Unpacked Network

In this episode, Chris talks to Patrick Smith, EMEA CTO at Pure Storage. The topic of conversation is the vision Pure Storage has for the future of data management within the enterprise. Extending on the messaging of the “Cloud Operating Model”, Patrick explains how Pure Storage has built an ecosystem of hardware and software that delivers value to customers through automation, policy and commercial flexibility. Patrick starts by outlining the issues he sees being experienced by customers every day. In many respects these reflect the same challenges over many decades, cost constraints, massive growth in capacity demands and restrictions on staff. Today that mix also includes AI and protecting data against ransomware. Of course, delivering infrastructure in an efficient way is an evolving process that needs constant innovation. Today we see that through FlashArray, FlashBlade, Purity, Pure1 and Fusion. What could be in the future? Tune in (or attend) Pure Accelerate to find out! The event takes place in Las Vegas between 17th-19th June 2025. Elapsed Time: 00:48:06 Timeline 00:00:00 – Intros 00:01:45 – What are the current storage and data problems for customers in the data centre? 00:03:13 – What has changed? Are we seeing the same problems as always? 00:04:51 – Pure is touting 300TB modules, an entire system 20 years ago 00:06:52 – Data is starting to change value over time (rather than declining) 00:08:15 – Automation and policy form a key part of Pure’s vision 00:12:10 – Budgets remain a challenge, especially with AI projects 00:13:44 – Quality of Service should enable data management in place 00:16:05 – Pure offers “Zero Move” tiering to implement in-place QoS 00:22:02 – Cost of complexity is a hidden cost in many businesses 00:24:44 – Public cloud was the greatest example of Shadow IT 00:27:04 – Pure Storage promotes a “Cloud Operating Model” 00:28:06 – Cloud means fleet management with policy and automation 00:32:40 – AI Copliot has helped customers to manage systems 00:36:33 – Pure builds simple hardware that can be exploited by software 00:37:37 – Software includes SaaS capabilities such as Pure1 00:39:07 – Many customers don’t want to manage their systems from SaaS 00:40:21 – The commercial model is the final piece in the Pure Strategy 00:44:30 – Subscriptions continues to lead revenue growth 00:46:44 – How should customers adapt to address the problems of the modern data centre? Copyright (c) 2016-2025 Brookend Ltd. No reproduction or re-use without permission. Podcast episode #bncv

In this episode, Chris talks to Sharad Kumar, Field CTO at Qlik about the value of good-quality data when developing AI solutions. Much of the current discussion around AI and large-language models (LLMs) is focused on the infrastructure and the significant expense needed to build and train generative AI. However, as the revelation of DeepSeek shows, the industry trend will see models commoditise and become cheaper to train and run. If infrastructure and software become quickly affordable, what is the differentiator for businesses? The answer is clearly their data. Data has value to an enterprise, but only if it is in an acceptable format. That means being of high quality and in terms of how Qlik operates, a trusted resource. During the conversation, Sharad explains the six metrics of the Talend Trust Score, a methodology that measures the value of data based on Diversity, Timeliness, Accuracy, Security, Discoverability and Consumability. He explains how the Trust Score is calculated, but more importantly, how businesses can build a framework to continually improve the quality and value of their data resources. More information on Qlik can be found on the company website – here. Sharad mentions the user conference taking place in May, details of which can be found here. Finally, Sharad references the Qlik LinkedIn page, which can be found here. Elapsed Time: 00:47:47 Timeline 00:00:00 – Introductions 00:01:46 – Data is the value piece within AI, not infrastructure 00:02:27 – What is occurring within the AI market? 00:04:25 – The future will be a mix of AI model types and sizes 00:05:20 – Will businesses build or buy models? 00:07:10 – How will agentic AI architectures work? 00:10:30 – Customers need to focus on data quality 00:12:44 – Both training and RAG data needs to be high quality 00:14:40 – Agentic AI wil be intent-driven 00:16:43 – What does good data look like within an enterprise? 