Huawei Archives - Storage Gaga

Enhancing NAS client resiliency and performance with SMB Multichannel and NFS nconnect

By cfheoh | May 13, 2024 - 7:30 am |May 11, 2024 100Gigabit Ethernet, Azure NetApp Files, CIFS, Clusters, Filesystems, FreeNAS, Gluster, High Performance Computing, Huawei, iXsystems, Linux, Microsoft, Microsoft Azure, NAS, NetApp, NFS, NFS+, pNFS, Pure Storage, Ryuusi, SMB, Software Defined Storage, Storage Optimization, TrueNAS, VMware

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NAS (network attached storage) is obviously the file-level workhorse for shared resources in the network of any organization. SMB (server message block) for Windows environments and NFS (network file system) for Linux platforms are the 2 most prominent protocols that rule the NAS world. Of course we have SMB implementations in the form of Samba and others in non-Windows, Linux and NFS implementations in Windows as well.

As the versions of both network file sharing protocols iterated, present versions of SMB v3.x and NFS v4.x (NFS v3 on the supported Linux kernel version) on the client-side have evolved well. Both now have enhanced resiliency and performance improvement features. And there is an underlying similarity of both implementations. This blog looks at the client-side architectures of both.

One TCP connection

NAS is a client-server architecture. Over the network, NAS clients (SMB or NFS) access their corresponding NAS server(s) – SMB or NFS server(s) – through the TCP/IP network.

NAS client-server architecture (Credit: https://hypertecsp.com/en-CA/knowledge-base/nas-vs-san/)

One very important key starting point to note is the use of one TCP connection per NAS client to the NAS server relationship. For both SMB and NFS, there is just one TCP link between client and the server even if there are several SMB mapped shares or NFS mount points respectively on the clients.

For a long time, this one TCP connection is sufficient for the NAS traffic. But as the network file accesses grow, this connection becomes both a single point of failure as well as a performance bottleneck.

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The prudence needed for storage technology companies

By cfheoh | August 3, 2020 - 9:15 am |August 2, 2020 Acquisition, Actifio, Amazon Web Services, Apple, Blitzscaling, Cloud, Cloudian, Clumio, Cohesity, Data Direct Networks, Datrium, Digital Transformation, Druva, Falconstor, Forrester, Gartner, Google, Huawei, Hyperconvergence, Kaminario, Nasuni, Nutanix, Pure Storage, Qumulo, Rubrik, SolidFire, Tegile, Tintri, Vast Data, Veeam, Veritas, Violin Memory, VMware, WekaIO

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Blitzscaling has been on my mind a lot. Ever since I discovered that word a while back, it has returned time and time again to fill my thoughts. In the wake of COVID-19, and in the mire of this devastating pandemic, is blitzscaling still the right strategy for this generation of storage technology, hyperconverged, data management and cloud storage startups?

What the heck is Blitzscaling?

For the uninformed, here’s a video of Reid Hoffman, co-founder of Linked and a member of the Paypal mafia, explaining Blitzscaling.

Blitzscaling is about hyper growing, scaling ultra fast and rocketing to escape velocity, at the expense of things like management efficiency, financial prudence, profits and others. While this blog focuses on storage companies, blitzscaling is probably most recognizable in the massive expansion of Uber (and contraction) a few years ago. In the US, the ride hailing war is between Uber and Lyft, but over here in South East Asia, just a few years back, it was between Uber and Grab. In China it was Uber and Didi.

From the storage angle, 2 segments exemplified the blitzscaling culture between 2015 and 2020.

All Flash Startups
Hyper Converged Infrastructure Startups

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Is Pure Play Storage good?

