This is it. This is the one that will end the wars of DAS, NAS and SAN and unite the warring factions between server-based SAN (the sexy name differentiating old DAS and new DAS) and the networked storage of SAN and NAS. There will be PEACE.
Nutanix popularized the “No SAN” movement which later led to VMware VSAN and other server-based SAN solutions, hyperconverged techs such as PernixData (acquired by Nutanix), DataCore, EMC ScaleIO and also operated in hyperscalers – the likes of Facebook and Google. The hyperconverged solutions and the server-based SAN lines blurred of storage but still, they are not the usual networked storage architectures of SAN and NAS. I blogged about this, mentioning about how the pendulum has swung back to favour DAS, or to put it more appropriately, server-based SAN. There was always a “Great Divide” between the 2 modes of storage architectures. Continue reading →
I am guilty. I have not been tendering this blog for quite a while now, but it feels good to be back. What have I been doing? Since leaving NetApp 2 months or so ago, I have been active in the scenes again. This time I am more aligned towards data analytics and its burgeoning impact on the storage networking segment.
I was intrigued by an article posted by a friend of mine in Facebook. The article (circa 2013) was titled “Never, ever do this to Hadoop”. It described the author’s gripe with the SAN bigots. I have encountered storage professionals who throw in the SAN solution every time, because that was all they know. NAS, to them, was like that old relative smelled of camphor oil and they avoid NAS like a plague. Similar DAS was frowned upon but how things have changed. The pendulum has swung back to DAS and new market segments such as VSANs and Hyper Converged platforms have been dominating the scene in the past 2 years. I highlighted this in my blog, “Praying to the Hypervisor God” almost 2 years ago.
I agree with the author, Andrew C. Oliver. The “locality” of resources is central to Hadoop’s performance.
Consider these 2 models:
In the model on your left (Moving Data to Compute), the delivery process from Storage to Compute is HEAVY. That is because data has dependencies; data has gravity. However, if you consider the model on your right (Moving Compute to Data), delivering data processing to the storage layer is much lighter. Compute or data processing is transient, and the data in the compute layer is volatile. Once compute’s power is turned off, everything starts again from a clean slate, hence the volatile stage.
PREFACE: This is just a thought, an idea. I am by no means an expert in this area. I have researched this to inspire a thought process of how we can bring together 2 disparate worlds of medical records and imaging with the emerging cloud services for healthcare.
Healthcare has been moving out of its archaic shell in the past few years, and digital healthcare technology and services are booming. And this movement is part of the digital transformation which could eventually lead to a secure and compliant distribution and collaboration of health data, medical imaging and electronic medical records (EMR).
December 22 2015: I kept this blog in draft for 6 months. Now I am releasing it as NetApp acquires Solidfire.
The above is an old Chinese adage which means “True Gold fears no Fire“. That is how I would describe my revisited view and assessment of SolidFire, a high performance All-Flash array vendor which is starting to make its presence felt in South Asia.
I first blogged about SolidFire 3 years ago, and I have been following the company closely as more and more All-Flash array players entered the market over the 3 years. Many rode on the hype and momentum of flash storage, and as a result, muddied and convoluted the storage infrastructure market understanding. It seems to me spin marketing ruled the day and users could not make a difference between vendor A and vendor B, and C and D, and so on….
I have been often asked, which is the best All-Flash array today. I have always hesitated to say which is the best because there aren’t much to say, except for 2-3 well entrenched vendors. Pure Storage and EMC XtremIO come to mind but the one that had stayed under the enterprise storage radar was SolidFire, until now.
A recent report intrigued me. Given the recent uprising of data, data and more data, things are getting a bit absurd about the voluminous data we are collecting and storing. The flip is that we might need all these data for analytics and getting more insight from the data.
The Veritas Darkberg report revealed that a very large percentage of the data collected and stored by organizations are useless data, unknown and unused. I captured a snapshot of the report below:
From the screenshot above, it shows 54% of the landscape surveyed is dark data, unseen and clogging up the storage. And in an instance, the Darkberg (cross of “Dark” and “Iceberg”) report knocked a lot of sense into this whole data acquisition frenzy we are going through right now.
I am so blind. After more than 20 years in the industry, I have chosen to be blind to one of the most important elements of data protection and availability. Yet, I have been talking about it over and over, and over again but never really incorporated it into mantra.
