Thursday, July 25, 2024
PR Newswire Area

WEKA Rolls Out New Features and Enhancements in 4.2 Software Release

New Version Offers Enhanced Operational Management, Data Reduction, and Cloud Performance for Next-Generation Workloads Like Generative AI

CAMPBELL, Calif., May 18, 2023 /PRNewswire/ — WekaIO (WEKA), the data platform provider for performance-intensive workloads, unveiled version 4.2 of the WEKA® Data Platform today. The new release brings a variety of enhanced features and new capabilities to the company designed to increase the affordability and performance of next-generation technologies for WEKA’s customers. These include advanced data reduction and a new container storage interface (CSI) plug-in for stateful containerized workloads that can help customers dramatically lower their storage and operational costs. WEKA 4.2 also offers significant performance improvements in the cloud, providing the limitless scale and application data protection needed to support thousands of containers for cloud-native artificial intelligence (AI) and machine learning (ML).

The release builds on the fourth generation of WEKA’s software-defined, hybrid cloud data platform. Launched in June 2022, WEKA 4 seamlessly runs in on-premises environments on commodity servers, natively in one or more major public clouds – including AWS, Azure, Google Cloud, and Oracle Cloud – or in hybrid configurations. It transforms stagnant data silos into dynamic data pipelines that can more quickly, efficiently, and sustainably fuel next-generation technologies and performance-intensive workloads like generative AI, natural language processing engines, AI/ML model training, high-performance data analytics, genomic sequencing, and more.

With its 4.2 software release, WEKA continues to deliver on its mission to provide uncompromising speed, simplicity, scale, and sustainability benefits for organizations grappling with rapid structured and unstructured data growth, large-scale data analysis, managing performance-intensive workloads, and controlling data management costs. The release offers numerous features and benefits, including:

  • Enhanced Data Reduction: Advanced block-variable differential compression combined with cluster-wide data deduplication delivers data reduction at scale for an estimated cost savings of up to 6x for AI/ML training models, 3–8x for exploratory data analysis, and up to 2x for bioinformatic or large-scale media and entertainment workloads like visual effects (VFX).
  • Improved Azure Performance and Scale: The fastest file storage in Microsoft Azure offers a 6x performance improvement over market alternatives with better economics. WEKA 4.2 also fully supports Azure VM Scale Sets, so customers can auto-scale their storage up and down to control costs as workloads peak and recede.
  • Advanced Kubernetes Support: A new CSI-plugin adds persistent volume claim (PVC) snapshots and PVC clone features to provide better data management at scale for large-scale container deployments, particularly for next-generation transactional workloads such as NoSQL distributed databases, events, message processing applications, and large language model processing for generative AI engines.
  • Increased DataOps Efficiency with Efficient Client Management: The new capability makes data from multiple WEKA clusters accessible to a single client, alleviating the need for complex client management or data copies in data pipeline workflows and drastically improving the efficiency of data operations.
  • Superior Observability: The WEKA Home cloud monitoring platform now provides better observability for large-scale deployments, including improved filtering, anonymized upload of analytics and usage data, and software upgrade history.
  • Accelerated On-Ramp with New WEKA Software Appliance: A new pre-packaged, software-only appliance that drastically reduces time to on-ramp by automating the installation of the WEKA platform on bare metal servers and streamlining technical support so customers can get started within as little as 30 minutes. 

“The recent explosion of data-intensive workloads like generative AI and containerized cloud-native stateful applications is driving a monumental upsurge in data infrastructure complexity and costs,” said Nilesh Patel, chief product officer at WEKA. “The latest enhancements in WEKA 4.2 are designed to give our customers an easy button for managing AI and other next-generation workloads. For any organization managing commerce-attached applications, performance-intensive workloads, or that require a modern containerized infrastructure, WEKA can provide a highly efficient, affordable, and easy-to-deploy solution that supports faster time to market, insights, and improved production capabilities.”

The new features and capabilities in the WEKA 4.2 platform release will be generally available later this month. For more details, visit https://www.weka.io/data-platform/whats-new/ and https://www.weka.io/blog/distributed-file-systems/whats-new-in-weka-4-2/.

About WEKA
WEKA is leading a paradigm shift in how data is stored, managed, and processed. We help organizations transform their traditional, stagnant data silos into dynamic data pipelines that fuel next-generation workloads like AI, ML, and HPC seamlessly and sustainably. The WEKA® Data Platform is a software-defined solution purpose-built for hybrid cloud in the AI era. Its advanced cloud-native architecture is optimized to solve complex data challenges, delivering 10-100x performance improvements for next-generation workloads running on-premises, in the cloud, at the edge, or in hybrid and multicloud environments. WEKA is fueling research and discovery breakthroughs and accelerating business outcomes for leading global enterprises – including eight of the Fortune 50. The company operates in over 20 countries worldwide and is backed by dozens of world-class investors. For more information, visit www.weka.io, or connect with us on Twitter, LinkedIn, and Facebook.

WEKA and the WEKA logo are registered trademarks of WekaIO, Inc. Other trade names used herein may be trademarks of their respective owners.