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Data Is The New Fuel, AI is The Accelerator

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Data is the new fuel and AI is the accelerator. We have been hearing these quotes so often,

Data is the new currency

Data is the new oil

Data is the new economy

The ability for AI to transform enterprises in every industry can be clearly seen in our day-to-day life. As per the recent survey statistics, nearly 50% of the Enterprise IT organization are piloting, shaping, and implementing Artificial Intelligence (AI) based solutions.

AI can be applied to every single industry vertical – Autonomous vehicles, Seismic analysis for Oil and Gas explorations, Genomics research, Personalized Medicine and Drug development in Healthcare and Life Sciences, Video Surveillance, Manufacturing and Banking applications.

Business goals and objectives:

Every modern-day business needs a robust, secure, efficient, and cost-effective data management solutions. Data management strategy is central to becoming more important than ever as IT organizations increasingly rely on intangible assets to create value out of their “Data”.

The goals and business objective of any Enterprise data management ecosystem is to help people, organizations, and connected things optimize the use of data. That too within the specified bounds of policies, compliance, and industry regulations. Businesses can make data-informed decisions and take actions that maximize the benefit to the organization.

The main benefits that Data and AI can bring to enterprises is the ability to create new products and services optimizing operations and transforming customer experience.

Data lifecycle management challenges:

Data management for AI and Analytics workloads suffer due to multiple reasons, –Legacy storage solutions, performance bottlenecks, vendor lock-in in previous NAS implementation, non-linear scalable systems, inefficient storage data services, lack of multi-protocol storage support, and proprietary architectures.

Storage matters – effective planning holds the key to a successful deployment and operational efficiency for any Data, AI, and Analytics workload.

Even the fastest CPU and GPU servers wait at the same speed for data access, adding to performance bottlenecks.

Storage Matters

The Data & AI storage opportunity:

IBM has launched Elastic Storage System 3200 (ESS 3200). ESS 3200 is the 3rd generation of modular storage system hardware designed to be simple, integrated & scale-out for file and object storage workloads.

ESS 3200 is a purpose-built factory-configured hardware appliance with an extremely high-performance tier of Spectrum Scale operating environment. ESS 3200 offers file & object storage capabilities for a broad variety of AI, Analytics, and Big Data applications.

IBM Elastic Storage Systems 3200

Reference architecture for Enterprise Data & AI pipeline:

Enterprise Data & AI workflows are classified into 4 major stages – Ingest, Organize, Analyze, and ML/DL.  Let us take a closer look at building a simplified view of the Enterprise Data & AI workflows and subsequent storage requirements for each stage.

IBM ESS 3200 offers storage solutions for every stage of the end-to-end enterprise data pipeline. The image shows architecture, workflows and storage characteristics required to serve each of these stages.

Enterprise Data & AI Pipeline

How IBM Storage solve challenges for Enterprise Data & AI pipeline?

The IBM ESS 3200 is the storage foundation that supports this entire workflow. ESS 3200 storage system for Data and AI solution provides a single name space, global collaboration, a very sophisticated and flexible range of data protection models, as well as full multi-protocol storage support.

For every stage of the Data & AI/ML pipeline, we have seen so far, requires a high performing, high throughput data storage solutions with the lowest latencies.

IBM Storage for AI workflows

Why IBM Elastic Storage System (ESS) for Data & AI workloads?

Do not let the storage systems be the weakest link in the data environment! The latest and greatest computing servers are only as fast as the data streams that the storage systems can provide.

This requirement is often-overlooked law of physics – especially in AI domains, where there has been tremendous focus on GPU acceleration. Accelerated servers are critical to any data-driven transformation, so is the storage.

Why IBM ESS for Data & AI pipeline?

So, what type of storage system should be used to support Data, AI, and Analytics deployments? IDC names IBM as the #1 market leader in Data & AI solutions segment. IBM ESS 3200 is taking that lead in smallest storage system, supporting every reason for running these workloads. 

Let us look at how and why IBM ESS 3200 should be the top reason for picking up an ideal storage solution for these data-processing workloads.

  • Economics:

IBM ESS 3200 can start as small as 46 TB and can scale in capacity virtually without limit. Start small and scale easily from experiment to production at enterprise scale.

  • Limitless performance, scale, and reliability:

ESS 3200 truly support start small & grow big philosophy. It is packaged in the smallest form-factor within a 2U rack units that delivers 80 GB/sec throughput (100% read, InfiniBand).

By adding more such units to scale the cluster in system capacity and performance linearly. Up to 260 TB of usable capacity and an additional 80 GB/sec of throughput for each unit added.

  • Simple, quick, and efficient:

ESS 3200 helps simplify the design, configuration, installation, and support of the Data and AI environment.

Deploy AI with pre-configured solutions that are built on a field-proven, validated reference architecture and sized for the most common use cases — with comprehensive support.

  • Proven, secure and industry compliant 

ESS 3200 provide requisite performance, scalability, authentication & security features. Prime security features include – Sec 17a-4, immutability, WORM, audit logging, NIST and FIPS encryption standards.

  • Global data access, collaboration & protection

ESS 3200 leverages the rich data services that help Spectrum Scale to stretch the clusters. The Active – Active replicas of data for real time global collaboration via S3, NFS and POSIX protocols. Snapshots are end-to-end, replication of file sets & filesystem, high performance backup, restore and disaster recovery & direct application to disk checksum.

Triple erasure coding, end-to-end data encryption, Spectrum Scale RAID and NIST/FIPS certification makes it the most secure storage system on the planet.

Conclusion

IBM ESS 3200 is a fully integrated, tested, and turnkey solution for typical Data, AI, and Analytics workflows. IBM Spectrum Scale provides unparalleled rich storage data services and building blocks for superb enterprise performance, reliability, availability, and serviceability.

IBM is helping organizations of every shape and size around the world for solving their critical puzzle with data.

References

To learn more about the IBM Data Storage solutions for AI infrastructure, refer following IBM documentation and product pages;

  1. IBM Elastic Storge System 3200 datasheet
  2. IBM AI and Big Data Storage solutions

SME - Tech Sales for IBM SDS, MDP & Hybrid Cloud

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