Reducing Large S3 API Costs Using Alluxio
This article described how engineers at datasapiens brought down S3 API costs by 200x by implementing Alluxio as a data orchestration layer between S3 and Presto.
This article described how engineers at datasapiens brought down S3 API costs by 200x by implementing Alluxio as a data orchestration layer between S3 and Presto.
As the third largest e-commerce site in China, Vipshop processes large amounts of data collected daily to generate targeted advertisements for its consumers. In this article, Gang Deng from Vipshop describes how to meet SLAs by improving struggling Spark jobs on HDFS by up to 30x, and optimize hot data access with Alluxio to create … Continued
Migrating SQL workloads from a fully on-premise environment to cloud infrastructure has numerous benefits, including alleviating resource contention and reducing costs by paying for computation resources on an on-demand basis. In the case of Presto running on data stored in HDFS, the separation of compute in the cloud and storage on-premises is apparent since Presto’s … Continued
Alluxio 2.3.0 focuses on streamlining the user experience in hybrid cloud deployments where Alluxio is deployed with compute in the cloud to access data on-prem. Features such as environment validation tools and concurrent metadata synchronization greatly improve Alluxio’s functionality. Integrations with AWS EMR, Google Dataproc, K8s, and AWS Glue make Alluxio easy to use in a variety of cloud environments. In this article, we will share some of the highlights of the release. For more, please visit our release notes page.
This article describes how engineers in the Data Service Center at Tencent PCG leverages Alluxio to optimize the analytics performance by 200% and minimize the operating cost in building Tencent Beacon Growing, a real-time data analytics platform.
Google’s TensorFlow and Facebook’s PyTorch are two Deep Learning frameworks that have been popular with the open source community. Although PyTorch is still a relatively new framework, many developers have successfully adopted it due to its ease of use. By default, PyTorch does not support Deep Learning model training directly in HDFS, which brings challenges … Continued
A collaboration of Alibaba, Alluxio, and Nanjing University in tackling the problems of Deep Learning model training in the cloud. Our goal was to reduce the cost and complexity of data access for Deep Learning training in a hybrid environment, which resulted in over 40% reduction in training time and cost.
International Data Corporation (IDC) reported that the global datasphere will grow from 33 zettabytes in 2018 to 175 zettabytes by 2025. This trend becomes more and more complicated with the variety and velocity of data growth, and it continuously changes the ways how data is collected, stored, processed and analyzed. New analytics solutions from machine … Continued
This article describes how Alluxio can accelerate the training of deep learning models in a hybrid cloud environment when using Intel’s Analytics Zoo open source platform, powered by oneAPI. Details on the new architecture and workflow, as well as Alluxio’s performance benefits and benchmarks results will be discussed.