Some readers will know that I frequently use these 7 points (or elements) in my approach to storage infrastructure and information management. These are:
A few days ago, I had an epiphany. I woke up in the morning, feeling so enlightened and yet conflicted with the dumbfounded dumb feeling. It was so weird, and that moment continued to play in my mind like a broken record. I had to let it out and hence I am writing this down now.
Element R – Recovery, Resiliency, Restorability, Resumption. That’s the element which I “discovered“. I was positively stunned that I never incorporated such an important element in my mantra, until now. Continue reading →
I hate the fact that I am bursting the big bubble brewing about Hyper Convergence (HC). I urge all to look past the hot air and hype frenzy that are going on, because in the end, the HC platforms have to be aligned and congruent to the organization’s data architecture and business plans.
The announcement of Gartner’s latest Magic Quadrant on Integrated Systems (read hyper convergence) has put Nutanix as the leader of the pack as of August 2015. Clearly, many of us get caught up because it is the “greatest feeling in the world”. However, this faux feeling is not reality because there are many factors that made the pack leaders in the Magic Quadrant (MQ).
First of all, the MQ is about market perception. There is no doubt that the pack leaders in the Leaders Quadrant have earned their right to be there. Each company’s revenue, market share, gross margin, company’s profitability have helped put each as leaders in the pack. However, it is also measured by branding, marketing, market perception and acceptance and other intangible factors.
Secondly, VMware EVO: Rail has split the market when EMC has 3 HC solutions in VCE, ScaleIO and EVO: Rail. Cisco wanted to do their own HC piece in Whiptail (between the 2014 MQ and 2015 MQ reports), and closed down Whiptail when their new CEO came on board. NetApp chose EVO: Rail and also has the ever popular FlexPod. That is why you see that in this latest MQ report, NetApp and Cisco are interpreted independently whereas in last year’s report, it was Cisco/NetApp. Market forces changed, and perception changed. Continue reading →
The Register wrote a damning piece about NetApp a few days ago. I felt it was irresponsible because this is akin to kicking a man when he’s down. It is easy to do that. The writer is clearly missing the forest for the trees. He was targeting NetApp’s Clustered Data ONTAP (cDOT) and missing the entire philosophy of NetApp’s mission and vision in Data Fabric.
I have always been a strong believer that you must treat Data like water. Just like what Jeff Goldblum famously quoted in Jurassic Park, “Life finds a way“, data as it moves through its lifecycle, will find its way into the cloud and back.
And every storage vendor today has a cloud story to tell. It is exciting to listen to everyone sharing their cloud story. Cloud makes sense when it addresses different workloads such as the sharing of folders across multiple devices, backup and archiving data to the cloud, tiering to the cloud, and the different cloud service models of IaaS, PaaS, SaaS and XaaS.
A catchy email from one of the forums I subscribed to, caught my attention. It goes something like “…Grateful … Disk is Dead“. Here the blog from Kevin Doherty, a Senior Account Manager at Violin Memory.
Coming from Violin Memory, this is pretty obvious because they have an agenda against HDDs. They don’t use any disks at all …. in any form factor. They use VIMMs (Violin Inline Memory Modules), something no vendor in the industry use today.
I recalled my blog in 2012, titled “Violin pulling the strings“. It came up here in South Asia with much fan fare, lots of razzmatazz and there was plenty of excitement. I was even invited to their product training at Ingram Micro in Singapore and met their early SE, Mike Thompson. Mike is still there I believe, but the EMC veteran in Singapore whom I mentioned in my previous blog, left almost a year later after joining. So was the ex-Sun, General Manager of Violin Memory in Singapore.
It is the morning that the SNIA Global Steering Committee reporting session is starting soon. I am in the office extremely early waiting for my turn to share the happenings in SNIA Malaysia.
And of late, I have been getting a lot of calls to catch up on hot technologies, notably All Flash Storage arrays and hyper-converged infrastructure. Even though I am now working for Interica, a company that focuses on Oil & Gas exploration and production software, my free coffee sessions with folks from the IT side have not diminished. And I recalled a week back in mid-March where I had coffee overdose!
Flash storage and hyperconvergence are HOT! Despite the hypes and frenzies of both flash storage and hyperconvergence, I still believe that integrating either or, or both, still have an effect that many IT managers overlook. The effect is a data silo.