ALLUXIO COMMUNITY OFFICE HOUR
In this talk, we describe the architecture to migrate analytics workloads incrementally to any public cloud (AWS, Google Cloud Platform, or Microsoft Azure) directly on on-prem data without copying the data to cloud storage.
In this Office Hour:
- We will go over an architecture for running elastic compute clusters in the cloud using on-prem HDFS.
- Have a casual online video chat with Alluxio Open Source core maintainers to address any Alluxio related questions from our community members
ALLUXIO COMMUNITY OFFICE HOUR
In this talk, we describe the architecture to migrate analytics workloads incrementally to any public cloud (AWS, Google Cloud Platform, or Microsoft Azure) directly on on-prem data without copying the data to cloud storage.
In this Office Hour:
- We will go over an architecture for running elastic compute clusters in the cloud using on-prem HDFS.
- Have a casual online video chat with Alluxio Open Source core maintainers to address any Alluxio related questions from our community members
Video:
Slides:
Videos:
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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.