ST Sep-Oct 2025

STORAGE

MAGAZINE

The UK’s number one in IT Storage

September/October 2025

Vol 25, Issue 5

CASE STUDY:

Silverstone Racetrack revs up

THE RANSOMWARE

PAYMENTS BAN:

Will it work?

WHY AI FACES NEW

GROWING PAINS:

Or the AI pipeline fails

ROLE OF DATA IN

ENTERPRISE AI:

Storage ecosystem needs to

be a solution

COMMENT - RESEARCH - INTERVIEWS - CASE STUDIES - OPINIONS - PRODUCT REVIEWS

Breakthrough

Areal Density

At Your Doorstep

HAMR-POWERED INNOVATION

Reduce TCO and future-proof storage infrastructure.

SUPERIOR POWER EFFICIENCY

3× the power efficiency per TB compared to typical drives.

BREAKTHROUGH AREAL DENSITY

First drive with 3 TB per platter, perfect for AI and big data.

BUILT FOR SUSTAINABILITY

Made with more renewable energy and recycled materials than

any previous Seagate product.

Data

Done Right

Discover data storage

solutions built on trust,

affordability and ease.

+ Storage you can count on

+ Best-in-class value and service

+ Seamless end-to-end integration

+ Operational simplicity

Read more:

CONTENTS

CONTENTS

COMMENT….....................................................................4

OPINION: THE RANSOMWARE PAYMENT BAN:.....….6

Will it work? Commvault offers researched insight

06

MANAGEMENT: SIX ESSENTIAL CYBER

STACK INGREDIENTS:.........................................................8

Infinidat runs through core components of cyber resilience

OPINION: RANSOMWARE HAS EVOLVED, SO MUST

OUR DEFENCES:......................................................…….10

CTERA cautions on the next frontlines

10

CASE STUDY: REVVING UP RELIABILITY:.........……..12

Silverstone Racetrack overhauls server infrastructure with Synology

OPINION: LEAP TO QUANTUM COMPUTING:....……14

Innovec highlights why you don’t have to be a quantum physicist to understand quantum

computing

14

TECHNICAL: OPEN-E AND WESTERN DIGITAL

TEAM UP:…...............................................................……18

Brings NVMe-based data storage boost

OPINION: WHY AI FACES NEW GROWING PAINS:…....20

How PEAK:AIO is overcoming AI growing pains at the Zoological Society of London

22

MANAGEMENT STRATEGY: THE FUTURE IS STILL

SPINNING:...............................................................................22

Toshiba strategises on how hard drives still remain indispensable in data centres

ROUNDTABLE: EMERGING MEMORY STRATEGIES:....24

Expert perspectives gathered in one roundtable

TECHNICAL: STORAGE IS TRANSFORMING AI........32

Supermicro considers the role of data in enterprise AI

24

CASE STUDY: NATIONAL LIBRARY OF SCOTLAND...34

Trusts cultural treasures to Scality

www.storagemagazine.co.uk @STMagAndAwards Sept/Oct 2025

STORAGE

MAGAZINE

03

COMMENT

EDITOR: Sharon Munday

editor@storagemagazine.co.uk

SUB EDITOR: Mark Lyward

mark.lyward@btc.co.uk

REVIEWS: Dave Mitchell

PUBLISHER: John Jageurs

john.jageurs@btc.co.uk

LAYOUT/DESIGN: Ian Collis

ian.collis@btc.co.uk

SALES/COMMERCIAL ENQUIRIES:

Lucy Gambazza

lucy.gambazza@btc.co.uk

Stuart Leigh

stuart.leigh@btc.co.uk

MANAGING DIRECTOR: John Jageurs

john.jageurs@btc.co.uk

DISTRIBUTION/SUBSCRIPTIONS:

Christina Willis

christina.willis@btc.co.uk

PUBLISHED BY: Barrow & Thompkins

Connexions Ltd. (BTC)

Suite 2, 157 Station Road East

Oxsted. RH8 0QE

Tel: +44 (0)1689 616 000

Fax: +44 (0)1689 82 66 22

SUBSCRIPTIONS:

UK £35/year, £60/two years,

£80/three years;

Europe: £48/year, £85 two years,

£127/three years;

Rest of World: £62/year

£115/two years, £168/three years.

Single copies can be bought for £8.50

(includes postage & packaging).

Published 6 times a year.

No part of this magazine may be

reproduced without prior consent, in

writing, from the publisher.

©Copyright 2025

Barrow & Thompkins Connexions Ltd

Articles published reflect the opinions

of the authors and are not necessarily those

of the publisher or of BTC employees. While

every reasonable effort is made to ensure

that the contents of articles, editorial and

advertising are accurate no responsibility

can be accepted by the publisher or BTC for

errors, misrepresentations or any

resulting effects

While most of the country was watching the spectacle of President Trump's

second state visit, those of us in data storage should have had our eyes

elsewhere: the announcement of a UK/US Tech Prosperity Deal bringing £31

billion in fresh US investment into UK data and cloud infrastructure.

For our industry, the detail is what really matters. Microsoft has pledged £22 billion

over the next four years for AI and cloud projects, including a new supercomputer hub

in Essex with Nscale. Nvidia will deploy 120,000 GPUs across UK data centres - one

of its largest European rollouts. OpenAI's "Stargate UK" initiative promises expanded

capacity and local GPU deployments, while Google is set to invest around £5 billion in

a new Waltham Cross data centre and scaling DeepMind's AI research. Importantly,

this isn't all confined to London and the South East: an AI Growth Zone in

Northumberland is on the cards, bringing 5,000 jobs and new energy-backed

infrastructure to Blyth.

This surge in US investment is more than political theatre. It could mark a pivotal

moment in the UK's bid to anchor sovereign compute and storage on home soil -

though "could" is the key word, as it comes with all the familiar challenges of power,

cooling, and resilience that we often grapple with in Storage Magazine.

Against that backdrop, this issue continues our focus on forward-thinking articles and

commentary. The standout research comes from Commvault, with a timely UK survey

that throws the spotlight on government plans to enforce ransomware non-payment

across both public and private sectors under the forthcoming Cyber Security and

Resilience Bill. Supermicro explores the role of customised large language models in

enterprise AI, showing how techniques like RAG can enable rapid, reliable data

retrieval. And still on the AI theme, PEAK:AIO explains how to deliver petabytes of raw

information to GPU cores without bottlenecks - and why trust in the resulting models is

vital when lives may depend on them.

This Autumn issue is stacked with insights - turn the page and see for yourself.

Sharon Munday

Editor, Storage Magazine

EDITORS COMMENT:

SHARON MUNDAY, EDITOR,

STORAGE MAGAZINE

04 STORAGE

MAGAZINE

Sept/Oct 2025

@STMagAndAwards

www.storagemagazine.co.uk

CAN

YOUR

NAS

support on-prem,

public, private, hybrid,

or even air-gapped

environments to fit

your business needs?

Modernize Your NAS

OPINION: COMMVAULT

THE RANSOMWARE PAYMENT BAN: WILL IT WORK?

DARREN THOMSON, FIELD CTO EMEAI AT COMMVAULT CONSIDERS THE IMPACT ON UK PUBLIC AND

PRIVATE SECTORS FOR MANDATORY REPORTING OF RANSOMWARE AND NON-PAYMENT OF

RANSOMWARE DEMANDS.

Following a public consultation, the UK

Government has confirmed it intends to

press ahead with introducing a ban on

ransomware payments for the public sector

and critical national infrastructure providers. It

is also considering a new 'payment prevention

regime' that will require organisations, not

covered by the ban, to notify the government

of their intention to pay the ransom demands

of cyber criminals.

Designed to "target the business model that

fuels cyber criminals' activities", the proposed

policy aims to dismantle the ransomware

model by reducing the financial incentive for

ransomware attacks; a move the Government

hopes will improve operational resilience

across the public sector by making the vital

services the public rely on a "less attractive

target for ransomware groups". If enacted, the

new legislation would make the UK the first

country to legally ban ransomware payments

by the public sector and regulated

organisations that oversee critical national

infrastructure (CNI).

While primarily targeted at public bodies and

CNI operators, the ban has significant

implications for the private sector too. The

introduction of a new mandatory reporting

regime for ransomware incidents will make

private sector organisations subject to an

oversight mechanism that, while it doesn't ban

payments, is likely to discourage payment by

increasing accountability. Meanwhile, suppliers

to the public sector must wait to see if they will be

included in the scope of the ransomware ban.

TAKING A STAND

The UK Government's proposal is being widely

viewed as a world-leading approach to

deterring ransomware attacks by cutting off the

flow of payments to criminals.

In an ideal world, prohibiting ransomware

payments should help curb the effort of the

ransomware gangs targeting schools, local

authorities, and hospitals. Since ransomware

only works if victims pay, making ransomware

payments 'off limits' would reduce the

attraction of public sector targets for financially

motivated attackers.

It's a viewpoint that is widely supported by the

UK private sector looking to break the

ransomware cycle and deprive the

ransomware ecosystem of 'fuel'. According to

our recent research, 94% of UK business

leaders supported the introduction of a

payments ban for public entities. An impressive

99% were also in favour of extending the ban

to private organisations too.

Of those supporting the Government's

proposed payments ban for the public sector, a

third (33%) believe this would decrease the

prevalence of attacks by reducing the incentive

for attackers. A further third (34%) believed it

would lead to increased government support

and intervention to safeguard cyber resilience.

However, the research also reveals that the

private sector's likely compliance with a

ransomware ban is uncertain. Three-quarters

(75%) of business leaders admitted that if the

ban was extended to the private sector, they

would still pay a ransom if it were the only way

to save their organisation, regardless of

whether civil or criminal penalties applied.