00:19:28 – Qlik has a 6-dimensional trust score 00:26:11 – How do customers calculate their trust score? 00:30:09 – Is AI driving better data quality? 00:34:51 – Qlik can help customers develop a data improvement programme 00:37:36 – Qlik brings “product thinking” to data 00:38:56 – Where are businesses on the AI journey? 00:41:12 – How is improving data quality driving improving AI benefits? 00:42:26 – AI could be applied to fix data quality problems Copyright (c) 2016-2025 Unpacked Network. No reproduction or re-use without permission. Podcast episode #ggc2

In this episode, Chris discusses the options available to storage system vendors when building modern storage appliances, with Bill Basinas, Senior Director, Product Marketing at Infinidat. The conversation derives from an observation on architectural choices, following the move to AMD processors from Intel for the latest G4 systems built by Infinidat. AMD offers a greater core count per processor compared to Intel, allowing Infinidat to move to single socket designs, while gaining improvements from PCIe 5.0 and DDR5 memory. Ultimately, this discussion highlights how modern storage system design can take standardised components and build flexible architectures, implementing most features in software. For Infinidat, that could mean expanding its range of solutions for smaller enterprise requirements, or building out products specifically for Edge use cases. Although Bill did not reveal any future plans, the implication is clear – watch this space for future evolution of the InfiniBox architecture to a wider and more varied set of hardwaree configurations. Elapsed Time: 00:37:13 Timeline 00:00:00 – Intros 00:01:15 – How do vendors choose the hardware components for storage systems? 00:02:30 – What are the main (storage) technology challenges for customers? 00:04:08 – Customers want predictable data features 00:05:55 – Capacity demand continues to grow relentlessly 00:07:30 – Infinidat features are built into software 00:09:35 – Most AI requirements wil run on existing performance storage 00:11:20 – Modern hardware provides significant flexibility for system design 00:15:00 – AMD gives access to single and high core-count processors 00:16:10 – PCIe 5.0 provides for faster SSDs and power efficiency 00:18:46 – Infinidat has introduced smaller form-factor solutions 00:21:32 – Multiple cores will always get used! 00:25:53 – Infinidat G4 architecture provides for in-place controller upgrades 00:28:22 – Storage arrays should become more “virtual” 00:34:10 – Data services implementations are very different between vendors 00:35:55 – Hybrid architecture still has value in the Infinidat world 00:36:20 – Wrap Up Related Podcasts & Blogs Storage Unpacked 258 – Introducing Infinidat G4, InfuzeOS 8 and InfiniSafe ACP #202 – Enterprise Storage Consolidation with Phil Bullinger from Infinidat Infinidat adds customer value with SSA Express and improved SSA capacity Copyright (c) 2016-2025 Unpacked Network. No reproduction or re-use without permission. Podcast episode #e4dr

In this episode, Chris discusses the enduring benefits of centralised storage, particularly with reference to storage virtualisation, with Dan Kogan, VP of Enterprise Growth and Solutions and Cody Hosterman, Senior Director of Product Management, both from Pure Storage. Centralised or shared storage has been around for over 30 years, providing efficiencies in infrastructure and operational management. In the virtualisation context, centralisation provides the ability to abstract workloads from the hypervisor and add flexibility and data management features to a centrally managed platform. Vendors, such as Pure Storage, have invested resources in making centralised storage efficient, while also providing significant security benefits that couldn’t be achieved with an HCI model. Although this discussion was intended to focus on centralisation, the ultimate conclusion of the conversation is to realise that centralised storage is a precursor to storage-as-a-service. This is where the industry is headed, whether using on-premises or public cloud infrastructure. Elapsed Time: 00:35:34 Timeline 00:00:00 – Intros 00:01:17 – Shared or Centralised