In this episode, we welcome Lead Principal Technologist Hari Kannan to cut through the noise and tackle some of the biggest myths surrounding AI data management and the revolutionary FlashBlade//EXA platform. With GPU shipments now outstripping CPUs, the foundation of modern AI is shifting, and legacy storage architectures are struggling to keep up. Hari dives into the implications of this massive GPU consumption, setting the stage for why a new approach is desperately needed for companies driving serious AI initiatives.
Hari dismantles three critical myths that hold IT leaders back. First, he discusses how traditional storage is ill-equipped for modern AI's millions of small, concurrent files, where metadata performance is the true bottleneck—a problem FlashBlade//EXA solves with its metadata-data separation and single namespace. Second, he addresses the outdated notion that high-performance AI is file-only, highlighting FlashBlade//EXA's unified, uncompromising delivery of both file and object storage at exabyte scale and peak efficiency. Finally, Hari explains that GPUs are only as good as the data they consume, countering the belief that only raw horsepower matters. FlashBlade//EXA addresses this by delivering reliable, scalable throughput, efficient DirectFlash Modules up to 300 TB, and the metadata performance required to keep expensive GPUs fully utilized and models training faster.
Join us as we explore the blind spots in current AI data strategies during our "Hot Takes" segment and recount a favorite FlashBlade success story. Hari closes with a compelling summary of how Pure Storage's complete portfolio is perfectly suited to provide the complementary data management essential for scaling AI. Tune in to discover why FlashBlade//EXA is the non-compromise, exabyte-scale solution built to keep your AI infrastructure running at its full potential.
For more information, visit: https://www.pure.ai/flashblade-exa.html
Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts:
https://purecommunity.purestorage.com/
00:00 Intro and Welcome
04:30 Primer on FlashBlade
11:32 Stat of the Episode on GPU Shipments
13:25 What is FlashBlade//EXA
18:58 Myth #1: Traditional Storage Challenges for AI Data
22:01 Myth #2: AI Workloads are not just File-based
26:42: Myth #3: AI Needs more than just GPUs
31:35 Hot Takes Segment
All content for The Pure Report is the property of Pure Storage and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
In this episode, we welcome Lead Principal Technologist Hari Kannan to cut through the noise and tackle some of the biggest myths surrounding AI data management and the revolutionary FlashBlade//EXA platform. With GPU shipments now outstripping CPUs, the foundation of modern AI is shifting, and legacy storage architectures are struggling to keep up. Hari dives into the implications of this massive GPU consumption, setting the stage for why a new approach is desperately needed for companies driving serious AI initiatives.
Hari dismantles three critical myths that hold IT leaders back. First, he discusses how traditional storage is ill-equipped for modern AI's millions of small, concurrent files, where metadata performance is the true bottleneck—a problem FlashBlade//EXA solves with its metadata-data separation and single namespace. Second, he addresses the outdated notion that high-performance AI is file-only, highlighting FlashBlade//EXA's unified, uncompromising delivery of both file and object storage at exabyte scale and peak efficiency. Finally, Hari explains that GPUs are only as good as the data they consume, countering the belief that only raw horsepower matters. FlashBlade//EXA addresses this by delivering reliable, scalable throughput, efficient DirectFlash Modules up to 300 TB, and the metadata performance required to keep expensive GPUs fully utilized and models training faster.
Join us as we explore the blind spots in current AI data strategies during our "Hot Takes" segment and recount a favorite FlashBlade success story. Hari closes with a compelling summary of how Pure Storage's complete portfolio is perfectly suited to provide the complementary data management essential for scaling AI. Tune in to discover why FlashBlade//EXA is the non-compromise, exabyte-scale solution built to keep your AI infrastructure running at its full potential.
