Nowadays, cloud native environments have attracted lots of data-intensive applications deployed and ran on them, due to the efficient-to-deploy and easy-to-maintain advantages provided by cloud native platforms and frameworks such as Docker, Kubernetes. However, cloud native frameworks does not provide the data abstraction support to the applications natively. Therefore, we build Fluid project, which co-orchestrate data and containers together. We use Alluxio as the cache runtime inside Fluid to warm up hot data. In this report, we will introduce the design and effects of the Fluid project.
Nowadays, cloud native environments have attracted lots of data-intensive applications deployed and ran on them, due to the efficient-to-deploy and easy-to-maintain advantages provided by cloud native platforms and frameworks such as Docker, Kubernetes. However, cloud native frameworks does not provide the data abstraction support to the applications natively. Therefore, we build Fluid project, which co-orchestrate data and containers together. We use Alluxio as the cache runtime inside Fluid to warm up hot data. In this report, we will introduce the design and effects of the Fluid project.
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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.