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I didn’t get a chance to attend Pure Accelerate event last month. From the blogs and tweets of my friends, Pure Accelerate was an awesome event. When I got the email invitation for the localized Pure Live! event in Kuala Lumpur, I told myself that I have to attend the event.
The event was yesterday, and I was not disappointed. Coming off a strong fiscal Q1 2018, it has appeared that Pure Storage has gotten many things together, chugging full steam at all fronts.
When Pure Storage first come out, I was one of the early bloggers who took a fancy of them. My 2011 blog mentioned the storage luminaries in their team. Since then, they have come a long way. And it was apt that on the same morning yesterday, the latest Gartner Magic Quadrant for Solid State Arrays 2017 was released.
I have known of RDMA (Remote Direct Memory Access) for quite some time, but never in depth. But since my contract work ended last week, and I have some time off to do some personal development, I decided to look deeper into RDMA. Why RDMA?
In the past 1 year or so, RDMA has been appearing in my radar very frequently, and rightly so. The speedy development and adoption of NVMe (Non-Volatile Memory Express) have pushed All Flash Arrays into the next level. This pushes the I/O and the throughput performance bottlenecks away from the NVMe storage medium into the legacy world of SCSI.
Most network storage interfaces and protocols like SAS, SATA, iSCSI, Fibre Channel today still carry SCSI loads and would have to translate between NVMe and SCSI. NVMe-to-SCSI bridges have to be present to facilitate the translation.
In the slide below, shared at the Flash Memory Summit, there were numerous red boxes which laid out the SCSI connections and interfaces where SCSI-to-NVMe translation (and vice versa) would be required.
[Preamble: I was a delegate of Storage Field Day 12. My expenses, travel and accommodation were paid for by GestaltIT, the organizer and I was not obligated to blog or promote the technologies presented in this event]
When it comes to large scale storage capacity requirements with distributed cloud and on-premise capability, object storage is all the rage. Amazon Web Services started the object-based S3 storage service more than a decade ago, and the romance with object storage started.
Today, there are hundreds of object-based storage vendors out there, touting features after features of invincibility. But after researching and reading through many design and architecture papers, I found that many object-based storage technology vendors began to sound the same.
At the back of my mind, object storage is not easy when it comes to most applications integration. Yes, there is a new breed of cloud-based applications with RESTful CRUD API operations to access object storage, but most applications still rely on file systems to access storage for capacity, performance and protection.
These CRUD and CRUD-like APIs are the common semantics of interfacing object storage platforms. But many, many real-world applications do not have the object semantics to interface with storage. They are mostly designed to interface and interact with file systems, and secretly, I believe many application developers and users want a file system interface to storage. It does not matter if the storage is on-premise or in the cloud.
Let’s not kid ourselves. We are most natural when we work with files and folders.
Implementing object storage also denies us the ability to optimally utilize Flash and solid state storage on-premise when the compute is in the cloud. Similarly, when the compute is on-premise and the flash-based object storage is in the cloud, you get a mismatch of performance and availability requirements as well. In the end, there has to be a compromise.
Another “feature” of object storage is its poor ability to handle transactional data. Most of the object storage do not allow modification of data once the object has been created. Putting a NAS front (aka a NAS gateway) does not take away the fact that it is still object-based storage at the very core of the infrastructure, regardless if it is on-premise or in the cloud.
Resiliency, latency and scalability are the greatest challenges when we want to build a true globally distributed storage or data services platform. Object storage can be resilient and it can scale, but it has to compromise performance and latency to be so. And managing object storage will not be as natural as to managing a file system with folders and files.
The flash frenzy has reached its zenith in 2016. We now no longer are interested in listening to storage technology vendors touting the power of solid state storage (NAND Flash included) over spinning drives.
The capacity of 3D NAND Flash SSDs has reached a whopping 15.3TB (that is even bigger than the 12TB 7200RPM HDDs of today), and with deduplication and compression, the storage efficiency has reached a conservative 4:1 or 5:1. Effective capacity of most mid-end storage arrays can easily reach 1-2 Petabytes.
And flash and hybrid platforms have reached maturity in these few short years. So what is next?
The landscape has obviously changed. The performance landscape, the capacity landscape and all related to the storage data points have changed. And the speed of SSDs together with the up-and-coming NVMe and NVDIMM technology in new storage array controllers are also shifting the data bottlenecks to another part of the architecture. The development of I/O communications and interfaces has to change as well, to take advantage of the asynchronous I/Os in storage tiering and caching using NAND Flash.
With this mature and well understood landscape, it is time to take Flash to the next level. This next level comes in the form of an exciting end-user conference in Singapore on 25th April 2017. It is called FlashForward.
The 2016 FlashForward event in Europe has already garnered great support from the cream of the storage technologists around the world, and had fantastic feedbacks from the end-user attendees. That FlashForward event has also seen the birth of an international business and technology exchange in its inaugural introduction. Yes, it is time to learn from the field experts, and it is time to build on the Flash Platform for new Data Services.
From the sponsorship package brochure I have received, it is definitely an event not to be missed.
The FlashForward Conference in Singapore is exquisitely procured by Evito Ltd, under the stewardship of Mr. Paul Talbut. Paul is a very seasoned veteran in the global circuit as an SNIA director of several initiatives. He has been immensely involved in the development of several SNIA chapters around the world, including South Asia, Malaysia, India, China, and even Brazil. He also leads by example with the SNIA Global Steering Committee (GSC); he is the SNIA Global Education Director and at one time, SNIA DPCO (Data Protection & Capacity Optimization) global proctor.
I have had the honour working with Paul for almost 8 years now, and I am sure he will lead the FlashForward Conference with valuable insights and experiences.
This is probably the greatest period for the industry and end users to get involved in the FlashForward Conference. For one, it is endorsed by SNIA, the vendor-neutral association which has been the growth beacon of the storage networking industry.
Secondly, it is the perfect opportunity for technology vendors to build their mindshare with end users and customers. And with the endorsement of the independent field experts and technology practitioners, end users would have a field day garnering approvals for their decisions, as well as learning the best practices to build upon the Flash technology they have implemented in their data center space.
The sponsorship packages are listed below, and I do encourage technology vendors, especially the All-Flash vendors to use the FlashForward conference as a platform to build their mindshare, and most of all, their branding. Continue reading
NVMe (Non-Volatile Memory Express) is upon us. And in the next 2-3 years, we will see a slew of new storage solutions and technology based on NVMe.
Just a few days ago, The Register released an article “Seventeen hopefuls fight for the NVMe Fabric array crown“, and it was timely. I, for one, cannot be more excited about the development and advancement of NVMe and the upcoming NVMeF (NVMe over Fabrics).
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.