This event features leading financial services company ING Bank’s user story on how they leverage open source technologies like Presto and Alluxio with S3.
Here in New York, at the AWS Summit, we are super excited to announce that Alluxio 2.0 is here, our most major release since the Alluxio launch. A couple months ago, we released 2.0 Preview – which included some of the capabilities, but 2.0 now includes even more, to continue building on to our data orchestration approach for the cloud.
In this meetup, Dipti and HY will present a new approach to hybrid analytical workloads using Alluxio, an open source data orchestration layer, which sits between compute and storage layer. Applications like Apache Spark or TensorFlow can then seamlessly access multiple disparate data sources with consistent performance using data locality and abstraction that the data orchestration tier brings.
This article aims to provide a different approach to help connect and make distributed files systems like HDFS or cloud storage systems look like a local file system to data processing frameworks: the Alluxio POSIX API. To explain the approach better, we used the TensorFlow + Alluxio + AWS S3 stack as an example.
Alluxio is a proud sponsor and exhibitor at the Presto Summit in San Francisco.
What’s Presto Summit? It’s the leading Presto conference co-organized by our partner Starburst Data and the Presto Software Foundation.
Haoyuan Li’s keynote at O’Reilly Beijing discusses open source data orchestration and the value of leveraging Alluxio with rising trends driving the need for a new architecture. Four big trends driving this need: Separation of compute & storage, hybrid-multi cloud environments, rise of object store and self-service data across the enterprise.
Tags: big data, cloud, cloud object storage, cloud storage, compute storage separation, conference, data, data orchestration, hybrid cloud, multi cloud, on-prem object storage, storage
While running analytics workloads using EMR Spark on S3 is a common deployment today, many organizations face issues in performance and consistency. EMR can be bottlenecked when reading large amounts of data from S3, and sharing data across multiple stages of a pipeline can be difficult as S3 is eventually consistent for read-your-own-write scenarios.
A simple solution is to run Spark on Alluxio as a distributed cache for S3. Alluxio stores data in memory close to Spark, providing high performance, in addition to providing data accessibility and abstraction for deployments in both public and hybrid clouds.
Tags: aws, cloud, compute storage separation, data, data orchestration, emr, hybrid cloud, on-prem object storage, spark, tech talk
The data orchestration layer bridging the gap between data locality with improved performance and data accessibility for analytics workloads in Kubernetes, and enables portability across storage providers.
An overview of Alluxio and the cloud use case with Spark in Kubernetes. Learn how to set up Alluxio and Spark to run in Kubernetes.
Tags: analytics, apache spark, compute, compute storage separation, data, data orchestration, hybrid cloud, kubernetes, locality, multi cloud, office hour, spark, storage
Learn how to set up Presto with Alluxio such that Presto jobs can seamlessly read from and write to S3.
Compare the performance between Presto on S3 with Presto and Alluxio on S3.