Storage has become a perpetual feature of the data centre 00:02:00 – Where did centralised storage come from? 00:03:03 – VMware introduced compute efficiencies, centralised storage does the same 00:05:20 – Centralised storage now incorporates block, file and object protocols 00:07:10 – HCI was probably the biggest “challenge” to centralised storage 00:13:04 – Centralisation is bringing additional consolidation benefits 00:15:55 – Centralisation provides significant operational benefits 00:17:36 – Integrated storage (HCI) is inherently insecure compared to centralised storage 00:22:31 – Data mobility is a key requirement of modern enterprises 00:29:11 – Centralised storage is driving us towards storage-as-a-service. 00:31:10 – Storage is becoming an “endpoint” 00:32:31 – Wrap Up Related Podcasts & Blogs Analysis: Storage vendors assist in the optimisation of VMware workloads Copyright (c) 2016-2024 Unpacked Network. No reproduction or re-use without permission. Podcast episode #jjr3

In this episode, Chris is in conversation with Jeb Horton, SVP Global Services at Hitachi Vantara, discussing the capabilities of Hitachi Vantara’s Global Services offerings, which deliver infrastructure management and infrastructure as a service to its customers. In addition to EverFlex, Hitachi Vantara has a long history of managed services capabilities that span more than just outsourced storage. As Jeb explains, the company also manages storage infrastructure from other vendors, in addition to non-storage systems. The interesting aspect of this discussion is the complex nature of the interaction between customers and Hitachi. Solutions offerings aren’t merely “transactional”, but have a human aspect and are tailored to meeting the specific goals of the customer. This conversation explores some of the nuances of working with customers to transfer the burden of infrastructure management to Hitachi, enabling businesses to focus on more strategic opportunities. To learn more about Hitachi Vantara check out the Infrastructure as a Service section on the Hitachi website – https://www.hitachivantara.com/en-us/services/infrastructure-as-a-service. Elapsed Time: 00:48:02 Timeline 00:00:00 – Intros 00:01:43 – What is “Infrastructure as a Service”? 00:03:25 – What else to customers want from a service (other than cost saving)? 00:05:20 – Public cloud has increased the appetite for service-based consumption 00:06:24 – What is the core of the Hitachi Vantara services offering? 00:07:14 – Hitachi added automation into a “services platform” 00:10:26 – The human aspect involves skills but also relationships 00:12:20 – A service contract involves a detailed commercial model 00:13:51 – Service also means service levels and agreements 00:16:53 – Cloud is transactional, what is Hitachi’s “value add”? 00:19:45 – Data has value, which is the focus of service offerings 00:22:26 – How does Hitachi help government institutions? 00:26:50 – What sort of data issues does Hitachi deal with? 00:28:33 – Data and AI will be a key issue to manage 00:30:40 – How does the engagement process work with Hitachi (and what is EverFlex)? 00:37:15 – What are real-world examples of Hitachi customers and requirements? 00:46:51 – Wrap Up Related Podcasts & Blogs Hitachi Vantara Microsite Storage Unpacked 260 – Hitachi VSP One Updates with Dan McConnell Storage Unpacked 254 – Announcing VSP One and Hitachi Vantara Reorganisation Copyright (c) 2016-2024 Unpacked Network. No reproduction or re-use without permission. Podcast episode #4d3x

In this recording, Chris talks to Subbiah Sundaram, SVP of Products at HYCU, Inc. about the 2024 edition of the HYCU State of SaaS Data Resilience Report. The report surveys customers to understand the gaps in perceived and actual data protection for SaaS platforms and the results are quite surprising. Subbiah walks through the top four findings, covering the understanding of the pervasive nature of SaaS in modern business, perceptions of data protection and the unexpected risks created by SaaS platforms. HYCU provides a robust and comprehensive approach to SaaS data protection, called R-Graph, part of R-Cloud. We’ve covered these products in previous podcasts, shown in the related content section below. We recommend downloading the report, which can be found here – The State of SaaS Data Resilience in 2024. Details on R-Graph can be found here – R-Graph. Elapsed Time: 00:39:59 Timeline 00:00:00 – Intros 00:01:39 – What is the SaaS Resiliency Report for 2024? 