Only 10% were able to say with conviction that

they would comply in the event of an attack.

This ambivalence highlights the conundrum

confronting private sector firms. While no

organisation wants to pay a ransom, the

research highlights many feel they will have

little choice but to pay and risk criminal

charges if the company's survival is at stake.

THE LAW OF UNINTENDED

CONSEQUENCES

The UK Government's proposed payment

prohibition measures for the public sector

could have unintended consequences. Since

public sector entities will no longer offer rich

pickings, the risk is that attackers will double

down on targeting the private sector. The fear

here is that they will focus their efforts on

pursuing organisations deemed the least

equipped to protect themselves, such as SMBs

and non-profits.

The recent and devastating experience of

KNP, a 158-year-old UK logistics company that

06 STORAGE Sept/Oct 2025

@STMagAndAwards


MAGAZINE

OPINION: COMMVAULT

"Three-quarters (75%) of business leaders admitted that if the ban was extended to the

private sector, they would still pay a ransom if it were the only way to save their organisation,

regardless of whether civil or criminal penalties applied."

Maintaining data integrity and availability

will also be crucial for restoring operations

and reducing the risk of reinfection. In this

respect, immutable, air-gapped backups and

regular recovery point testing and validation is

vital for ensuring the availability of clean data

for restoration.

employed around 700 people, underlines the

devastating impact of an attack on an SMB.

Unable to pay a ransom estimated to be in the

millions, the company had no other option but

to close.

Faced with declaring bankruptcy, some

organisations may decide to make payments

in secret. Alongside forcing ransomware

payments 'underground', this could potentially

expose organisations to further extortion

should cybercriminals subsequently threaten to

publicise these payments.

Given the likelihood that ransomware attacks

are an inevitability and the decision to pay a

ransom is fraught with ethical, legal, and

practical challenges, the only way forward for

private sector organisations is to increase their

investment in prevention, detection, and rapid

recovery technologies that strengthen their

cyber resilience.

A BUSINESS-FIRST APPROACH: THE

MINIMUM VIABILITY MODEL

Given that recovery from a cyberattack takes

24 days on average and that 43% of UK

businesses report they have experienced a

cyber breach or attack in the past 12 months,

maintaining essential services during a

cyberattack has become an absolute must

have. That means having a clear and

actionable plan in place to restore critical

systems, data and processes.

Minimum viability, or a 'minimum viable

company', is a top-down business-led

approach that enables organisations to

prioritise the recovery of core operations until

full recovery can be achieved. By protecting

the key systems, assets, processes, and people

needed to maintain essential services during a

cyberattack, organisations can continue to

operate when disruption hits and protect their

long-term viability.

Developing a plan for minimum viability starts

well before an attack and involves the

identification of what truly matters for

continuous business. In other words, the

fundamental applications and services that

must stay secure and operational at all times.

Typically, this will include communication

platforms such as email and collaboration

tools, financial and customer-facing systems,

and core operational workflows.

Finally, since resilience depends on people as

much as technology, clearly defined incident

procedures and regular scenario-based drills

are essential for evaluating team response

times and continually improving processes.

The goal here is to test the organisation's

readiness and ability to recover from an attack

and identify areas that need strengthening.

PREPARING FOR THE FUTURE

Implemented effectively, the Government's

ransomware payment ban could indeed reduce

the financial incentive for attackers as intended,

but for those organisations without a solid cyber

recovery plan or the time and resources to

recover from an attack, banning payments

brings the potential for existential risk.

Irrespective of where organisations stand on

the value or practicalities of a payment ban,

the importance of improving protection and

recovery capabilities is irrefutable. Especially

when paying a ransom rarely guarantees

recovery and often increases the likelihood of

being targeted again.

By incorporating minimum viability principles

into their resilience planning and recovery

strategies, organisations can significantly

reduce the likelihood of catastrophic

outcomes when an attack occurs. They will

also be able to validate that their core services

can be recovered quickly and safely should

the worst happen.

More Info: www.commvault.com


@STMagAndAwards Sept/Oct 2025

STORAGE

MAGAZINE

07

MANAGEMENT: CYBER RESILIENCE

SIX ESSENTIAL 'CYBER

STACK' INGREDIENTS

ERIC HERZOG, CMO AT INFINIDAT RUNS THROUGH THE

CORE COMPONENTS OF NEXT-GENERATION CYBER

RESILIENCE: FROM ATTACK MAPPING TO RAPID RECOVERY

Every single second of the day there's

a cyberattack taking place multiple

times somewhere in the world. That's

according to estimates from a range of

professional cyber security experts and

tech vendors. A well-known brand or

public sector organisation is almost always

in the news and facing serious disruption

because of a cyber incident. So far this

year we've had retailers, hotels, hospitals,

airports, schools, and manufacturers such

as in the automotive sector - all forced to

shut down their operations to minimise the

effects of a cyberattack.

This heightened risk and frequency of

cyberattacks means that finding solutions

to deliver proactive, next-generation

data protection, by employing

sophisticated AI enhanced technology

and deep content analysis, is imperative.

This what we call your 'Cyber Stack'. It

comprises all the essential capabilities

needed by today's enterprises if they

want to ensure their storage systems are

truly cyber resilient. And cyber resilient

storage, that proactively protects data to

withstand an attack and that offers the

ability to rapidly detect a breach and

then restore operations to normal

functioning, is now critical.

This article discusses the six essential

ingredients of cyber resilient enterprise

storage to have in your Cyber Stack and

why. Let's consider each of these in turn to

appreciate what they mean for the

enterprise:


@STMagAndAwards


MAGAZINE

MANAGEMENT: CYBER RESILIENCE

"A well-defined Cyber Stack, proactive detection, and tested response plans are what

separate disruption from resilience."

1. Ability to map the attack's impact and

progress

Understanding how an attack unfolds is

fundamental to being able to control it.

Using tools like Security Operations Centre

(SOC) systems or dedicated storage

cybersecurity software (SIEM or SOAR),

enterprises can track suspicious activity as

it moves through the network, servers and,

crucially, storage. This visibility acts as an

early warning system provided storage

scanning is also included.

2. Identification of known ransomware

varieties and outcomes:

By leveraging AI-based detection

technologies such as regular updates and

global intelligence feeds, it's possible to

ensure rapid recognition of any

ransomware and malware that is already

known to the cyber security community. By

keeping cyber risk databases current,

detection levels continuously improve and

the storage system is able to adapt to

thwart new cyberattack types.

3. Mapping an attack timeline and data

changes with precision

Technology such as the SIEM and SOAR

installed in the data centre, when

combined with storage scanning tools,

enable cybersecurity teams to pinpoint

exactly if, when and how data was

modified. This precision supports both a

secure forensic investigation and a timely

response to damage limitation during

ongoing cyberattacks.

4. Maintaining a full audit trail for

compliance and examination purposes

Comprehensive cyber security solutions

must log every event across servers,

storage, and snapshots. By maintaining an

unbroken audit trail, it becomes possible to

drill down to the individual asset level and

observe what was affected during a cyber

incident. This level of granularity is crucial

for both regulatory compliance

requirements and when performing a root

cause analysis.

5. Dashboard reporting showing key event

information

Dashboards provide clear, actionable views

into key event details. They can verify the

time, type and scope of each attack, plus

provide more detailed information about

immutable snapshots taken that contain

uncompromised data. A best practice

approach is to adopt automated policies

and fully integrate enterprise storage with

other cybersecurity tools. This helps to

ensure quick, visible action is possible, with

policy adaptation as and when needed.

6. Sourcing the latest clean versions of

damaged data for rapid recovery

Rapid recovery after a cyberattack depends

on secure forensic fencing and the ability

to scan immutable data snapshots until a

clean (uninfected) backup copy can be

found. Scanning can either be automated

or completed manually and checked by

application teams. Whatever the approach

taken, it should always prioritise the most

recent data, unless a compromise is

detected, in which case earlier snapshot

versions must be reviewed.

NOTHING BEATS PROACTIVE, EARLY

DETECTION

These six ingredients are vitally important

to mitigate the effects of a cyber incident,

but nothing can replace the importance of

early detection of an impending attack.

This is always more important than

detection once an attack is underway. In

spite of this, many enterprise storage

companies persist in offering reactive

ransomware/cyberattack detection

capabilities based on "Anomaly Detection"

technology.

These approaches are far less effective

than proactive threat detection - because

once the attack has taken place, it is

most likely too late. The data

compromised has probably already been

written to storage and may even have

been captured as snapshots. And once

compromised data has been backed up,

it becomes a very lengthy process to

identify clean recovery points.

Best practice advice is always to invest in

proactive detection of your data to ensure

that in the event of an attack, you're well

equipped to recover quickly, with

comprehensive forensic reporting. You can

then perform a deep content analysis to

accurately determine "known good" copies

of data and restore them quickly. These

capabilities are one of the most important

elements of a "total storage cyber resilience

solution" that's designed to deliver a "cyberfocused

and recovery-first strategy" - nextgeneration

data protection.

Experience has shown that enterprises

with a well-defined Cyber Stack, proactive

detection, and well tested response plans

always recover quickly. In contrast, the

ones lacking these essential ingredients will

struggle to recover and inevitably,

some never do.

More Info: www.infinidat.com



STORAGE

MAGAZINE

09

OPINION: CTERA

RANSOMWARE HAS EVOLVED.

