Introducing what’s new in 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.

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What’s New in Alluxio 2.5

Community Online Office Hour *

Alluxio 2.5 focuses on improving interface support to broaden the set of data driven applications which can benefit from data orchestration.

Introduction to what’s new in Alluxio 2.4

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Alluxio 2.4.0 focuses on features critical to large scale, production deployments in Cloud and Hybrid Cloud environments. Features such as highly scalable metadata journaling, aggregate cluster metrics monitoring, and automated detection of JVM pauses further improve Alluxio’s suitability for demanding workloads.

What’s New in Alluxio 2.3

Community Online Office Hour *

Alluxio 2.3 was just released at the end of June 2020. Calvin and Bin will go over the new features and integrations available and share learnings from the community. Any questions about the release and on-going community feature development are welcome.

Bursting Spark or Presto Jobs to AWS using Alluxio

In this office hour, we demonstrate how a “zero-copy burst” solution helps to speed up Spark and Presto queries in the public cloud while eliminating the process of manually copying and synchronizing data from the on-premise data lake to cloud storage. This approach allows compute frameworks to decouple from on-premise data sources and scale efficiently by leveraging Alluxio and public cloud resources such as AWS.

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Bursting Spark or Presto Jobs to AWS using Alluxio

Community Online Office Hour *

In this office hour, we demonstrate how a “zero-copy burst” solution helps to speed up Spark and Presto queries in the public cloud while eliminating the process of manually copying and synchronizing data from the on-premise data lake to cloud storage. This approach allows compute frameworks to decouple from on-premise data sources and scale efficiently by leveraging Alluxio and public cloud resources such as AWS.