By cfheoh | November 13, 2018 - 3:16 am |November 15, 2018 Acquisition, Analytics, Appliance, Artificial Intelligence, Cloud, Cloudian, Cohesity, Data Management, Data Protection, Data Security, Datera, Datrium, Deep Learning, Dell, DellEMC, Drivescale, E8 Storage, EMC, Excelero, Flash, Gartner, Hammerspace, HDS, Hedvig, Hitachi Vantara, Huawei, IBM, Kaminario, NetApp, Nimble Storage, Nutanix, NVMe, Panasas, Promise Technology, Pure Storage, Ryuusi, Scale-out architecture, Server SAN, Software Defined Storage, Software-defined Datacenter, Solid State Devices, Storage Field Day, Storage Market Share, Tech Field Day, Tegile, Tintri, Unified Storage, Violin Memory, WekaIO, XtremIO

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I post storage and cloud related articles to my unofficial SNIA Malaysia Facebook community (you are welcomed to join) every day. It is a community I started over 9 years ago, and there are active live banters of the posts of the day. Casual, personal were the original reasons why I started the community on Facebook rather than on LinkedIn, and I have been curating it religiously for the longest time.

The Big 5 of Storage (it was Big 6 before this)

Looking back 8-9 years ago, the storage vendor landscape of today has not changed much. The Big 5 hegemony is still there, still dominating the Gartner Magic Quadrant for Enterprise and Mid-end Arrays, and is still there in the All-Flash quadrant as well, albeit the presence of Pure Storage in that market.

The Big 5 of today – Dell EMC, NetApp, HPE, IBM and Hitachi Vantara – were the Big 6 of 2009-2010, consisting of EMC, NetApp, Dell, HP, IBM and Hitachi Data Systems. The All-Flash, or Gartner calls it Solid State Arrays (SSA) market was still an afterthought, and Pure Storage was just founded. Pure Storage did not appear in my radar until 2 years later when I blogged about Pure Storage’s presence in the market.

Here’s a look at the Gartner Magic Quadrant for 2010:

We see Pure Play Storage vendors in the likes of EMC, NetApp, Hitachi Data Systems (before they adopted the UCP into their foray), 3PAR, Compellent, Pillar Data Systems, BlueArc, Xiotech, Nexsan, DDN and Infortrend. And when we compare that to the 2017 Magic Quadrant (I have not seen the 2018 one yet) below:

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Huawei Dorado – All about Speed

By cfheoh | April 1, 2018 - 11:18 am |April 1, 2018 Analytics, Appliance, Big Data, Data, Data Fabric, Data Management, Deduplication, Disks, Filesystems, Flash, High Performance Computing, Hitachi Vantara, Huawei, Hyperconvergence, Machine Learning, NetApp, Performance Benchmark, Performance Caching, Reliability, Scale-out architecture, Snapshots, Solid State Devices, Storage Field Day, Storage Optimization, Virtualization

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[Preamble: I was a delegate of Storage Field Day 15 from Mar 7-9, 2018. My expenses, travel and accommodation were paid for by GestaltIT, the organizer and I was not obligated to blog or promote the technologies presented at this event. The content of this blog is of my own opinions and views]

Since Storage Field Day 15 3 weeks ago, the thoughts of the session with Huawei lingered. And one word came to describe Huawei Dorado V3, their flagship All-Flash storage platform is SPEED.

My conversation with Huawei actually started the night before our planned session at their Santa Clara facility the next day. We had a evening get-together at Bourbon Levi’s Stadium. I was with my buddy, Ammar Zolkipli, who coincidentally was in the Silicon Valley for work. Ammar is from Hitachi Vantara Japan, and has been a good friend of mine for over 17 years now.

Shortly, the Huawei team arrived to join the camaraderie. And we introduced ourselves to Chun Liu, not knowing that he is the Chief Architect at Huawei. A big part of that evening was our conversation with him. Ammar and I have immersed in the Oil & Gas EP (Exploration & Production) data management and petrotechnical applications when he was in Schlumberger and after that a reseller of NetApp. I was a Consulting Engineer with NetApp back then. So, the 2 of us started blabbering (yeah, that would be us when we get together to talk technology).

I observed that Chun was very interested to find learn about real world application use cases that would push storage performance to its limits. And I guessed that the best type of I/O characteristics would be small block, random I/O and billions of them, with near-real time latency. After that evening I did some research and could only think of a few, such as deep analytics or some applications with needs for Monte Carlo simulations. Oh, well, maybe I would share that with Chun the following day.

The moment the session started, it was already about the speed prowess of Huawei Storage. It was like the greyhounds unleashed going after the rabbit. In the lineup, the Dorado series stood out.

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Category Archives: Huawei