide variety of applications, including machine learning, reinforcement learning, data processing, and more. It has been adopted by many companies, including Amazon, NVIDIA, and Uber. Ray's popularity can be attributed to its ease of use, scalability, and flexibility.
Azure is a popular cloud option for companies looking to run Ray workflows at scale. Kaspian securely deploys into your Azure environment, ensuring that all storage and compute assets remain within your cloud. Kaspian's flexible compute layer empowers data teams to run Ray jobs on Azure in a highly performant, scalable, and configurable manner; no overpriced vendor markups or cloud-locking solutions required.
Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.

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