SO MUST OUR DEFENCES

ARON BRAND, CTERA'S CHIEF TECHNOLOGY OFFICER, TELLS US

WHY AI AND HUMAN DECEPTION ARE THE NEXT FRONTLINES IN

THE FIGHT AGAINST RANSOMWARE

Coveware's Q2 2025 ransomware

report landed like a hammer:

average payments have doubled

since last quarter, now sitting at $1.13

million. The ransomware economy has

shifted up many gears.

And ransomware isn't about encryption

anymore. It's about data theft and social

engineering.

For years, the ransomware playbook

was simple: encrypt files, demand

payment for the keys. That model is

fading. Coveware's data shows that in

74% of cases, attackers never bother

encrypting at all. Instead, they quietly

steal sensitive data and use the threat of

exposure as leverage.

Why? Because it works. Exfiltration

requires less effort than deploying fullscale

encryption campaigns, and

reputational pressure on victims to pay

is immense.

Technical defenses aren't what attackers

are working hardest to beat. Instead,

they're working harder to trick people.

Coveware points to groups like Scattered

Spider, Silent Ransom, and Shiny Hunters

using impersonation tactics against help

desks, employees, and service providers.

Phishing, credential theft, and fake

"security prompts" are replacing exploits

and malware as the initial breach vector.

In short: ransomware has gone

human-first.

Backups are still necessary. So are

firewalls, patching, and MFA. But in an

era where attackers impersonate trusted

colleagues over Teams or poison search

results to deliver malware, these measures

are not working. You can't firewall human

trust. You can't patch human behavior.

"Ransomware has gone human-first, so


@STMagAndAwards


MAGAZINE

OPINION: CTERA

"Ransomware has gone human-first, so our defence has to

live at the data layer." - Aron Brand, CTO of CTERA

our defence has to live at the data layer.

By combining behaviour-based AI with

built-in deception, we spot suspicious

access early and shut it down before it

becomes a breach."

That's why Gartner introduced the

category of Cyberstorage in 2022.

Cyberstorage is about extending storage

systems beyond resilience and backup into

active defense. Cyberstorage provides

active capabilities like AI based

ransomware behaviour based prevention,

anomaly detection, and data immutability,

right into where the data lives. The goal

isn't just to recover after the fact but to

detect, contain, and respond in real time.

FROM WALLS TO TRAPS

To keep pace, defenses need to evolve in

two ways:

AI-driven detection. When credentials

are stolen, only machine learning can

reliably flag the unusual data access,

strange download patterns, or

anomalous file changes that follow.

Humans can't watch that much

telemetry at once.

Deception and honeypots. Instead of

only hardening the castle walls,

organizations need traps inside the

walls. Fake data, decoy servers, and

honeypots waste attacker resources

while alerting organizations before real

damage occurs.

look like ransomware or insider abuse.

It's about identifying abnormal

behavior in real time, before an

incident becomes a crisis.

And with CTERA Honeypots,

we've built deception directly

into the platform. Attackers

who probe your

environment may think

they've found something

valuable, but they've

actually stumbled into a

trap that alerts you instantly.

It's defense by manipulation,

not just prevention.

CLOSING THOUGHTS

Ransomware has gone

human-first, and that

means we, as defenders,

need to think differently.

If the bad guys are

playing people, maybe

the right move is to

start playing them

back.

More Info:

www.ctera.com

Attackers are innovating. As defenders

we must innovate faster.

This is exactly the philosophy behind

CTERA's approach to organizational

resiliency. CTERA Ransom Protect, our AIbased

ransomware detection continuously

monitors file activity to spot anomalies that



STORAGE

MAGAZINE

11

CASE STUDY: SILVERSTONE STUDY:

REVVING UP RELIABILITY:

SILVERSTONE OVERHAULS SERVER INFRASTRUCTURE WITH SYNOLOGY

The Challenge: Outdated servers and

unreliable disaster recovery

Silverstone Racetrack had inherited a

server platform that had been outgrown by

the organisation. Their Disaster Recovery

solution was particularly difficult to manage

and needed human intervention to run

properly. Silverstone started looking for high

performance in a solution that was

economical, streamlined and efficient,

alongside also providing Disaster Recovery

that was reliable and easy to manage. A

Synology solution seemed to address these

requirements.

The request was for scalability that would

meet the requirements of the organisation

now and for several years to come.

Minimising downtime in the event of a

problem was also a key requirement.

Silverstone also needed a Disaster Recovery

solution that was dependable and effective.

The Solution: Overhauling server

infrastructure with Synology RackStation for

high-performance storage

Analysis of the existing infrastructure showed

the limitations of the network as well as

identifying disk performance as a key

performance bottleneck. Based on the results

of this analysis, a solution was proposed by

Serveline, a Synology premium partner, to

provide a virtualised server and storage

platform with high availability in place.

The new storage platform was built on

Synology RS2416RP+, in conjunction with

all-flash based SAN to power the

virtualisation environment.

This solution offered to Silverstone Circuits

provided many advantages. Synology's

RackStations are fully VMware certified and

come with regular software updates so ensure

users can leverage the latest technology

offered by VMware (if one physical server

needs repairing or upgrading, the integration

between the Synology and VMware solutions

allows for the live migration of a Virtual server

without any downtime). Virtualisation reduces

the number of physical servers required by the

organisation, reducing maintenance and

energy costs. Virtual servers are managed,

modified and multiplied much more easily

than physical servers, so the new

infrastructure can easily continue to support

the organisation as it grows and changes.

The Benefits: Real-time backups, effortless

failover, and simpler server management

The new Disaster Recovery solution is a

rapid and fully automated backup solution

protecting the organisation's data. Utilising

the multiple server room locations at the

800-acre Silverstone site, a remote,

automated backup target with real-time file

replication was configured. The data is now

stored in the main building, and replicated to

the secondary server location to provide rapid

recovery in the event of fire, flood or theft.

Silverstone Circuits are now enjoying the

benefits of a robust, high performing, highavailability

server platform with room for

expansion as the organisation grows, and an

improved, reliable Disaster Recovery solution

which is hassle-free.

About the Customer:

Silverstone, a motor racing circuit in England,

is built on the site of a World War II Royal Air

Force bomber station, RAF Silverstone, which

opened in 1943. The airfield's three runways

- in classic WWII triangle format - lie within

the outline of the present track. Silverstone is

the current home of the British Grand Prix,

which it first hosted in 1948. The 1950 British

Grand Prix at Silverstone was the first race in

the newly created World Championship of

Drivers. The race rotated between Silverstone,

Aintree and Brands Hatch from 1955 to

1986, but relocated permanently to

Silverstone in 1987. The circuit also hosts the

British round of the MotoGP series.

More Info: www.synology.com


@STMagAndAwards


MAGAZINE

Workload Protection Made Easy

Safeguard a wide variety of enterprise workloads via a single console

Learn more

Reserve your free seat

18M+

SaaS accounts

protected

2.1M+

Endpoints & VMs

protected

4.7 / 5 4.6 / 5

OPINION: INNOVEC

OPINION PIECE: QUANTUM LEAP

TO QUANTUM COMPUTING

IAIN WHAM, MANAGING DIRECTOR OF SCOTTISH IT SUPPORT

PROVIDER, INNOVEC, ASKS WHO IS PREPARED TO TAKE THE

QUANTUM LEAP?

The world of information technology is in

constant flux, presenting new and

ongoing challenges for fintech

businesses. In recent times we have seen the

rise of cloud computing, the growth of data

management and the arrival of artificial

intelligence (AI) into every workplace.

Just keeping pace with changes in IT is a

daily challenge. Now, another transformative

wave is on the horizon: quantum computing.

While it might sound like something out of

science fiction, the implications of quantum

computing for even the smallest fintech

business are profound and far-reaching.

Within the next couple of years, quantum

computing will be as relevant to your business

as AI has become, and understanding its

potential and preparing for its arrival is no

longer optional; it's a strategic imperative.

DEMYSTIFYING THE QUANTUM REALM

Quantum computers aren't just faster than

conventional computers, they are designed to

tackle specific, complex problems that are

currently impossible, even for the world's most

powerful supercomputers.

While most quantum computers currently

remain in research labs, outside the budget

of all but the biggest and richest

companies, another type of quantum

computer, called a 'quantum annealer', is

already commercially viable.

More akin to a traditional computer

processor, the quantum annealer is particularly

adept at solving optimisation problems, which

are a vast category of challenges faced by

businesses of all sizes, that involve finding the

best possible solution from an enormous

number of options.

THE QUANTUM ADVANTAGE

While the most sophisticated quantum

computers are still a decade or more away

from widespread use, the implications for

businesses, including small and local ones, are

already emerging.

Think about the challenges faced by many

small, local businesses. For instance, an

artisan bakery might struggle with optimising its

ingredient sourcing, to minimise waste and

cost while ensuring product freshness.

A courier business might use quantum

computing to organise route planning by

considering real-time traffic, weather,

vehicle capacity, delivery windows, and

even staff availability.

Quantum algorithms can identify the most

efficient routes, saving time, fuel, and

reducing wear and tear on vehicles. A

boutique clothing store could use quantum

insights to ensure they have the right stock at

the right time, maximising sales and

minimising dead inventory.

For businesses relying on customer loyalty,

understanding individual preferences is crucial.

This could enable a small independent

bookshop to offer highly personalised

recommendations, or a local brewery to craft

targeted marketing campaigns that resonate

with specific customer segments.

Even small businesses deal with financial

transactions and the associated risks.

Quantum computers can perform more

complex financial modelling, leading to

better investment strategies, more accurate

risk assessments, and improved fraud

detection. A small financial advisory firm

could leverage quantum insights to provide

clients with more robust portfolio

optimisation.

