On-Demand Videos
Nilesh Agarwal, Co-founder & CTO at Inferless, shares insights on accelerating LLM inference in the cloud using Alluxio, tackling key bottlenecks like slow model weight loading from S3 and lengthy container startup time. Inferless uses Alluxio as a three-tier cache system that dramatically cuts model load time by 10x.
In this talk, Jingwen Ouyang, Senior Product Manager at Alluxio, will share how Alluxio make it easy to share and manage data from any storage to any compute engine in any environment with high performance and low cost for your model training, model inference, and model distribution workload.
Storing data as Parquet files on cloud object storage, such as AWS S3, has become prevalent not only for large-scale data lakes but also as lightweight feature stores for training and inference, or as document stores for Retrieval-Augmented Generation (RAG). However, querying petabyte-to-exabyte-scale data lakes directly from S3 remains notoriously slow, with latencies typically ranging from hundreds of milliseconds to several seconds.
In this webinar, David Zhu, Software Engineering Manager at Alluxio, will present the results of a joint collaboration between Alluxio and a leading SaaS and data infrastructure enterprise that explored leveraging Alluxio as a high-performance caching and acceleration layer atop AWS S3 for ultra-fast querying of Parquet files at PB scale.
David will share:
- How Alluxio delivers sub-millisecond Time-to-First-Byte (TTFB) for Parquet queries, comparable to S3 Express One Zone, without requiring specialized hardware, data format changes, or data migration from your existing data lake.
- The architecture that enables Alluxio’s throughput to scale linearly with cluster size, achieving one million queries per second on a modest 50-node deployment, surpassing S3 Express single-account throughput by 50x without latency degradation.
- Specifics on how Alluxio offloads partial Parquet read operations and reduces overhead, enabling direct, ultra-low-latency point queries in hundreds of microseconds and achieving a 1,000x performance gain over traditional S3 querying methods.
Speaker: David Zhu
David Zhu is a Software Engineer Manager at Alluxio. At Alluxio, David focuses on metadata management and end-to-end performance benchmarking and optimizations. Prior to that, David completed his Ph.D. from UC Berkeley, with a focus on distributed data management systems and operating systems for the data center. David also holds a Bachelor of Software Engineering from the University of Waterloo.
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ALLUXIO DAY X 2022
March 3, 2022
Chen Liang from Uber and Beinan Wang from Alluxio will present the practical problems and interesting findings during the launch of Alluxio Local Cache. Their talk covers how Uber’s Presto team implements the cache invalidation and dashboard for Alluxio’s Local Cache. Chen Liang will also share his experience using a customized cache filter to resolve the performance degradation due to a large working set.
ALLUXIO DAY X 2022
March 3, 2022
Within Alluxio, the master processes keep track of global metadata for the file system. This includes file system metadata, block cache metadata, and worker metadata. When a client interacts with the filesystem it must first query or update the metadata on the master processes. Given their central role in the system, master processes can be backed by a highly available, fault tolerant replicated journal. This talk will introduce and compare the two available implementations of this journal in Alluxio, the first using Zookeeper and the more recent version using Raft.
ALLUXIO DAY X 2022
March 3, 2022
In this talk, Lei Li and Zifan Ni share the experience of applying Alluxio in their AI platform to increase training efficiency at bilibili. The talk also includes technical architecture and specific issues addressed.
Data platform teams are increasingly challenged with accessing multiple data stores that are separated from compute engines, such as Spark, Presto, TensorFlow or PyTorch. Whether your data is distributed across multiple datacenters and/or clouds, a successful heterogeneous data platform requires efficient data access. Alluxio enables you to embrace the separation of storage from compute and use Alluxio data orchestration to simplify adoption of the data lake and data mesh paradigms for analytics and AI/ML workloads.
Join Alluxio’s Sr. Product Mgr., Adit Madan, to learn:
- Key challenges with architecting a successful heterogeneous data platform
- How data orchestration can overcome data access challenges in a distributed, heterogeneous environment
- How to identify ways to use Alluxio to meet the needs of your own data environment and workload requirements
ALLUXIO DAY IX 2022
January 21, 2022
Video: Presentation Slides: Industrial Bank's Alluxio Deployment from Alluxio, Inc.
ALLUXIO DAY IX 2022
January 21, 2022
ALLUXIO DAY IX 2022
January 21, 2022
ALLUXIO DAY VIII 2021
December 14, 2021
Feifei Cai & Hao Zhu from WeRide provide an overview of Alluxio + Spark use case, which has been deployed and running in production to accelerate auto data tagging in the autonomous driving development.
ALLUXIO DAY VIII 2021
December 14, 2021
This talk will introduce Apache Iceberg and its place in a modern and open data platform. It will cover the motivation for creating Iceberg at Netflix, as well as the data architecture that Iceberg makes possible.
ALLUXIO DAY VIII 2021
December 14, 2021
This talk provides an overview of the read-after-write data consistent mechanism in the Alluxio system. Alluxio Core Maintainer and Presto Committer share their recent work on Alluxio and Apache Iceberg integration, as well as some recent work from the Presto community on Iceberg connector.
ALLUXIO DAY VI 2021
October 12, 2021
Apache Spark and Alluxio were both born in UC Berkeley’s AMPLab as research projects. As an open source data orchestration platform, Alluxio is able to achieve seamless docking and acceleration of different data sources, and improve the efficiency and fault tolerance of Spark’s big data computing business.
Alluxio has been deployed and running on a large scale managing petabytes level data in the production environment of companies such as Microsoft, Tiktok, Tencent, Singapore Development Bank, China Unicom, etc.
This talk shares the designs and use cases of the Alluxio and Spark integrated solutions, as well as the best practice and “what not to do” in designing and implementing Alluxio distributed systems.
ALLUXIO DAY VI 2021
October 12, 2021
In this talk, we will provide a complete picture of the Hudi platform components, along with their unique design choices. We will then deep dive into two important areas of active development going forward – table metadata management and caching. Specifically, we will discuss gaps in the data lake ecosystem around these aspects and provide strawman design approaches for Hudi aims to solve them going forward.