Disaggregation and Composability vital for AI/DL models to scale

New generations of applications and workloads like AI/DL (Artificial Intelligence/Deep Learning), and HPC (High Performance Computing) are breaking the seams of entrenched storage infrastructure models and frameworks. We cannot continue to scale-up or scale-out the storage infrastructure to meet these inundating fluctuating I/O demands. It is time to look at another storage architecture type of infrastructure technology – Composable Infrastructure Architecture.

Infrastructure is changing. The previous staid infrastructure architecture parts of compute, network and storage have long been thrown of the window, precipitated by the rise of x86 server virtualization almost 20 years now. It triggered a tsunami of virtualizing everything, including storage virtualization, which eventually found a more current nomenclature – Software Defined Storage. Both storage virtualization and software defined storage (SDS) are similar and yet different and should be revered through different contexts and similar goals. This Tech Target article laid out both nicely.

As virtualization raged on, converged infrastructure (CI) which evolved into hyperconverged infrastructure (HCI) went fever pitch for a while. Companies like Maxta, Pivot3, Atlantis, are pretty much gone, with HPE® Simplivity and Cisco® Hyperflex occasionally blipped in my radar. In a market that matured very fast, HCI is now dominated by Nutanix™ and VMware®, with smaller Microsoft®, Dell EMC® following them.

From HCI, the attention of virtualization has shifted something more granular, more scalable in containerization. Despite a degree of complexity, containerization is taking agility and scalability to the next level. Kubernetes, Dockers are now mainstay nomenclature of infrastructure engineers and DevOps. So what is driving composable infrastructure? Have we reached the end of virtualization? Not really.

Evolution of infrastructure. Source: IDC

It is just that one part of the infrastructure landscape is changing. This new generation of AI/ML workloads are flipping the coin to the other side of virtualization. As we see the diagram above, IDC brought this mindset change to get us to Think Composability, the next phase of Infrastructure.

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How well do you know your data and the storage platform that processes the data

Last week was consumed by many conversations on this topic. I was quite jaded, really. Unfortunately many still take a very simplistic view of all the storage technology, or should I say over-marketing of the storage technology. So much so that the end users make incredible assumptions of the benefits of a storage array or software defined storage platform or even cloud storage. And too often caveats of turning on a feature and tuning a configuration to the max are discarded or neglected. Regards for good storage and data management best practices? What’s that?

I share some of my thoughts handling conversations like these and try to set the right expectations rather than overhype a feature or a function in the data storage services.

Complex data networks and the storage services that serve it

I/O Characteristics

Applications and workloads (A&W) read and write from the data storage services platforms. These could be local DAS (direct access storage), network storage arrays in SAN and NAS, and now objects, or from cloud storage services. Regardless of structured or unstructured data, different A&Ws have different behavioural I/O patterns in accessing data from storage. Therefore storage has to be configured at best to match these patterns, so that it can perform optimally for these A&Ws. Without going into deep details, here are a few to think about:

  • Random and Sequential patterns
  • Block sizes of these A&Ws ranging from typically 4K to 1024K.
  • Causal effects of synchronous and asynchronous I/Os to and from the storage

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The burgeoning world of NVMe

When I wrote this article “Let’s smoke this storage peace pipe” 5 years ago, I quoted:

NVMe® and NVM®eF‰, as it evolves, can become the Great Peacemaker and bringing both divides and uniting them into a single storage fabric.

I envisioned NVMe® and NVMe®oF™ setting the equilibrium at the storage architecture level, finishing the great storage fabric into one. This balance in the storage ecosystem at the storage interface specifications and language-protocol level has rapidly unifying storage today, and we are already seeing the end-to-end NVMe paths directly from the PCIe bus of one host to another, via networks over Ethernet (with RoCE, iWARP, and TCP flavours) and Fibre Channel™. Technically we can have an end point device, example a tablet, talking the same NVMe language to its embedded storage as well as a cloud NVMe storage in an exascale storage far, far away. In the past, there were just too many bridges, links, viaducts, aqueducts, bypasses, tunnels, flyovers to cross just to deliver a storage command, or a data in a formats, encased and encoded (and decoded) in so many different ways.

