ALLUXIO COMMUNITY OFFICE HOUR
We are thrilled to announce the release of Alluxio 2.5!
Alluxio 2.5 focuses on improving interface support to broaden the set of data driven applications which can benefit from data orchestration. The POSIX and S3 client interfaces have greatly improved in performance and functionality as a result of the widespread usage and demand from AI/ML workloads and system administration needs. Alluxio is rapidly evolving to meet the needs of enterprises that are deploying it as a key component of their AI/ML stacks.
At the same time, Alluxio continues to integrate with the latest cloud and cluster orchestration technologies. In 2.5, Alluxio has new connectors for Google Cloud Storage and Azure Data Lake Storage Gen 2 as well as better operability functionality for Kubernetes environments.
In this Office Hour, we will go over:
- JNI Based POSIX API
- S3 Northbound API
- ADLS Gen 2 Connector
- GCSv2 Connector
ALLUXIO COMMUNITY OFFICE HOUR
We are thrilled to announce the release of Alluxio 2.5!
Alluxio 2.5 focuses on improving interface support to broaden the set of data driven applications which can benefit from data orchestration. The POSIX and S3 client interfaces have greatly improved in performance and functionality as a result of the widespread usage and demand from AI/ML workloads and system administration needs. Alluxio is rapidly evolving to meet the needs of enterprises that are deploying it as a key component of their AI/ML stacks.
At the same time, Alluxio continues to integrate with the latest cloud and cluster orchestration technologies. In 2.5, Alluxio has new connectors for Google Cloud Storage and Azure Data Lake Storage Gen 2 as well as better operability functionality for Kubernetes environments.
In this Office Hour, we will go over:
- JNI Based POSIX API
- S3 Northbound API
- ADLS Gen 2 Connector
- GCSv2 Connector
Videos:
Presentation Slides:
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Videos
Fireworks AI is a leading inference cloud provider for Generative AI, powering real-time inference and fine-tuning services for customers' applications that require minimal latency, high throughput, and high concurrency. Their GPU infrastructure spans 10+ clouds and 15+ regions, serving enterprises and developers deploying production AI workloads at scale.
With model sizes reaching 70GB+, Fireworks AI faced critical challenges: eliminating cold start delays, managing highly concurrent model downloads across GPU clusters, reducing tens of thousands in annual cloud egress costs, and automating manual pipeline management that consumed 4+ hours weekly. They chose Alluxio as their solution to scale with their hyper-growth without requiring dedicated infrastructure resources.
In this tech talk, Akram Bawayah, Software Engineer at Fireworks AI, and Bin Fan, VP of Technology at Alluxio, share how Fireworks AI uses Alluxio to power their multi-cloud inference infrastructure.
They discuss:
- How Fireworks AI uses Alluxio in its high-performance model distribution system to deliver fast, reliable inference across multiple clouds
- How implementing Alluxio distributed caching achieved 1TB/s+ model deployment throughput, reducing model loading from hours to minutes while significantly cutting cloud egress costs
- How to simplify infrastructure operations and seamlessly scale model distribution across multi-cloud GPU environments