00:02:23 – There are over 35,000 global SaaS applications 00:04:11 – SaaS has become embedded in business process 00:05:02 – Businesses underestimate SaaS applications by 10x 00:06:29 – Businesses don’t realise SaaS data isn’t protected like on-premises 00:09:20 – 61% of data breaches occur through SaaS platforms 00:13:40 – Businesses assume cloud platforms protect their data 00:15:18 – The reasons for data restoration are multi-fold and business related 00:17:47 – 75% of critical infrastructure (identity management) was not being protected 00:19:21 – All credentials management systems operate slightly differently 00:22:30 – Business process creates historical security exceptions 00:26:09 – use R-Graph to discover your application dependencies 00:27:42 – Protect your identity management systems 00:31:09 – R-Cloud enables anyone to add data integrations for backup 00:32:26 – Protect your endpoints, protect your data, protect your customer data 00:34:18 – Where does SaaS data protection go next? Tracking behaviour 00:37:14 – R-Cloud can be used for cross-environment data seeding 00:39:12 – Wrap Up Related Podcasts & Blogs Data Unpacked 006 – Introducing HYCU R-Cloud Data Unpacked 004 – Reflections on Data Management, Security & Protection With HYCU CEO Simon Taylor Research Note: HYCU extends SaaS Integration with R-Scout and Generative AI HYCU expands SaaS and IaaS backup with protection for AWS Infrastructure as Code HYCU tackles the SaaS data protection challenge with the announcement of R-Cloud Copyright (c) 2016-2024 Unpacked Network. No reproduction or re-use without permission. Podcast episode #vcxz

In this podcast episode, Chris is in conversation with Jeffries Briginshaw (Head of EMEA Government Relations at NetApp) and Adam Gale (CTO for AI & Cyber Security, NetApp) discussing the EU AI Act and the regulation of artificial intelligence across the world. The EU AI Act is an early introduction into the regulation of the use of AI by businesses within their engagements and interactions with customers. As explained in this conversation, there are classifications of AI types and within that, restrictions on what businesses are permitted to implement based on those categorisations. Some AI usage will be banned, while others will require human intervention and close monitoring. How should your business engage with AI and ensure compliance with the act? Listen to the discussion for more details. As mentioned in the recording, for details on what NetApp can offer, point your favourite browser to https://www.netapp.com/artificial-intelligence/ to learn more. Elapsed Time: 00:52:17 Timeline 00:00:00 – Intros 00:01:19 – Why should we be regulating AI? 00:02:30 – What will the impacts of AI be on personal and work life? 00:03:55 – What if we get regulation wrong? 00:05:30 – What happens if AI goes wrong, such as data poisoning? 00:09:04 – Existing EU/UK law has been successful at regulation (GDPR) 00:10:25 – What is the EU AI Act? 00:11:46 – “Prohibited Practices” will be banned from 2025 00:14:00 – How will the use of business in AI be regulated? 00:18:05 – The EU AI Act appears to focus on protection for individuals 00:20:56 – EU citizens are broadly positive to AI – if it is successfully regulated 00:21:52 – Compliance has an overhead – in terms of hard costs (developers) 00:25:20 – What are the penalties for not complying with the EU AI Act? 00:29:50 – What about the rest of the world – the US and elsewhere? 00:35:10 – Could we see “cross-border” complexity? 00:37:40 – What are the technology implications for AI regulation? 00:40:07 – Should businesses be demonstrating their AI compliance? 00:44:03 – What does NetApp offer customers to help AI compliance? 00:47:38 – AI will require a “big red stop button” 00:50:00 – Wrap Up Copyright (c) 2016-2024 Unpacked Network. No reproduction or re-use without permission. Podcast episode #dfsx

