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Alluxio 2.0 Debuts

March 8, 2019

Alluxio 2.0 is the most ambitious platform upgrade since the inception of Alluxio. This preview release, now available for free download, is the largest open source release with the most new features added since the creation of the project and is designed to allow the community to experiment with new capabilities and explore Alluxio for new use cases such as simplifying data engineering and access for AI model training.

“Today, our users already deploy Alluxio at very large scale with many thousand node single cluster production deployments across telecommunications, retail and internet companies,” said Haoyuan Li, CEO and co-founder of Alluxio. “This release allows our users to take Alluxio deployments to the next level of scale with support for extreme data requirements. Our users as well as the data engineering community will find a much more intuitive interface with greatly expanded capabilities to help them run analytics and AI workloads on private, public or hybrid cloud infrastructures leveraging valuable data wherever it might be stored.”

“At China Unicom, we use Alluxio at scale as a core component of our modern data stack along with Apache Spark, HDFS, Hive and Apache Kafka. We are excited about Alluxio 2.0, particularly the new metadata management and scale out capabilities that will allow us to continue elastically scaling our deployment for the explosive data growth we see coming,” said Ce Zhang, Senior Software Engineer at China Unicom Software Research Institute.

“AVA -- our cloud-native deep learning platform -- is built on Tensorflow, Caffe, Alluxio and KODO (a customized object store and CEPH). Alluxio orchestrates data movement from storage systems to data science environments, eliminating complex data engineering tasks and speeding up model training. Alluxio 2.0’s improved file system API to access data stored in any storage system will allow for accelerating machine learning training even further for faster innovation,” said Chaoguang Li, Technical Director of Atlab at Qiniu Cloud.
 

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