Alluxio 2.0 is the most ambitious platform upgrade since the inception of Alluxio with greatly expanded capabilities to empower users to run analytics and AI workloads on private, public or hybrid cloud infrastructures leveraging valuable data wherever it might be stored.
This release, now available for download, includes many advancements that will allow users to push the limits of their data-workloads in the cloud.
In this tech talk, we will introduce the key new features and enhancements such as:
- Support for hyper-scale data workloads with tiered metadata storage, distributed cluster services, and adaptive replication for increased data locality
- Machine learning and deep learning workloads on any storage with the improved POSIX API
- Better storage abstraction with support for HDFS clusters across different versions & active sync with Hadoop
Alluxio 2.0 is the most ambitious platform upgrade since the inception of Alluxio with greatly expanded capabilities to empower users to run analytics and AI workloads on private, public or hybrid cloud infrastructures leveraging valuable data wherever it might be stored.
This release, now available for download, includes many advancements that will allow users to push the limits of their data-workloads in the cloud.
In this tech talk, we will introduce the key new features and enhancements such as:
- Support for hyper-scale data workloads with tiered metadata storage, distributed cluster services, and adaptive replication for increased data locality
- Machine learning and deep learning workloads on any storage with the improved POSIX API
- Better storage abstraction with support for HDFS clusters across different versions & active sync with Hadoop
Videos:
Presentation Slides:
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Videos
Pratik Mishra delivered insights on architecting scalable, deployable, and resilient AI infrastructure at scale. His discussion on fault tolerance, checkpoint optimization, and the democratization of AI compute through AMD's open ecosystem resonated strongly with the challenges teams face in production ML deployments.
In this talk, Bin Fan, VP of Technology at Alluxio, presents on building tiered architectures that bring sub-millisecond latency to S3-based workloads. The comparison showing Alluxio's 45x performance improvement over S3 Standard and 5x over S3 Express One Zone demonstrated the critical role the performance & caching layer plays in modern AI infrastructure.
In this talk, Greg Lindstrom shared how Blackout Power Trading achieved double-digit millisecond offline feature store performance using Alluxio, a game-changer for real-time power trading where every millisecond counts. The 60x latency reduction for inference queries was particularly impressive.