Don’t get too drunk on Hyper Converged

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).

Gartner MQ Integrated Systems Aug 2015

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 transcendence of Data Fabric

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.

Continue reading

Hail Hydra!

The last of the Storage Field Day 6 on November 7th took me and the other delegates to NEC. There was an obvious, yet eerie silence among everyone about this visit. NEC? Are you kidding me?

NEC isn’t exactly THE exciting storage company in the Silicon Valley, yet I was pleasantly surprised with their HydraStorprowess. It is indeed quite a beast, with published numbers of backup throughput of 4PB/hour, and scales to 100PB of capacity. Most impressive indeed, and HydraStor deserves this blogger’s honourable architectural dissection.

HydraStor is NEC’s grid-based, scale-out storage platform with an object storage backend. The technology, powered by the DynamicStor ™ software, a distributed file system laid over the HydraStor grid architecture. At the same time, it has the DataRedux™ technology that provides the global in-line deduplication as the HydraStor ingests data for data protection, replication, archiving and WORM purposes. It is a massive data consolidation platform, storing gazillion loads of data (100PB you say?) for short-term and long-term retention and recovery.

The architecture is indeed solid, and its data availability goes beyond traditional RAID-level resiliency. HydraStor employs their proprietary erasure coding, called Distributed Resilient Data™. The resiliency knob can be configured to withstand 6 concurrent disks or nodes failure, but by default configured with a resiliency level of 3.

We can quickly deduce that DynamicStor™, DataRedux™ and Distributed Resilient Data™ are the technology pillars of HydraStor. How do they work, and how do they work together?

Let’s look a bit deeper into the HydraStor architecture.

HydraStor is made up of 2 types of nodes:

  • Accelerator Nodes
  • Storage Nodes

The Accelerator Nodes (AN) are the access nodes. They interface with the HydraStor front end, which could be CIFS, NFS or OST (Open Storage Technology). The AN nodes chunks the in-coming data and performs in-line deduplication at a very high speed. It can reach speed of 300TB/hour, which is blazingly fast!

The AN nodes also runs DynamicStor™, handling the performance heavy-lifting portion of HydraStor. The chunked data from the AN nodes are then passed on to the Storage Nodes (SN), where they are further “deduped in-line” to determined if the chunks are unique or not. It is a two-step inline deduplication process. Below is a diagram showing the ANs built above the SNs in the HydraStor grid architecture.

NEC AN & SN grid architecture

 

The HydraStor grid architecture is also a very scalable architecture, allow the dynamic scale-in and scale-out of both ANs and SNs. AN nodes and SN nodes can be added or removed into the system, auto-configuring and auto-optimizing while everything stays online. This capability further strengthens the reliability and the resiliency of the HydraStor.

NEC Hydrastor dynamic topology

Moving on to DataRedux™. DataRedux™ is HydraStor’s global in-line data deduplication technology. It performs dedupe at the sub-file level, with variable length window. This is performed at the AN nodes and the SN nodes level,chunking and creating unique hash values. All unique chunks are further compressed with a modified LZ compression algorithm, shrinking the data to its optimized footprint on the disk storage. To maintain the global in-line deduplication, the hash table is available across the HydraStor cluster.

NEC Deduplication & Compression

The unique data chunk resulting from deduplication and compression are then written to disks using the configured Distributed Resilient Data™ (DRD) algorithm, at its set resiliency level.

At the junction of DRD, with erasure coding parity, the data is broken up into multiples of fragments and assigned a parity to a grouping of fragments. If the resiliency level is set to 3 (the default), the data is broken into 12 pieces, 9 data fragments + 3 parity fragments. The 3 parity fragments corresponds to the resiliency level of 3. See diagram below of the 12 fragments spread across a group of selected disks in the storage pool of the Storage Nodes.

NEC DRD erasure coding on Storage Nodes

 

If the HydraStor experiences a failure in the disks or nodes, and has resulted in the loss of a fragment or fragments, the DRD self-healing function will auto-rebuild and auto-reconfigure the recovered fragments in another set of disks, maintaining the level of 3 parities.

