The Alluxio core engineering team re-designed things to come up with a more efficient and transparent way for users to leverage data orchestration through the POSIX interface. This enables much better performance for ML workloads where data is accessed via the POSIX interface.
Tags: data orchestration, fuse, ml, performance, POSIX, pytorch, tensorflow
ALLUXIO DAY V 2021 August 27, 2021 Speaker: Lu Qiu has been involved in open source software for many years and is currently a software engineer at Alluxio. Lu develops easier ways for Alluxio integration in the public cloud environment. Lu is mainly responsible for leader election, journal management, metrics management, and big data preparation for … Continued
Tags: alluxio day, data orchestration
Alluxio’s distributed systems experts explore today’s data access challenges and open source data orchestration solutions for modernizing your data platform.
Tags: ai, analytics, data orchestration, data platform, hybrid cloud, webinar
Driven by strong interests from our open-source community, the core team of Alluxio started to re-design an efficient and transparent way for users to leverage data orchestration through the POSIX interface.
Join Alluxio’s distributed systems experts as they explore today’s data access challenges and open source data orchestration solutions for modernizing your data platform.
Join Alluxio’s distributed systems experts as they explore today’s data access challenges and open source data orchestration solutions for modernizing your data platform.
Join us at ApacheCon to learn how Alluxio’s capabilities as a Data Orchestration framework have encouraged users to onboard more of their data-driven applications to an Alluxio powered data access layer.
Alluxio joins Eric Kavanagh of Bloor Group and host of DM Radio, “Let’s talk data” at an upcoming show.
Alluxio 2.6 significantly improves the performance of data-intensive AI/ML workloads across any storage, and also improves the general maintainability and visibility of Alluxio clusters, especially for large-scale deployments. We have taken the feedback and contributions from the community and introduced features which simplify deployment, introduce new data management capabilities, optimize performance, and provide enhanced visibility into system behavior.