CHANGES TO CYBERSECURITY

While the opportunities of quantum

computing are immense, it also presents a

challenge, particularly in the realm of

cybersecurity. One of the most talked-about

implications of quantum computing is its

potential to break current encryption

standards.

Algorithms which can be run on sufficiently

powerful quantum computers, could render

much of today's online security obsolete. This

means that sensitive data, financial

transactions, and confidential

communications which are secure today,

could become vulnerable in the future.

This transition is referred to as the "postquantum

cryptography" (PQC) era and it is

crucial to understand that you don't need a

quantum computer to implement PQC.


@STMagAndAwards


MAGAZINE

OPINION: INNOVEC

PQC algorithms are designed to run on

conventional PCs and they offer protection

against quantum threats. Businesses of all sizes

can start to prepare for PQC now, with a

target deadline of 2030 for transitioning

critical systems. For a small business, this might

seem daunting, but it could be a vital step to

protect your digital assets.

WHY QUANTUM IS THE NEXT BIG

THING FOR FINTECH BUSINESSES

As cloud-based quantum computing-as-aservice

(QCaaS) become more accessible, the

barrier to entry will decrease. Companies like

IBM, Google, and Microsoft are already

offering access to quantum hardware and

development tools, democratising this

powerful technology.

Ignoring quantum computing now would be

akin to ignoring the internet in the late 1990s

or AI a few years ago.

Those who understand and begin to integrate

quantum thinking into their business strategy

will gain a significant competitive advantage

over their rivals.

PREPARING FOR THE QUANTUM

FUTURE

So, what concrete steps can your business take

today to prepare for the quantum revolution?

Conduct a feasibility analysis: Understand

what quantum computing is and what it can

(and cannot) do for your business. You don't

need to become a quantum physicist; focus on

understanding the types of problems quantum

computers are good at solving, particularly

optimisation and simulation. Consider the

computational requirements and data

complexity of the problems you face.

Start small and experiment: You don't need to

buy a quantum computer - many providers

offer QCaaS, allowing you to access quantum

computing power via the cloud. This is the

most practical way for small

businesses to experiment.

Internal training: Invest in "quantum literacy"

for your core team. This doesn't mean

everyone needs to be a programmer. It means

fostering an understanding of the concepts

and potential applications. Workshops, online

courses), and internal knowledge-sharing

sessions can be highly effective.

External partnerships: Explore collaborations

with universities, research institutions, or

quantum computing companies. Many

universities have departments focused on

quantum technologies and may be open to

partnerships that could benefit your business

to provide access to expertise and cuttingedge

research.

Have a transition plan: Start planning how

you will migrate to quantum-resistant

cryptography. This might involve software

upgrades, hardware changes, or working

with your IT provider. Aim to have a plan in

place by 2025-2026 to be ready for the

2030 deadline.

Form a project team or assign a champion:

Designate an individual to stay informed about

quantum developments. This "quantum

champion" can research new applications,

monitor trends, and identify potential

opportunities or threats.

Re-evaluate your business plan: As quantum

computing matures, it will unlock new

possibilities. Consider how these

advancements might impact your business

model. Could you offer new services based on

quantum-enhanced analytics?

SKILLS, TRAINING, AND EQUIPMENT

The primary investment for most small

businesses will be in human capital. This

means allocating budget for training existing

staff, or hiring individuals with an aptitude for

analytical thinking and technology.

Initially, investment in equipment will be

minimal and focused on ensuring your

existing IT infrastructure is robust enough to

access QCaaS platforms and implement

PQC solutions. This might involve

upgrading network capabilities or ensuring

your current systems can support new

cryptographic standards.

Consider investing in partnerships with

quantum computing service providers or

consultants. This can provide access to

specialised expertise without the need for

extensive in-house training initially.

THE QUANTUM FUTURE IS NOW

The growth of quantum computing is not a

distant theoretical concept; it's an evolving

reality that will impact businesses of all sizes.

By understanding its fundamental principles,

identifying potential use cases, and taking

proactive steps to prepare, fintech businesses

can not only weather this technological shift

but also harness its power to innovate,

optimise, and thrive in the coming years.

More Info: https://innovec.co.uk/


@STMagAndAwards


MAGAZINE

SCAN ME

THE DOUBLE-LAYER

IMMUTABILITY BACKUP

POWERED BY OPEN-E AND VEEAM ®

Is your data storage really immutable? Discover a new, effortless way to get

a truly immutable, high-performance backup data storage solution you can

count on at all times. Open-E JovianVHR is a Veeam-certified software solution

that empowers your Hardener Repository with an extra layer of security and

performance. Now, you have an extra shield that protects you 24/7.

Discover a brand new solution built to take

your data protection to the next level.

CLOSE THE RANSOMWARE GAP TO ENSURE

YOUR PEACE OF MIND.

CHEVRON-CHEVRON-

www.open-e.com

Learn more

TECHNICAL:

OPEN-E & WESTERN DIGITAL TEAM TO BRING

NVME-BASED DATA STORAGE BOOST

KRISTOF FRANEK, OPEN-E CEO, DELIBERATES ON THE NEED FOR ULTRA-LOW LATENCY, HIGH

THROUGHPUT, AND UNWAVERING RELIABILITY FOR INTENSIVE WORKLOADS

How do you ensure that a data storage

system will keep up with the most

challenging demands? For IT system

administrators pushing the limits of AI, data

analytics, and cloud infrastructure, a fast and

safe storage system remains the number one

essential. At the end of the day, organisations'

success is built on a proper data storage

foundation. So what can be used to enhance

enterprise IT infrastructures systems and

enable them with a proper boost?

THE GROWING NEED FOR NVME

OVER FABRICS

A key technology at the forefront of this

demand is NVMe over Fabrics (NVMe-oF).

Why is it so essential for modern data

centres? NVMe-oF allows high-speed NVMe

data storage to be accessed over a network,

effectively eliminating the distance limitations

of local storage. This is a revolutionary shift,

enabling more flexible and scalable

architecture. However, as we also know,

speed without reliability is a risk. That's where

the Multipath I/O feature becomes crucial. It

provides multiple connection paths to the

data storage, ensuring that if one path fails,

data can still be accessed through another.

This guarantee of high availability is a nonnegotiable

feature for any enterprise today.

OPEN-E DATA STORAGE SOFTWARE

RESPONDS WITH A CERTIFIED

SOLUTION

Open-E listens to its customers' needs and

directly addresses them. That's why the

company implemented the NVMe over

Fabrics (NVMe-oF) Initiator Target with

Multipath I/O in its latest update, Open-E

JovianDSS Up32. But Open-E didn't stop

there. To ensure this feature delivers a truly

reliable and high-performance solution, the

company teamed up with Western Digital.

Open-E's goal was to create a solution that

works flawlessly, saving its customers time,

resources, and the hassle of compatibility

issues.

As Open-E CEO Kristof Franek said, "Our

customers demand ultra-low latency, high

throughput, and unwavering reliability for

intensive workloads. By listening to these

needs, we partnered with Western Digital to

provide a certified, pre-validated solution with

NVMe-oF and Multipath I/O, ensuring our

customers get a high-performance and

dependable JBOF, certified to work

seamlessly with Open-E JovianDSS."

THE POWER OF PARTNERSHIP WITH

WESTERN DIGITAL

Open-E's collaboration with Western Digital is

a prime example of its commitment to

addressing critical customer needs through

strategic partnerships, resulting in the Western

Digital OpenFlex Data24 4200 NVMe-oF

Platform certification with Open-E JovianDSS

Up32 software. The process wasn't simple, as it

involved a rigorous certification regime with

extensive functional and stability tests. The

Open-E team simulated real-world scenarios

like disk failures, hot-plug/hot-swap events,

and power outages to prove the system's ability

to protect and recover data.

The greatest advantage of this partnership for

both customers and channel partners is access

to a pre-validated solution that directly

addresses real-world business needs. Open-E's

collaboration with Western Digital allowed for

the NVMe-oF protocol to be developed and

rigorously tested within the Open-E JovianDSSbased

environment. This collaborative

approach delivers a new level of confidence to

IT professionals. You can learn more about this

specific solution by downloading the Open-E

Certification Report: https://www.opene.com/r/8kng/

More Info: www.open-e.com


@STMagAndAwards


MAGAZINE

Learn More About StorPool

Disaster Recovery Engine

StorPool Disaster

Recovery Engine:

First-Ever, Built-In DR

Solution for KVM Clouds

StorPool Storage Becomes the First

Software-Defined Primary Storage Vendor to

Offer a Disaster Recovery Engine for KVM-based Clouds.

StorPool Disaster

Recovery Engine

Get the Full Details

Disaster Recovery Engine In Action

• Simple to create and enforce data replication policies

• Automatically creates VM recovery points

• Automates failover and failback between remote sites

• Four protection models available

• No additional licenses necessary

StorPool Storage - Trusted by Service Providers

Ultra-Fast

Storage

Instantly accelerate your

applications with extreme

scalability and latency

consistently under 100µs,

even with heavy workloads.

Architected

for Cloud

Designed for KVM-based

clouds, providing affordable,

always-on, flexible, integrated

storage that delivers measured

uptime above 5 nines.