Colours in equilibrium, like the rainbow

Simple basics of NVMe®

SATA (Serial Attached ATA) and SAS (Serial Attached SCSI) are not optimized for solid state devices. besides legacy stuff like AHCI (Advanced Host Controller Interface) in SATA, and archaic SCSI-3 primitives in SAS, NVM® has so much to offer. It can achieve very high bandwidth and support 65,535 I/O queues, each with a queue depth of 65,535. The queue depth alone is a massive jump compared to SAS which has a queue depth limit of 256.

A big part of this is how NVMe® handles I/O processing. It has a submission queue (SQ) and a completion queue (CQ), and together they are know as a Queue Pair (QP). The NVMe® controller handles tens of thousands at I/Os (reads and writes) simultaneously, alerted to switch between each SQ and CQ very quickly using the MSI or MSI-X interrupt. Think of MSI and MSI-X as a service bell, a hardware register that informs the NVM® controller when there are requests in the SQ, and informs the hosts that there are completed requests in the CQ. There will be plenty of “dings” by the MSI-X service register but the NVMe® controller can perform it very well, with some smart interrupt coalescing.

NVMe I/O processing

NVMe® 1.1, as I recalled, used to be have 3 admin commands and 10 base commands, which made it very lightweight compared to SCSI-3. However, newer commands were added to NVMe® 2.0 specifications included command sets fo key-value operations and zoned named space.

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The future of Fibre Channel in the Cloud Era

The world has pretty much settled that hybrid cloud is the way to go for IT infrastructure services today. Straddled between the enterprise data center and the infrastructure-as-a-service in public cloud offerings, hybrid clouds define the storage ecosystems and architecture of choice.

A recent Blocks & Files article, “Broadcom server-storage connectivity sales down but recovery coming” caught my attention. One segment mentioned that the server-storage connectivity sales was down 9% leading me to think “Is this a blip or is it a signal that Fibre Channel, the venerable SAN (storage area network) protocol is on the wane?

Fibre Channel Sign

Thus, I am pondering the position of Fibre Channel SANs in the cloud era. Where does it stand now and in the near future? Continue reading

Storage IO straight to GPU

The parallel processing power of the GPU (Graphics Processing Unit) cannot be denied. One year ago, nVidia® overtook Intel® in market capitalization. And today, they have doubled their market cap lead over Intel®,  [as of July 2, 2021] USD$510.53 billion vs USD$229.19 billion.

Thus it is not surprising that storage architectures are changing from the CPU-centric paradigm to take advantage of the burgeoning prowess of the GPU. And 2 announcements in the storage news in recent weeks have caught my attention – Windows 11 DirectStorage API and nVidia® Magnum IO GPUDirect® Storage.

nVidia GPU

Exciting the gamers

The Windows DirectStorage API feature is only available in Windows 11. It was announced as part of the Xbox® Velocity Architecture last year to take advantage of the high I/O capability of modern day NVMe SSDs. DirectStorage-enabled applications and games have several technologies such as D3D Direct3D decompression/compression algorithm designed for the GPU, and SFS Sampler Feedback Streaming that uses the previous rendered frame results to decide which higher resolution texture frames to be loaded into memory of the GPU and rendered for the real-time gaming experience.

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Memory cloud reality soon?

The original SAN was not always Storage Area Network. SAN had a twin nomenclature called System Area Network (SAN) back in the late 90s. Fibre Channel fabric topology (THE Storage Area Network) was only starting to take off when many of the Fibre Channel topologies at the time were either FC-AL (Fibre Channel Arbitrated Loop) or Point-to-Point. So, for a while SAN was System Area Network, or at least that was what Microsoft® wanted it to be. That SAN obviously did not take off.

System Area Network (architecture shown below) presented a high speed network where server clusters can communicate. The communication protocol of choice was VIA (Virtual Interface Adapter), and the proposed applications, notably the Microsoft® SQL Server, would use Winsock API to interface with the network services. Cache coherency in the combined memory resources of a clustered network is often the technology to ensure data synchronization, consistency and integrity.