For more information, visit: https://www.pure.ai/flashblade-exa.html
Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts:
https://purecommunity.purestorage.com/
00:00 Intro and Welcome
04:30 Primer on FlashBlade
11:32 Stat of the Episode on GPU Shipments
13:25 What is FlashBlade//EXA
18:58 Myth #1: Traditional Storage Challenges for AI Data
22:01 Myth #2: AI Workloads are not just File-based
26:42: Myth #3: AI Needs more than just GPUs
31:35 Hot Takes Segment
The Platform Mindset: Driving Workflow Efficiency in the Data Center
The Pure Report
53 minutes 44 seconds
1 month ago
The Platform Mindset: Driving Workflow Efficiency in the Data Center
The Pure Report welcomes Shawn Rosemarin, VP R&D, Customer Engineering at Pure Storage, to explore the critical topic of workflow optimization in today's IT landscape. Shawn shares his unique perspective on how the industry is moving beyond a product-centric view to embrace a platform mindset, emphasizing the profound impact this shift has on people and processes. Drawing on decades of experience, he highlights how true value is derived when technology actively evolves the way companies operate, making life better for IT professionals and streamlining essential business functions.
Our conversation dives deep into the "death by a thousand cuts" phenomenon, where seemingly minor inefficiencies in IT workflows accumulate into major productivity drains and significant risks. Shawn breaks down key areas such as provisioning and resource allocation, performance management and monitoring, and refresh cycles, illustrating how traditional approaches often lead to wasted time, increased costs, and security vulnerabilities. He uses compelling analogies, from ride-hailing apps to airplane checklists, to underscore the need for automated, consistent, and intelligent solutions that simplify complex tasks and minimize human error.
We ultimately arrive at a discussion around an autonomous operating environment, where human ingenuity is augmented by machine intelligence to proactively identify and resolve issues, reduce risk, and accelerate time to market. Thought the episode we link to how Pure’s platform approach, including innovations like Pure 1 and Evergreen//One, is transforming the way customers manage their data estate, enabling centralized policy controls, self-service upgrades, and seamless cloud integration.
The Pure Report
In this episode, we welcome Lead Principal Technologist Hari Kannan to cut through the noise and tackle some of the biggest myths surrounding AI data management and the revolutionary FlashBlade//EXA platform. With GPU shipments now outstripping CPUs, the foundation of modern AI is shifting, and legacy storage architectures are struggling to keep up. Hari dives into the implications of this massive GPU consumption, setting the stage for why a new approach is desperately needed for companies driving serious AI initiatives.
Hari dismantles three critical myths that hold IT leaders back. First, he discusses how traditional storage is ill-equipped for modern AI's millions of small, concurrent files, where metadata performance is the true bottleneck—a problem FlashBlade//EXA solves with its metadata-data separation and single namespace. Second, he addresses the outdated notion that high-performance AI is file-only, highlighting FlashBlade//EXA's unified, uncompromising delivery of both file and object storage at exabyte scale and peak efficiency. Finally, Hari explains that GPUs are only as good as the data they consume, countering the belief that only raw horsepower matters. FlashBlade//EXA addresses this by delivering reliable, scalable throughput, efficient DirectFlash Modules up to 300 TB, and the metadata performance required to keep expensive GPUs fully utilized and models training faster.
Join us as we explore the blind spots in current AI data strategies during our "Hot Takes" segment and recount a favorite FlashBlade success story. Hari closes with a compelling summary of how Pure Storage's complete portfolio is perfectly suited to provide the complementary data management essential for scaling AI. Tune in to discover why FlashBlade//EXA is the non-compromise, exabyte-scale solution built to keep your AI infrastructure running at its full potential.
For more information, visit: https://www.pure.ai/flashblade-exa.html
Check out the new Pure Storage digital customer community to join the conversation with peers and Pure experts:
https://purecommunity.purestorage.com/
00:00 Intro and Welcome
04:30 Primer on FlashBlade
11:32 Stat of the Episode on GPU Shipments
13:25 What is FlashBlade//EXA
18:58 Myth #1: Traditional Storage Challenges for AI Data
22:01 Myth #2: AI Workloads are not just File-based
26:42: Myth #3: AI Needs more than just GPUs
31:35 Hot Takes Segment