Fully-Managed

Service

StorPool experts design, deploy,

monitor, and maintain your

storage, freeing your staff from

daily repetitive tasks allowing

more time for strategic projects.

www.storpool.com

Get Started with StorPool

info@storpool.com

OPINION: PEAK:AIO

WHY AI FACES NEW GROWING PAINS

MARK KLARZYNSKI, FOUNDER AND CHIEF STRATEGY OFFICER, EXPLAINS HOW PEAK:AIO IS HELPING

CLIENTS LIKE THE ZOOLOGICAL SOCIETY OF LONDON OVERCOME AI'S GROWING PAINS

For decades, enterprise IT was

measured by outputs: database

performance, system uptime and

operational resilience. The mission was to

keep businesses running smoothly. Artificial

intelligence has rewritten those rules. In AI,

the focus is no longer on the output of

compute but on the input. Success depends

on feeding GPUs with vast, continuous

streams of data, preserving the integrity of

those inputs, and guaranteeing that the

models built upon them can be trusted.

This fundamental shift was the insight

behind PEAK:AIO's creation. From the

company’s very beginning, PEAK:AIO

recognised that AI was not simply

another workload to be layered onto

traditional IT systems. It represented a new

discipline with different requirements. While

IT teams still concentrate on resilience and

continuity, AI pioneers such as geneticists

identifying new compounds, doctors

detecting early signs of disease,

climatologists simulating extreme weather

and conservationists tracking endangered

species are dealing with data on an

unprecedented scale.

Their challenge is not how to keep a

server alive. It is how to deliver terabytes

and even petabytes of raw information to

GPU cores without bottlenecks, and how to

ensure that the models trained on this flood

of input can be trusted when lives or

ecosystems depend on them.

The Zoological Society of London (ZSL)

illustrates this point clearly. The organisation

has long been at the forefront of using

technology for conservation, from its Instant

Wild programme that enlists citizen

scientists to classify images, to acoustic

sensors that monitor rainforest biodiversity

and affordable satellite tagging of turtles.

These projects share a common thread:

data. Camera traps alone generate millions

of photos, the majority of them empty

frames. Acoustic monitors and video

streams add terabytes more. Before a single

model can be trained, this mass of

information has to be ingested, filtered and

organised. For ZSL, the need was not more

traditional IT infrastructure but a way to

feed GPUs with clean, usable data at the

pace that conservation now demands.


@STMagAndAwards


MAGAZINE

OPINION: PEAK:AIO

"Traditional IT was built around keeping outputs reliable. AI is built around

keeping inputs trustworthy. If you cannot feed GPUs with fast, secure data, or if

you cannot prove that a model is the one you validated, then the whole AI

pipeline fails." - Mark Klarzynski, PEAK:AIO

This is where AI's growing pains show most

clearly. In the IT world, performance is

supported by clusters of systems, teams of

administrators and carefully layered

redundancy. In AI, projects often run outside

the data centre, in the field, where

researchers do not have the staff or the

infrastructure to manage complex storage

estates. They need systems that are selfmanaging,

compact, energy efficient and

able to deliver extreme throughput. They also

face risks that IT has never had to consider.

One example is model poisoning, where

corrupted or misleading data enters a

training set and alters the models behaviour.

In conservation that could mean a

recognition system misidentifying species,

undermining an entire programme. Once a

model has been created and validated it must

also remain intact as it is shared around the

world. Traceability, the ability to link a model

back to its dataset and guarantee that it has

not been changed, is no longer optional. It is

as critical as the model itself.

PEAK:AIO's answer was to design storage

around these new realities. For ZSL this

meant systems that could hold more than a

petabyte of data within a small, energy

efficient footprint. The performance was

enough to keep GPUs fully occupied

without specialist intervention. Most

importantly, protection was built in.

PEAK:AIO created a fully automated archive

that is immutable and invisible to users,

controlled entirely by the primary AI data

server. No external servers are involved, no

manual steps are required, and yet within

seconds the archive can be reactivated as a

live NVMe pool. For scientists this means

their irreplaceable images and recordings

are secure without any added complexity.

Security becomes inherent to the system

rather than another task to manage.

The change in results was dramatic. Where

ZSL teams had once been able to process

only a few images per minute, they were

now handling thousands. In London's

Hedgehog Watch project, more than 15

million images were processed at speed,

turning what would once have been weeks

of manual effort into rapid, data-driven

insight that could influence conservation

action in real time. With researchers

uploading imagery and video around the

clock from field sites worldwide, ZSL gained

the assurance that their data would not only

reach GPUs at performance but would

remain protected against ransomware,

corruption or tampering.

The implications extend far beyond wildlife.

By linking trained models directly to their

datasets, with unique identifiers and

cryptographic checks, PEAK:AIO ensures

that models are verifiable. In medicine, this

is essential. A diagnostic model for cancer

cannot be allowed to drift from its training

data or be subtly altered. The cost of a

misdiagnosis is measured in lives. In climate

modelling or urban planning, the reliability

of an AI model can determine multi-billionpound

decisions. Guaranteeing that a

model is unchanged from the one that was

validated is as important as the accuracy of

the initial training.

Mark Klarzynski, Founder and Chief

Strategy Officer of PEAK:AIO, explains it

simply: "Traditional IT was built around

keeping outputs reliable. AI is built around

keeping inputs trustworthy. If you cannot

feed GPUs with fast, secure data, or if you

cannot prove that a model is the one you

validated, then the whole AI pipeline fails.

We designed PEAK:AIO to remove that risk,

to make sure data fuels discovery rather

than undermines it."

This is the real contrast between IT and AI.

IT continues to frame its priorities around

uptime and continuity. Those remain

important, but AI moves at a pace and on a

scale where data is not simply a by-product

of compute but its very fuel. Protecting the

flow of that data, feeding GPUs without

interruption, securing the models that result,

and maintaining their provenance are now

central tasks. In conservation, healthcare and

climate science, the accuracy of a model can

influence the wellbeing of individuals, the

survival of species and the strategies nations

adopt to face environmental change.

The story of ZSL and PEAK:AIO shows what

is possible when storage is reimagined for this

new reality. It is no longer about keeping

systems online. It is about safeguarding inputs,

accelerating discovery and protecting the

decisions that follow. By staying close to the

market and working directly with innovators,

PEAK:AIO is constantly developing solutions

that goes far beyond storing information and

ultra-performance. It ensures trust. It delivers

speed without complexity. And it helps solve

AI's growing pains at the very point where they

matter most.

More Info: www.peakaio.com



STORAGE

MAGAZINE

21

MANAGEMENT:

MANAGEMENT: HDDs AND THE DATE CENTER

THE FUTURE IS STILL SPINNING:

HOW HARD DRIVES REMAIN

INDISPENSABLE IN DATA CENTRES

RAINER W. KAESE, AT TOSHIBA ELECTRONICS EUROPE GMBH

LOOKS AT WHY HDDS REMAIN THE WORKHORSES OF MODERN

DATA CENTRES

In recent years, there have been

predictions of the hard drive's demise.

Yet, this storage medium remains

indispensable in the data centres of

enterprises and cloud providers. And, for the

foreseeable future, this is unlikely to change.

While hard drives may have

disappeared from most consumer

devices -and with that, from the view of

end users - they remain highly prevalent

in data centres. More than that, they

bear the brunt of data storage demands,

as no other storage medium can provide

the direct access and necessary capacity

for AI, video streaming, and other dataintensive

applications as economically

as hard drives. After all, SSDs are still

about five to eight times more expensive

per unit of capacity. Even if their price

were to match HDDs, it would take many

decades and insurmountable

investments to scale production capacity

to a level where SSDs could possibly

replace hard drives. This is due to the

complex and costly production of flash

memory in cleanrooms.

Therefore, not only does the majority

of installed storage capacity in data

centres consist of hard drives, but newly

added capacity is also predominantly

based on this classic storage medium. In

the year 2024 alone, 56 million

enterprise HDDs were shipped globally,

with a total capacity of 959 Exabytes -

that's 959 million Terabytes and more


@STMagAndAwards


MAGAZINE

MANAGEMENT:

MANAGEMENT: HDDs AND THE DATE CENTER

than four times the capacity of enterprise

SSDs shipped in the same period (59

million units with a total of 226

Exabytes).

The reason the hard drive is still so in

demand almost 70 years after its debut is

due primarily to its consistent capacity

growth - by 2 terabytes per year - while

maintaining stable costs. Initially,

innovations like helium-filled drives and

thinner disks enabled higher capacities.

Today, new recording technologies such

as Microwave-Assisted Magnetic

Recording (MAMR) and Heat-Assisted

Magnetic Recording (HAMR) are driving

this progress. These technologies utilise

microwaves and laser diodes respectively,

which means less magnetic energy is

required and the write head can be

smaller. Smaller write heads mean denser

data storage and, consequently, higher

capacities. Experts predict that drives with

up to 50 terabytes per unit will be

possible in the coming years.

Additionally, despite their moving parts,

hard drives are remarkably durable and

efficient. The failure rate of enterprise

HDDs is typically around 0.35%, which

translates to just seven failed drives per

year in a data centre with 2,000 hard

drives in operation. Large data centre

operators and cloud providers often

achieve even better reliability rates.

Power consumption for hard drives is

also relatively consistent, regardless of

capacity or workload, as most energy is

used to spin the spindle - typically

around 7 to 8 W. For high-capacity

drives, this makes HDDs very energyefficient,

consuming only 0.3 to 0.5 W

per terabyte, which is comparable to

SSDs of the same capacity.

The comparatively low performance is

often cited against hard drives, but this

case

only holds

true when

considering a

single drive. In

modern storage

architectures, dozens of hard

drives work together in arrays,

enabling parallel read and write

operations. In this way, storage systems

can easily achieve throughput rates of 15

GB/s and over 15,000 IOPS.