Alas, System Area Network did not truly take off, and now it is pretty much deprecated from the Microsoft® universe.

System Area Network (SAN)

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Kubernetes Persistent Storage Managed Well

[ Disclosure: This is a StorPool Storage sponsored blog ]

StorPool Storage – Distributed Storage

There is a rapid adoption of Kubernetes in the enterprise and in the cloud. The push for digital transformation to modernize businesses for a cloud native world in the next decade has lifted both containerized applications and the Kubernetes container orchestration platform to an unprecedented level. The application landscape, especially the enterprise, is looking at Kubernetes to address these key areas:

  • Scale
  • High performance
  • Availability and Resiliency
  • Security and Compliance
  • Controllable Costs
  • Simplified

The Persistent Storage Question

Enterprise applications such as relational databases, email servers, and even the cloud native ones like NoSQL, analytics engines, demand a single data source of truth. Fundamentals properties such as ACID (atomicity, consistency, isolation, durability) and BASE (Basic Availability, Soft State, Eventual Consistency) have to have persistent storage as the foundational repository for the data. And thus, persistent storage have rallied under Container Storage Interface (CSI), and fast becoming a de facto standard for Kubernetes. At last count, there are more than 80 CSI drivers from 60+ storage and cloud vendors, each providing block-level storage to Kubernetes pods.

However, at this juncture, Kubernetes is still very engineering-centric. Persistent storage is equally as challenging, despite all the new developments and hype around it.

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A Paean to NFS

It is certainly encouraging to see both NAS protocols, NFS and SMB, featured well in the latest VMware® vSAN 7 Update 1 release. The NFS v3 and v4.1 support was already in vSAN 7.0 when it was earlier announced as part of its Native File Services for vSAN. But some years ago, NFS was not always the primary storage protocol of choice. SAN protocols, Fibre Channel and iSCSI, were almost always designated to serve enterprise applications. At the client side, Windows became prominent, and the SMB/CIFS protocol dominated the landscape of the desktop. This further pushed NFS into the back closet.

NFS or Network File System has its naysayers. The venerable, but often maligned distributed network file protocol is 36 years today. In storage vendors such as NetApp®, VAST Data, Pure Storage FlashBlade, and Dell EMC Isilon, NFS is still positioned as the primary file protocol for manufacturing testers on the shop floor, EDA/eCAD applications, seismic and subsurface applications in Oil & Gas and many more. In another development, just like its presence in the vSAN Native Services,, NFS has also quietly embedded itself into many storage platforms to serve the data platform services within the respective framework itself.

And I have experienced NFS from the client side to the enterprise applications and more, and I take this opportunity to pay tribute.

NFS (Network File System) client server network

NFS (Network File System) client server network

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Dell EMC Isilon is an Emmy winner!

[ Disclosure: I was invited by GestaltIT as a delegate to their Storage Field Day 19 event from Jan 22-24, 2020 in the Silicon Valley USA. My expenses, travel, accommodation and conference fees were covered by GestaltIT, the organizer and I was not obligated to blog or promote the vendors’ technologies presented at this event. The content of this blog is of my own opinions and views ]

And the Emmy® goes to …

Yes, the Emmy® goes to Dell EMC Isilon! It was indeed a well deserved accolade and an honour!

Dell EMC Isilon had just won the Technology & Engineering Emmy® Awards a week before Storage Field Day 19, for their outstanding pioneering work on the NAS platform tiering technology of media and broadcasting content according to business value.

A lasting true clustered NAS

This is not a blog to praise Isilon but one that instill respect to a real true clustered, scale-out file system. I have known of OneFS for a long time, but never really took the opportunity to really put my hands on it since 2006 (there is a story). So here is a look at history …

Back in early to mid-2000, there was a lot of talks about large scale NAS. There were several players in the nascent scaling NAS market. NetApp was the filer king, with several competitors such as Polyserve, Ibrix, Spinnaker, Panasas and the young upstart Isilon. There were also Procom, BlueArc and NetApp’s predecessor Auspex. By the second half of the 2000 decade, the market consolidated and most of these NAS players were acquired.

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