In this podcast episode, Chris discusses the platform update announcements from Pure Accelerate 2024 with Prakash Darji, VP and GM of the Digital Experience BU at Pure Storage. The new features focus on usability and operational enhancements, including AI-based features and support for AI workloads. Highlighted in this discussion are: Fusion automation enhancements for fleet management and individual arrays New Generative AI Copilot for storage to provide querying capabilities and advice Evergreen//One for AI – an AI-level tier of Storage-as-a-Service NVIDIA SuperPOD Ethernet Certification Secure application Workspaces using Portworx Cyber Recovery and Resilience SLAs Security Assessment SLA AI-Powered Anomaly Detection enhancements Site Rebalance SLA AI-Powered Reserve Expansion recommendations As the list shows, there are lots of new updates to make the management and operation of a Pure Storage fleet more efficient and easy. As Prakash explains the reasoning behind the features, it is clear that AI is being used to deliver simplicity, while the platform will provide support for customers wanting to build AI-focused workloads. To learn more, follow the news from Pure Accelerate 2024 here (link). Prakash mentions two blog posts, which can be found here – Ransomware is a Darwinian Problem That Will Never Be Solved and Editorial: Why Centralised Storage Refuses to Go Away. Elapsed Time: 00:38:33 Timeline 00:00:00 – Intros 00:00:51 – It’s not all about AI! 00:01:34 – What changes have been announced to the Pure Storage platform? 00:02:37 – New features include cybersecurity enhancements and simplicity of management 00:03:30 – How do we manage systems at scale? 00:04:27 – Applications need policy management 00:05:08 – Fusion has been enhanced to enable array or fleet management at the same time 00:08:10 – Pure is introducing a GenAI Copilot in preview 00:12:19 – Evergreen now has an AI storage-as-a-service tier 00:14:00 – Pay for performance and capacity is a feature of Evergreen 00:15:55 – SuperPod certification for Ethernet is coming to Pure Storage arrays 00:16:40 – There must be many Jensen clones 00:18:27 – Pure is introducing secure application workspaces using Portworx 00:22:32 – New cybersecurity features include a security assessment for configuration settings 00:23:19 – There is also a security SLA for fixing and certificating security settings 00:24:01 – The AI Copilot will also recommend security improvements 00:24:32 – Anomaly detection is now performance-based, looking at typical profiles 00:30:45 – Reserve expansion recommendation is now AI-powered 00:31:55 – Reserve commit across sites can now be rebalanced once per year 00:33:40 – It’s easy for storage to become fragmented between sites 00:36:27 – When will the new features be made available? 00:37:45 – Wrap Up Related Podcasts & Blogs Storage Unpacked 259 – Sustainable Storage in the World of AI with Shawn Rosemarin Storage Unpacked 257 – The Future of Data Storage in the Enterprise Storage Unpacked 252 – A Vision of Storage Future with Coz from Pure Storage Storage Unpacked 251 – Modernising Storage as a Service with Prakash Darji Pure Storage Microsite X-Ray: Pure Storage, Inc. Copyright (c) 2016-2024 Unpacked Network. No reproduction or re-use without permission. Podcast episode #

In this podcast episode, Chris catches up with Dan McConnell, Senior VP for Product Management at Hitachi Vantara. The company recently announced VSP One Block, a new mid-range appliance for block storage. This follows on from two product announcements in April, which we covered in this Research Note, and the restructuring of Hitachi Vantara announced towards the end of last year (see this Research Note). Dan discusses VSP One Block, an appliance that targets mid-range storage requirements. He also covers VSP One SDS, a software-defined solution which runs in AWS and on-premises. The third product announcement covers file, with VSP One File, the latest iteration of the technology that came from the BlueArc acquisition over a decade ago. You can find out more about the Block Storage Appliance here (link and here). Details on the VSP One SDS announcement can be found here (link), which includes details on VSP One File. Elapsed Time: 00:15:29 Timeline 00:00:00 – Intros 00:01:18 – April 2024 announcement – VSP One SDS & VSP File 00:02:00 – Hitachi blog products use SVOS 00:03:13 – VSP one SDS is scale-out 00:03:51 – VSP File is the evolution of previous file-based products 00:05:16 – The VSP One family introduces consistent management & hybrid support 00:06:24 – EverFlex introduces multiple consumption models 