Ultimately, hard drives offer everything

data centre operators and cloud

providers value: high capacities at low

acquisition and operating costs, high

reliability, and sufficient performance for

most applications. Where performance

falls short, a few SSDs can easily be

added into the mix, but the majority of

data still resides on disks.

Hard drives may not be the star of the

data centre - they've been around too

long for that. Instead, they are the quiet,

indispensable workhorses that reliably

operate in the background. Without

them, it's fair to say, our digital world

would no longer function.

More Info: www.toshiba-storage.com

"No other medium can

match the capacity and

economics of hard

drives for today's datahungry

applications."



STORAGE

MAGAZINE

23

ROUNDTABLE:

ROUNDTABLE : EMERGING MEMORY TECHNOLOGIES

EXPERT PERSPECTIVES:

MEETING FUTURE

WORKLOAD DEMANDS

AN INDUSTRY ROUNDTABLE ON THE RISE OF EMERGING MEMORY

TECHNOLOGIES: FEATURING CONTRIBUTIONS FROM INDUSTRY

EXPERTS INCLUDING BIOMEMORY, BLOOR RESEARCH, CERABYTE,

SCALEFLUX, SNIA AND TARMIN

In this roundtable, vendors, analysts, and

researchers share their perspectives on

the future of memory - and the

challenges of performance, capacity,

bandwidth, energy efficiency, and latency.

To set the stage, we start with an overview of

memory developments in recent years.

It often feels as though memory is an

outlier in the technology world. While we've

seen significant changes in compute power

(both with CPU and GPU) and storage,

memory development has been iterative

rather than revolutionary.

While that approach has worked in the

past, current memory technology is

starting to cause challenges, due to an

issue known as the "memory wall

problem". This occurs when a processor's

speed outpaces memory's bandwidth and,


@STMagAndAwards


MAGAZINE

ROUNDTABLE:


"Emerging memory technologies are being driven by the explosive growth in AI and

machine learning, big data analytics, scientific computing, and hyperscale cloud

data centres," - JB Baker, ScaleFlux

as a result, the processor has to wait for

data to be transferred from memory,

introducing a bottleneck.

The performance restrictions caused by the

memory wall problem are only getting

worse, as CPU and GPU advancement

continues to outpace improvements in

memory architecture. And it's being

exacerbated by the growth of demanding,

memory-intensive workloads such as highperformance

computing (HPC) and AI, which

didn't exist at the same scales until relatively

recently but are now seeing rapid adoption.

This issue is creating the need for new

memory technologies, designed for

modern workloads.

"Emerging memory technologies are being

driven by the explosive growth in AI and

machine learning, big data analytics,

scientific computing, and hyperscale cloud

data centres," said JB Baker, VP marketing

and product management, ScaleFlux.

"Traditional memory technologies like

DRAM and NAND flash are reaching

scaling, speed, and density limits that

restrict the performance required for nextgeneration

workloads."

With AI demands highlighting the flaws in

existing systems, Baker believes that new

memory technologies are required.

"The needs for higher bandwidth, lower

latency, greater capacity, and energy

efficiency in AI and HPC applications are

exposing the inadequacy of traditional

solutions. We are indeed approaching the

physical and economic end of the road for

conventional memory scaling, making new

architectures and technologies essential,"

he noted.

While traditional memory technology still

has a role to play, other factors are pushing

the demand for emerging technologies.

David Norfolk, Practice leader:

development and governance, Bloor

Research, explained, "AI hype is driving

things - that and the need for vendors to sell

something new with higher margins. I very

much doubt that we are at the end of the

road yet, but people always want more

speed, scaling, and density. "What may be a

driver, is more energy efficiency, less heat

and more reliability - less waste."

DEFINING THE PROBLEM:

High-performance workloads have

numerous requirements, so no single

emerging memory technology works across

the board. For example, AI workloads

require a significant volume of data, both for

fresh processing and longer-term storage.

That applies to both typical Generative AI

(Gen AI) services, such as ChatGPT, and to a

growing number of physical machines that

collect data using sensors for decisionmaking.

But it isn't always clear what data is

needed, when, and for how long it should be

stored.

Martin Kunze, CMO, Cerabyte, explained,

"It is not yet defined how much raw sensor

data is needed for decision making, and

how long it needs to be retained for when it

comes to machine-human interaction. There

were already legal consequences for

companies that didn't keep enough data to

reconstruct accidents that were caused by

false AI-decisions."

Legal reasons, rather than purely

technological ones, will have their part to

play in how emerging memory technologies

are provisioned and used.

"The 'audit trail data' will be one of many

drivers that lead to the surging demand for

data storage," Kunze continued. "Current

storage technologies are approaching their

limits; analysts are forecasting a scenario

where mainstream technologies can deliver

only 50% of the required demand - a

looming supply gap could put AI-related

investments at risk."

A TIERED APPROACH:

Universal memory, which combines persistent

memory and storage into a single unit,

would seem to be the panacea, providing

fixed storage for vast amounts of data and

high speeds for processing on demand.

However, that is unlikely to be a realistic

proposition for some time, so tiered data

using a variety of technologies will be the

default in the short-to-medium term.

Arthur Sainio and Raghu Kulkarni,

Persistent Memory Special Interest Group cochairs,

SNIA (The Storage Networking

Industry Association), said, "Universal

memory such as PCM and ULTRARAM

promises to merge RAM speed with

persistence, but faces manufacturing

complexity, high costs, and scaling barriers.

Tiered architectures will dominate short-to-



STORAGE

MAGAZINE

25

ROUNDTABLE :


Faster persistent memory technologies have

their place, although there are still hurdles

that need to be overcome.

"Emerging alternatives like MRAM and

ReRAM provide advantages such as near-

SRAM speed, zero standby power in the

case of MRAM, and analogue compute

capabilities like ReRAM, but face scalability

and manufacturing hurdles. They are

gaining some traction as they promise better

scalability, energy efficiency, and

performance for future HPC demands, but

have hurdles to overcome," said Saino and

Kulkarni. "CXL NV-CMM types of products

offer DRAM-like speed and persistence,

making them valuable for caching and

checkpointing functions in HPC

applications. High density hybrid CXL

solutions are likely as well."

NO NEW ARCHITECTURES:

One thing that seems clear is that there will

not be a new server architecture for HPC

and AI workloads that replaces what we

have today. Advances in CPU and GPU

technology, and large investments in such

platforms, still make general-purpose

computing the best fit for most jobs.

As such, some emerging memory

technologies are likely to be more of niche

interest, for custom jobs that require the

fastest speeds. Computational-RAM (CRAM),

where computations can take place directly

in RAM, is a good example of this.

"Although CRAM offers compelling

advantages for AI inference and acceleration

in theory, it suffers from very limited

programmability and restricted workload

flexibility. As a result, CRAM is unlikely to

replace the traditional server architecture for

general HPC. Instead, it will at most be

deployed selectively for niche applications,"

said Baker.

Effective scaling and higher density:

Irrespective of this, AI and HPC are pushing

the requirements for more memory and

require more flexible ways of using it. In that

regard, continuing to push the boundaries of

today's memory technologies makes sense,

as it can help maximise investment in current

computing architecture.

At the core of memory development are

two technologies that can help: 3D DRAM

for increased capacity and Compute

Express Link (CLX) for improved scaling and

memory pooling.

"HPC and AI require both 3D DRAM for

capacity and bandwidth, and CXL for

scalable, cost-effective memory expansion.

3D DRAM such as HBM3, is ideal for onpackage,

high-speed tasks like training large

AI models due to its fast data access and

energy efficiency. CXL will provide pooled

memory for flexibility and persistent

workloads," said Sainio and Kulkarni. "A

hybrid approach that combines these

technologies is essential for efficiently

meeting the growing demands of modern

HPC and AI applications."

Emerging technologies also promise to

maximise the investment in existing storage,

which is particularly important given the

need for a tiered approach to modern

workloads.

Kunze gives an example: "Emerging

technologies such as ceramic storage can

release expensive high performing storage

like HDDs which today is used for storing

cold data, for a better use."

Emerging memory technologies also

promise improved caching and access to

data available on traditional storage

technologies, such as flash and hard disks.

"Advanced caching strategies leveraging

faster memory types - such as HBM or

stacked DRAM - can significantly accelerate

access to hot data, improving the

performance of existing storage systems.

Using persistent memory for metadata

acceleration or tiered caching layers will

continue to enhance storage efficiency

without fundamentally redesigning

architectures," said Baker.

SOFTWARE IS CRITICAL:

While hardware may steal the limelight,

software is essential in provisioning and

managing data tiers. Crucially, software has

to make life easier and work with what's

available, rather than changing how

systems work.

This is a valuable lesson learned from Intel

Optane, as Lynn explained: "A final hurdle

for Optane was the slow adaptation of the

software ecosystem. While, in theory, Optane


@STMagAndAwards


MAGAZINE

Ransomware-Proof

Backups with Ootbi

Ootbi (Out-of-the-Box Immutability) delivers secure, simple, and powerful backup storage for Veeam

customers with no security expertise required.

In a world where businesses fall victim to ransomware every 11 seconds and 93% of attacks are targeting

backups, Ootbi by Object First helps make backup data ransomware-proof.

3 Reasons Why Ootbi Is the Best Storage for Veeam

Secure

• S3 out-of-the-box immutability

• A hardened storage target with

zero access to the root

• Separation of the Backup

Software and Backup Storage

layers according to Zero Trust

best practices

Simple

• NO security expertise required

• 15 minutes to deploy and scale

• Updated and optimized

automatically by Object First

Powerful

• Lightning fast backup

up to 8 GB/s

• Supercharged Instant Recovery,

capacity, and performance scale

linearly

• Use of standard Veeam

block size and encryption

Eliminate the need to sacrifice performance

and simplicity to meet budget constraints

with Ootbi by Object First.

