2022 Industry Predictions
As we move into 2022, it’s time to think about what we’ve learned as well as the trends we’re seeing. We expect major developments in cloud, AI, deep learning and data analytics in 2022. We will see even more advances in AI, machine learning and analytic workloads with new services to support organizations. Here are 5 major data predictions for 2022.
Alluxio Day VIII: Featuring Apache Iceberg and Presto
Our eighth Alluxio Day event featured fellow Alluxio Open Source community contributors from Apache Iceberg, Presto, WeRide and Alluxio core team. Sessions covered the latest ML & AI use cases, Presto, Iceberg and Alluxio integration experience, and explained how to accelerate Spark analytics workloads with Alluxio.
Accelerating Machine Learning / Deep Learning in the Cloud: Architecture and Benchmark
New whitepaper describes how Alluxio can dramatically improve end-to-end distributed machine learning times in the cloud. The paper includes comparative analysis and benchmarking. See how Alluxio can benefit your training pipeline.
ALLUXIO 2021 RECAP
With the world shifting beyond Hadoop and exploring new ways to apply AI/ML, Alluxio has helped hundreds of organizations to modernize their data infrastructure, provide simpler access to new data stores, and speed their analytics and AI/ML applications. We have scaled mega-cloud object storage support using RocksDB for off-heap storage; and added native support for interfaces, such as the S3 API. In addition, Alluxio becomes cloud native with Kubernetes as the platform for hybrid and multi-cloud data analytics and AI.
The latest Alluxio 2.7 release has led to 8-12x improved I/O efficiency for machine learning at a lower cost, and further accelerated analytics workloads. Alluxio 2.7 is available for both the open source Community Edition and Alluxio Enterprise Edition. Download here.
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MOST VIEWED RESOURCES OF 2021
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Peijie Zhou is an infrastructure engineer at BossZP China. She’s been working on the kernel optimization of Spark, Flink, and Alluxio. She builds high-performance pipelines on top of those big data frameworks with cloud kubernetes. Her contribution to Alluxio mainly focuses on improving the stability and performance of Alluxio in machine learning and deep learning training. She also helps working on the best practice of Alluxio in Kubernetes. Check out her presentation at Alluxio Community Day (in Chinese) here!
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If you like our product, please give it a star on GitHub, and keep our open source community more popular!
Metadata Synchronization in Alluxio: Design, Implementation and Optimization (8 min read)
Speeding Up the AI Supercomputing Platform – Practice at Unisound (12 min read)
With the recent complete Series C investment, Alluxio will continue fueling its rapid growth by investing in expanded product capabilities as well as scaling go-to-market and engineering operations across the globe. Check out over 20 job opportunities here.
Solutions Engineer | CA, United States
Solutions Engineer | United Kingdom