00:08:30 – VSP Block 20 is the next generation mid-range storage array 00:10:10 – Dynamic Carbon Reduction optimises power usage by workload demand 00:12:03 – What comes next? 00:13:15 – Cloud storage products shouldn’t be a “lift and shift” 00:14:47 – Wrap Up Related Podcasts & Blogs Research Note: Hitachi Vantara VSP One reaches GA Research Note: Hitachi Vantara reorganises and announces VSP One Platform Hitachi Vantara Microsite X-Ray: Hitachi Vantara Storage Unpacked 254 – Announcing VSP One and Hitachi Vantara Reorganisation with Gary Lyng Copyright (c) 2016-2024 Unpacked Network. No reproduction or re-use without permission. Podcast episode #4dcx

In this episode, Chris discusses the topic of building sustainable storage solutions with Shawn Rosemarin, Global VP of Customer Engineering at Pure Storage. AI and specifically Generative AI (GenAI) has become a hot topic over the past 12 months. Businesses are looking at projects to use AI internally for productivity gains, but also to drive additional business. However, AI is still relatively expensive and requires huge volumes of training data. Training is an ongoing process that must react to changes in the data landscape, such as rights and permissions, and government regulation. With AI hardware being so expensive, it’s important to get the storage piece right, and that means having a scalable and cost effective solution. Shawn details how Pure Storage has focused on two aspects. First, the hardware, where DFMs (direct flash modules) have reached 75TB, with commitments to deliver 150TB and 300TB drives in the next few years. Second, the software management capability delivered through Purity, the operating system of Pure Storage hardware. It’s clear that building cost and power-efficient flash devices will be a challenge for the wider industry, where the focus lies with consumer devices. Pure Storage believes it is well positioned to help customers and potentially hyper-scalers in their goals to deliver efficient storage for AI. As Shawn highlights, this topic and more will be discussed at Pure Accelerate, to be held in Las Vegas from 18-21 June 2024. Check out the website where you can learn more. Elapsed Time: 00:52:08 Timeline 00:00:00 – Intros 00:01:44 – We’ve been quiet on the topic of AI 00:03:10 – AI has become cost-effective (sort of) 00:04:00 – Efficient AI is a 10-15 year journey 00:05:22 – AI technology needs to be efficient due to the resource demands 00:06:41 – Data growth is currently growing at 30% per annum 00:07:31 – Early mover may not be the best move with AI 00:08:16 – 149 foundational models were released in 2023 00:09:10 – Businesses will want to merge public and private data 00:10:40 – Results accuracy is super-important 00:13:30 – Trusted AI will be adopted in areas like security & vehicle evasive manoeuvres 00:15:10 – Where will AI models be developed? 00:16:37 – Model retraining will be required due to changing data ownership & permissions 00:18:30 – Model training also needs to be resource efficient 00:19:49 – $100 million to do the basic training of an AI model 00:22:26 – How do you feed GPUs with adequate data to run at 100% 00:24:10 – Edge devices could be used for AI processing 00:25:18 – How will data centres need to evolve for AI? 00:28:08 – Sustainability, regulation and jobs will all be issues in AI deployment 00:31:05 – With HPC, many users built bespoke systems and that’s a problem for AI 00:33:45 – How will businesses “industrialise” their AI projects? 00:36:46 – Storage density will help resolve the operational issues of AI storage 00:38:19 – SSD vendors’ main market is 2TB consumer SSDs 00:39:32 – 300TB drives are great, but how will software manage the hardware? 00:41:51 – Pure Storage DFMs will grow exponentially in capacity 00:42:43 – Hardware engineering is cool again! 00:45:15 – How will the hyper-scalers deal with massive storage growth? 00:51:30 – Wrap Up Related Podcasts & Blogs Storage Unpacked 257 – The Future of Data Storage in the Enterprise Storage Unpacked 252 – A Vision of Storage Future with Coz from Pure Storage Storage Unpacked 245 – Design Strategies for 300TB Flash Drives with Shawn Rosemarin from Pure Storage Dude, Here’s Your 300TB Flash Drive! Copyright (c) 2016-2024 Unpacked Network. No reproduction or re-use without permission. Podcast episode #xs2w