Learn More About

the Best Storage

for Veeam

ROUNDTABLE :


Faster persistent memory technologies have

their place, although there are still hurdles

that need to be overcome.

"Emerging alternatives like MRAM and

ReRAM provide advantages such as near-

SRAM speed, zero standby power in the

case of MRAM, and analogue compute

capabilities like ReRAM, but face scalability

and manufacturing hurdles. They are

gaining some traction as they promise better

scalability, energy efficiency, and

performance for future HPC demands, but

have hurdles to overcome," said Saino and

Kulkarni. "CXL NV-CMM types of products

offer DRAM-like speed and persistence,

making them valuable for caching and

checkpointing functions in HPC

applications. High density hybrid CXL

solutions are likely as well."

NO NEW ARCHITECTURES:

One thing that seems clear is that there will

not be a new server architecture for HPC

and AI workloads that replaces what we

have today. Advances in CPU and GPU

technology, and large investments in such

platforms, still make general-purpose

computing the best fit for most jobs.

As such, some emerging memory

technologies are likely to be more of niche

interest, for custom jobs that require the

fastest speeds. Computational-RAM (CRAM),

where computations can take place directly

in RAM, is a good example of this.

"Although CRAM offers compelling

advantages for AI inference and acceleration

in theory, it suffers from very limited

programmability and restricted workload

flexibility. As a result, CRAM is unlikely to

replace the traditional server architecture for

general HPC. Instead, it will at most be

deployed selectively for niche applications,"

said Baker.

Effective scaling and higher density:

Irrespective of this, AI and HPC are pushing

the requirements for more memory and

require more flexible ways of using it. In that

regard, continuing to push the boundaries of

today's memory technologies makes sense,

as it can help maximise investment in current

computing architecture.

At the core of memory development are

two technologies that can help: 3D DRAM

for increased capacity and Compute

Express Link (CLX) for improved scaling and

memory pooling.

"HPC and AI require both 3D DRAM for

capacity and bandwidth, and CXL for

scalable, cost-effective memory expansion.

3D DRAM such as HBM3, is ideal for onpackage,

high-speed tasks like training large

AI models due to its fast data access and

energy efficiency. CXL will provide pooled

memory for flexibility and persistent

workloads," said Sainio and Kulkarni. "A

hybrid approach that combines these

technologies is essential for efficiently

meeting the growing demands of modern

HPC and AI applications."

Emerging technologies also promise to

maximise the investment in existing storage,

which is particularly important given the

need for a tiered approach to modern

workloads.

Kunze gives an example: "Emerging

technologies such as ceramic storage can

release expensive high performing storage

like HDDs which today is used for storing

cold data, for a better use."

Emerging memory technologies also

promise improved caching and access to

data available on traditional storage

technologies, such as flash and hard disks.

"Advanced caching strategies leveraging

faster memory types - such as HBM or

stacked DRAM - can significantly accelerate

access to hot data, improving the

performance of existing storage systems.

Using persistent memory for metadata

acceleration or tiered caching layers will

continue to enhance storage efficiency

without fundamentally redesigning

architectures," said Baker.

SOFTWARE IS CRITICAL:

While hardware may steal the limelight,

software is essential in provisioning and

managing data tiers. Crucially, software has

to make life easier and work with what's

available, rather than changing how

systems work.

This is a valuable lesson learned from Intel

Optane, as Lynn explained: "A final hurdle

for Optane was the slow adaptation of the

software ecosystem. While, in theory, Optane


@STMagAndAwards


MAGAZINE

ROUNDTABLE :


""Universal memory such as PCM and ULTRARAM promises to merge RAM

speed with persistence, but faces manufacturing complexity, high costs,

and scaling barriers. Tiered architectures will dominate short-to-medium

term due to cost efficiency. Universal memory may see niche use (edge

AI, aerospace) but requires material breakthroughs to displace tiered

systems, likely post-2030. Hybrid solutions like CXL PMEM + DRAM +

SSDs, remain the pragmatic path." Arthur Sainio and Raghu Kulkarni, Persistent Memory Special

Interest Group co-chairs, SNIA (The Storage Networking Industry Association)

DIMMs expanded memory transparently to

the OS, in practice, optimising databases

and file systems to take full advantage of its

unique persistence and performance

characteristics proved to be complex and

time-consuming, further hindering its

widespread and effective use."

Software is critical to the success of any

technology, particularly in a future where

resources must be efficiently combined

across different platforms.

"Software optimises workloads across

CPUs, GPUs, TPUs, and CRAM by

managing resources, scheduling tasks, and

improving memory use. Tools like

Kubernetes and TensorFlow ensure efficient

hardware utilisation, while future

innovations in AI-driven orchestration,

unified APIs, and real-time monitoring will

enhance performance and energy efficiency

across heterogeneous platforms," said

Sainio and Kulkarni.

BARRIERS TO UPTAKE:

While the AI explosion may make adoption

of emerging memory technologies a forgone

conclusion, there are still many risks,

particularly around the investment in existing

memory technologies. Demand for new

technologies can be limited by what's

currently working.

A general resistance to new technology is

something noted by Norfolk, who

highlighted that one of the biggest barriers

to adoption is "The amount of legacy tech

still in use and working 'well enough' in

many applications. Plus, general mistrust of

anything too new unless there is no

alternative."

In a similar vein, new technology has to

be demonstrably better than what's

available now. As Baker said, "New

memory technologies must not only

outperform but also offer acceptable

economics compared to DRAM or NAND

to achieve widespread adoption."

These are factors that we've seen time and

time again, but failure to invest in emerging

technologies poses a risk of its own. As

Kunze explained: "100x more money is

invested in computation than in memory and

storage. But without investment in newly

scalable technologies, billions of investments

in AI could be squandered due to lack of

storage. This looming risk should be

exposed to and explored in the AI and AI-

Investor community."



STORAGE

MAGAZINE

29

ROUNDTABLE:


THE FUTURE IS COMING:

Despite these warnings, the requirements of

demanding computing workflows are only

exacerbating the memory wall problem,

increasing the need for novel solutions.

Emerging memory technologies are required

now more than ever, and wider adoption is

only a matter of time.

"Looking five years ahead, the confluence

of ever-increasing data intensity and the

scaling of datasets suggests we are indeed

on the cusp of a transformative period in

memory technology, arguably the most

significant in a generation. This relentless

growth in data demands will necessitate

radical advancements and new architectural

approaches to overcome the limitations of

current memory systems," said Lynn.

Developments in scalability and density

must be priorities for any new technology

looking to successfully tackle the memory

wall challenge. Thankfully, the building

blocks of these technological advancements

are already available.

"Breakthroughs in CXL-based memory and

Racetrack memory could transform the

industry. CXL will enable scalable, lowlatency

persistent memory integration, while

Racetrack memory offers ultra-high density,

faster speeds, and energy efficiency. These

advancements can revolutionise AI, HPC,

and edge computing performance," said

Sainio and Kulkarni.

It's important to think about how data will

be used to understand the future of

emerging memory technologies, as Kunze

explained: "There will be 'hot storage' and

'not so hot storage.' The distinction between

hot and cold storage/data will disappear;

rather, data will be classified by the need to

make it immediately accessible or not."

As a result, the future looks set to be based

on multiple technologies, with tiering used

to hit different requirements at different

points in a system. That means emerging

memory technologies, but also continuing to

push the limits of what today's technology

can offer.

"We expect there will be more flavours of

persistent and volatile memory. They will be

based primarily on DDR cell but also NAND

cells," said Baker. "The objective of DDR

based memory will offer lower power, slower

performance vs DRAM and cost vs a

standard DRAM. It will reside between

DRAM and NAND in the compute hierarchy.

The innovation on NAND memory will target

to expand the bandwidth in the overall

compute hierarchy to meet the needs of AI

and in-memory databases."

CONCLUSION

You'll probably be disappointed if you are

expecting a new, emerging memory

technology to become standardised in the

near future. For the time being, the

traditional tiered memory architecture isn't

going anywhere, and will continue to see

iterative improvements to boost speed and

capacity.

But, equally, the ever-growing demands of

AI and HPC workloads mean that there's a

sense of urgency to solve the performance

bottlenecks with current memory designs.

Held back by issues such as high costs,

limited software support and a general

resistance to technological change,

emerging technologies have not caught on

quite yet.

That said, there is clearly a sense that

change is inevitable, sooner or later, and

various approaches could be adopted now

to address these bottlenecks. As our

contributors make clear, while universal

memory may still be years away, the

combination of tiered approaches, persistent

memory, and advanced orchestration

software promises a transformative era for

HPC and AI workloads. For the technology

industry, the challenge is not if, but how fast,

we can adapt.


@STMagAndAwards


MAGAZINE

The future is here.

Tiered Backup Storage

• Fastest backups

• Fastest restores

• Scalability for fixed-length backup window

• Comprehensive security with ransomware recovery

• Comprehensive disaster recovery from a site disaster

• Low cost up front and over time

Thank you so much

to all who voted, and

congratulations to our fellow

Storage Awards 2025 winners!

Visit our website to learn more

about ExaGrid’s award-winning

Tiered Backup Storage.

