Introducing IBM Spectrum Scale

Posted on 11 November, 2020

With businesses creating, analysing and keeping more data than ever before, the cloud is becoming difficult to manage within organisations. It's important to deliver insights faster while managing rapid infrastructure growth. 

When delivering those insights, an organisation's underlying information architecture must support the hybrid cloud, big data and AI workloads, along with traditional applications, while ensuring security, reliability, data efficiency and high performance.

IBM Spectrum Scale™ meets these challenges as a scale-out high performance global parallel file system.

What's new for IBM Spectrum Scale?

Kubernetes and IBM Spectrum Scale

  • Container Native Storage access now containerises IBM Spectrum Scale access and clusters data from high performance Spectrum Scale nodes

Advanced File Management (AFM) for Object storage 

  • Native object storage is now part of the high performance global file system and provides NVMe access to object storage data

Cloudera and IBM Spectrum Scale

  • IBM Spectrum Scale Hadoop connector now supports Cloudera Analytics


One Click integration to IBM Cloud Pak for Data and IBM Watson

  • Real-time ingest to IBM Spectrum Discover creates more value for AI workflows

Benefits

Extreme Scalability - Leverage no-bottleneck architecture to scale performance for extreme throughput and low-latency across not expected from network-attached storage

Data Aware Intelligence - Allow Spectrum Scale to grow and share your storage infrastructure while automatically moving file and object data to the optimal storage tier as quickly as possible

Enable Global Collaboration - Enable data-anywhere across the spans storage and locations to accelerate applications from edge to data centre to cloud and around the world

Data Integrity and Security - Take advantage of authentication, encryption, security, erasure coding and replication options to meet your business and regulatory requirements

Tags: IBM, Spectrum Scale

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