Alluxio is a proud sponsor and exhibitor at the AWS Summit in New York. If you weren't able to attend, here are the highlights!
What's AWS Summit? It's a one day conference bringing together the cloud computing community to engage on topics ranging from Machine Learning, Hybrid Cloud, Big Data & Analytics, and more.
What we learned
- Enterprises are advancing along the cloud journey, and data access has become a prevalent challenge, because enterprises adopting hybrid cloud are not able to efficiently access data on-premise and in their public cloud.
- Amazon's CTO Werner Vogels talks about AWS Outposts in his keynote. Amazon's investment in Outposts is another indication of the rise of hybrid cloud.
- Cloud applications are heavily weighed towards data driven applications such as analytics and machine learning applications.
Announcements
We were thrilled to have announced the release of Alluxio 2.0 at the Summit! Alluxio 2.0 is the largest release since inception with over 900 PRs as well as many new features to continue building on to our data orchestration approach for the cloud.
Learn more: Orchestrating Data for the Cloud World with Alluxio 2.0 , Download Alluxio
Thanks to everyone for stopping by the Alluxio booth and the great conversations!
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Blog
Coupang, a Fortune 200 technology company, manages a multi-cluster GPU architecture for their AI/ML model training. This architecture introduced significant challenges, including:
- Time-consuming data preparation and data copy/movement
- Difficulty utilizing GPU resources efficiently
- High and growing storage costs
- Excessive operational overhead maintaining storage for localized data silos
To resolve these challenges, Coupang’s AI platform team implemented a distributed caching system that automatically retrieves training data from their central data lake, improves data loading performance, unifies access paths for model developers, automates data lifecycle management, and extends easily across Kubernetes environments. The new distributed caching architecture has improved model training speed, reduced storage costs, increased GPU utilization across clusters, lowered operational overhead, enabled training workload portability, and delivered 40% better I/O performance compared to parallel file systems.
Suresh Kumar Veerapathiran and Anudeep Kumar, engineering leaders at Uptycs, recently shared their experience of evolving their data platform and analytics architecture to power analytics through a generative AI interface. In their post on Medium titled Cache Me If You Can: Building a Lightning-Fast Analytics Cache at Terabyte Scale, Veerapathiran and Kumar provide detailed insights into the challenges they faced (and how they solved them) scaling their analytics solution that collects and reports on terabytes of telemetry data per day as part of Uptycs Cloud-Native Application Protection Platform (CNAPP) solutions.
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