LEARN MORE

TECHNICAL: SUPERMICRO

STORAGE IS TRANSFORMING AI

WENDELL WENJEN, DIRECTOR OF STORAGE MARKET DEVELOPMENT, SUPERMICRO CONSIDERS THE

ROLE OF DATA IN ENTERPRISE AI AND INCLUDES DATA LAKES FOR AGGREGATING ENTERPRISE DATA

AND USING IT FOR ENTERPRISE-SPECIFIC AI MODEL TRAINING FINE-TUNING

It's a cliché to say that "data is the new oil"

but what does that mean for enterprise

AI? How has enterprise AI evolved in the

past 12 months? Let's start by debunking the

"data is the new oil" analogy. While oil is a

fungible and finite commodity, data is mostly

unique and can be infinitely created. What is

true is that data, particularly the enterprise's

proprietary data, is the fundamental source

for the customisation of AI models for

specific companies, industry and use cases.

Most enterprises are in the process of

planning AI-enabled applications, and

many have successfully deployed some into

production. The process of moving proofof-concept

AI projects into full deployment

continues to be an area where many

projects face significant barriers and fail to

make the transition. These include elements

such as significant project costs, including

the AI development and deployment

infrastructure, project goal alignment with

stakeholders, and scarcity of AI

development talent.

THE ENTERPRISE DATA LAKE

The enterprise data lake where relevant

organisational data is collected from siloed

applications, shared drives and log data is

the most common method to utilise such

data to build AI learning models.

Identifying, aggregating, extracting,

normalising and other data ingestion

tasks, while often the most time

consuming and labor-intensive

part of the AI development

process, are essential to create

an accurate AI model. Modern

data lakes (as compared with

legacy Hadoop-based data

lakes) are based on object

storage software, which is often

stored on disk-based storage

servers, for cost efficiency.

Once ingested, the data is then

used to fine-tune commercial or

open-source large language models

(LLM), as in the case of generative AI

applications. Rather than create a

completely new LLM from scratch,

a pre-built language model

which incorporates commonly

available domain

knowledge but requires

additional training using

enterprise's specific

data. This enterprise model fine-tuning stage

requires dedicated GPU and storage

infrastructure and is a continuous process as

new data is created. The result is a

customized large language model which

contains the company's specific information

to generate responses.

It's often not feasible to retrain enterprise

LLMs every time new data is created,

especially in the case of real-time data such

as financial market information, news and

other temporal data. In these cases, retrieval

augmented generation (RAG) has become a

popular technique. It appends contextually

relevant information to the input query which

is used to augment the original query.

The retrieval phase searches a vector

database for similar information where the

relevant information has been previously

stored in the form of vector embeddings

which are numerical representations of the

data and then combines it with the

tokenised original query as input into the

enterprise LLM. This method produces more

relevant responses and reduces

hallucinations. The vector database used in

RAG is a data store which can be

implemented as file or object storage.

CHANGES IN THE STORAGE

INFRASTRUCTURE

Storage and data management continue to

be an integral part of enterprise AI

infrastructure. This includes storage servers,

networking, and disk and flash media,

which all build a foundation for retaining

enterprise data in a persistent and protected

environment. Both disk and flash-based

storage are used in enterprise AI

infrastructure with tradeoffs in cost and

performance.


@STMagAndAwards


MAGAZINE

TECHNICAL: SUPERMICRO

"The process of moving proof-of-concept AI projects into full deployment continues to be

an area where many projects face significant barriers."

Data management refers to the storage

management software used to maintain and

update digital information. This can be

block-based, file-based or object-based, and

whilst each storage access method has a

role in the enterprise AI infrastructure, they

again offer tradeoffs in performance and

flexibility to accommodate fixed or variable

sized data. A new element of data

management is the introduction of data

orchestration, which adds intelligent and

automated workflows to the data

management platforms.

Data having gravity is a common metaphor

referring to the difficulty in moving large data

sets to different computing resources. As

enterprise data stores grow, the concept of

data gravity will drive more of the AI

computing workload to be done "in place".

This means that the computational resources

will come to the data or be incorporated into

the data management platforms rather than

moving the data to the compute resources.

This is especially important when executing

demanding workloads, at scale.

LARGE SCALE INFERENCE

One change from last year is the

implementation of large-scale, high-volume

inference as a part of agentic AI workflows,

which combines a series of reasoning or

goal-seeking series of AI agents. This highvolume

AI inference workload processes

thousands of queries per second, requiring

more optimised efficiency in data processing.

One optimisation which is starting to

become adopted is known as a

disaggregated inference process, which

separates the two phases of processing an

inference query. First, the prefill phase

tokenises input query, and the second

decode phase outputs the AI model

response. By dedicating separate GPUs

resources for each phase, the overall

inference throughput can be improved.

In the decode phase, a further optimisation

is to store the results of previously processed

queries to look up the results when the same

token pattern is presented. The Key-Value

(KV) cache stores these previous results in

multiple tiers - from the very fast but smallscale

GPU memory, to larger, local in-system

NVMe storage, and then further to shared

large scale network storage.

This KV cache can grow to multiple

petabytes, using shared NVMe-based file or

object storage for these intermediate token

results. Processing bottlenecks from

continuous re-computation of the same

query can be eliminated. By referring to

results stored in the KV cache, the overall

inference performance is greatly increased.

STORAGE ECOSYSTEMS

NEED TO BE A

SOLUTION FOR AI

The role of data in enterprise

AI includes the data lake

for aggregating the

enterprise data

and using it

for

enterprise-specific AI model training finetuning.

As AI becomes more prevalent in

corporate environments, businesses need to

adopt tools like RAG inference which

contains a vector database to enable the

fast lookup of enterprise specific information

related to their AI queries. Another new

trend is the need for large scale inference

and the implementation of disaggregated

inference processing which contains the KV

cache data, primarily stored in flash-based

network storage.

With the state-of-the-art enterprise AI

infrastructure and processes continuing to

evolve and improve, the companies

implementing these projects need to develop

infrastructure which is flexible, reconfigurable

and able to support new AI deployment

methods developed in the future. However,

the fundamental storage infrastructure and

management of enterprise data will always

be reusable.

More Info: www.supermicro.com



STORAGE

MAGAZINE

33

CASE STUDY:

CASE STUDY: NATIONAL LIBRARY OF SCOTLAND

NATIONAL LIBRARY OF

SCOTLAND ENTRUSTS

CULTURAL TREASURES TO SCALITY

THOUSANDS OF ASSETS ARE DIGITISED AND STORED ON SCALITY

RING PER WEEK, PRESERVING PRECIOUS COLLECTIONS AND

MAKING THEM ACCESSIBLE TO THE PUBLIC

The National Library of Scotland (NLS)

houses one of Scotland's national

cultural collections, and, as a legal

deposit library, it is entitled to claim a copy

of everything published in the United

Kingdom. The 31 million items in its

growing collection already occupy 120

miles of shelving, with around 5,000 new

items being added every single week.

The library's holdings include vastly differing

formats - from maps to music to VHS tapes -

as well as priceless items, including one of

only 21 complete Gutenberg Bibles known to

exist and the last letter written by Mary Queen

of Scots just before her execution in 1587.

THE CHALLENGE

The library set an ambitious goal for a third

of its collection to be in digital format by

2025. Their former preservation storage

involved one copy on SAN, backed up on

tape. As the digitisation initiative got

underway, the strategy had to be

reconsidered. To preserve their precious data,

NLS decided to keep three copies in different

geographic locations and use multiple

technologies for safety with checksums to

ensure data integrity twice each year.

With so much irreplaceable data to hold,

protect and make accessible for generations

to come, eliminating tape, while ensuring

streamlined growth and enabling simple onprem

and cloud storage synergy with S3,

emerged as key goals.

THE OUTCOME

After receiving proposals from "all of the

expected vendors," NLS chose Scality RING as

a foundation of their preservation storage

strategy. In addition to providing the resilient

S3-compatible storage they wanted, Scality

further advanced the library's data integrity

assurance model by developing a Bitrot

checker for digital preservation that

streamlines the integrity checking process.

Now that Scality RING has shown its strength,

the National Library of Scotland is looking to

add use cases and is even considering

offering it as a service to other organisations,

given its multi-tenancy capabilities.

"In an environment where there are large

volumes of invaluable data, we needed a

ransomware-proof backup solution that was

easy and quick to implement while also being

capable of infinite scaling up as data and use

cases increase. Working with Scality has been

brilliant."

Stuart Lewis Associate Director, National

Library of Scotland

Results: Scalability: Now the storage can grow

as they achieve their digitisation goals. All they

have to do is add more capacity, linearly.

There's no rip and replace, and no technology

refresh - add drives to servers, add servers

when the current ones are at capacity.

Standard S3 interface: To achieve a single

interface for cloud and on-prem object

storage, the library decided to standardise on

S3. This decision motivated a re-engineering

of their homegrown asset management system

to support S3 - and was key to choosing

Scality RING.

Lower TCO: The library maintains three

copies - one in each of their data centres and

one in the cloud. Ease of management and

the ability to scale without replacement,

coupled with software licensing that doesn't

penalise for replicating the data, which equals

big savings.

Less stress: No LUNS means less maintenance

and no more lengthy tape backups from

which the library wondered if they would ever

be able to restore. All that, plus they can lose

a data centre and everything is fine - even

available throughout.

"We're looking at moving other backups,

replacing tape with disk-to-disk backup;

moving the non-print collections and even

offering it as a service to other organisations,

given its multitenancy capabilities."

Stuart Lewis Associate Director, National

Library of Scotland

More Info: www.scality.com


@STMagAndAwards


MAGAZINE

ST Sep-Oct 2025

Transform your PDFs into Flipbooks and boost your revenue!

Delete template?

Save as template ?