The resiliency level, as mentioned earlier, can be set up to 6, boosting the HydraStor survival factor of 6 disks or nodes failure in the grid. See below of how the autonomous DRD recovery works:

NEC Autonomous Data recovery

Despite lacking the razzle dazzle of most Silicon Valley storage startups and upstarts, credit be given where credit is due. NEC HydraStor is indeed a strong show stopper.

However, in a market that is as fickle as storage, deduplication solutions such as HydraStor, EMC Data Domain, and HP StoreOnce, are being superceded by Copy Data Management technology, touted by Actifio. It was rumoured that EMC restructured their entire BURA (Backup Recovery Archive) division to DPAD (Data Protection and Availability Division) to go after the burgeoning copy data management market.

It would be good if NEC can take notice and turn their HydraStor “supertanker” towards the Copy Data Management market. That would be something special to savour.

P/S: NEC. Sorry about the title. I just couldn’t resist it 😉

Praying to the hypervisor God

I was reading a great article by Frank Denneman about storage intelligence moving up the stack. It was pretty much in line with what I have been observing in the past 18 months or so, about the storage pendulum having swung back to DAS (direct attached storage). To be more precise, the DAS form factor I am referring to are physical server hardware that houses many disk drives.

Like it or not, the hypervisor has become the center of the universe in the IT space. VMware has become the indomitable force in the hypervisor technology, with Microsoft Hyper-V playing catch-up. The seismic shift of these 2 hypervisor technologies are leading storage vendors to place them on to the altar and revering them as deities. The others, with the likes of Xen and KVM, and to lesser extent Solaris Containers aren’t really worth mentioning.

This shift, as the pendulum swings from networked storage back to internal “direct-attached” storage are dictated by 4 main technology factors:

  • The x86 server architecture
  • Software-defined
  • Scale-out architecture
  • Flash-based storage technology

Anyone remember Thumper? Not the Disney character from the Bambi movie!

thumper-bambi-cartoon-character

When the SunFire X4500 (aka Thumper) was first released in (intermission: checking Wiki for the right year) in 2006, I felt that significant wound inflicted in the networked storage industry. Instead of the usual 4-8 hard disk drives in the all the industry servers at the time, the X4500 4U chassis housed 48 hard disk drives. The design and architecture were so astounding to me, I even went and bought a 1U SunFire X4150 for my personal server collection. Such was my adoration for Sun’s technology at the time.

Continue reading

Technology prowess of Riverbed SteelFusion

The Riverbed SteelFusion (aka Granite) impressed me the moment it was introduced to me 2 years ago. I remembered that genius light bulb moment well, in December 2012 to be exact, and it had left its mark on me. Like I said last week in my previous blog, the SteelFusion technology is unique in the industry so far and has differentiated itself from its WAN optimization competitors.

To further understand the ability of Riverbed SteelFusion, a deeper inspection of the technology is essential. I am fortunate to be given the opportunity to learn more about SteelFusion’s technology and here I am, sharing what I have learned.

What does the technology of SteelFusion do?

Riverbed SteelFusion takes SAN volumes from supported storage vendors in the central datacenter and projects the storage volumes (aka LUNs)to applications and hosts at the remote branches. The technology requires a paired relationship between SteelFusion Core (in the centralized datacenter) and SteelFusion Edge (at the branch). Both SteelFusion Core and Edge are fronted respectively by the Riverbed SteelHead WAN optimization device, to deliver the performance required.

The diagram below gives an overview of how the entire SteelFusion network architecture is like:

Riverbed SteelFusion Overall Solution 2 Continue reading

Convergence data strategy should not forget the branches

The word “CONVERGENCE” is boiling over as the IT industry goes gaga over darlings like Simplivity and Nutanix, and the hyper-convergence market. Yet, if we take a step back and remove our emotional attachment from the frenzy, we realize that the application and implementation of hyper-convergence technologies forgot one crucial elementThe other people and the other offices!

ROBOs (remote offices branch offices) are part of the organization, and often they are given the shorter end of the straw. ROBOs are like the family’s black sheeps. You know they are there but there is little mention of them most of the time.

Of course, through the decades, there are efforts to consolidate the organization’s circle to include ROBOs but somehow, technology was lacking. FTP used to be a popular but crude technology that binds the branch offices and the headquarter’s operations and data services. FTP is still used today, in countries where network bandwidth costs a premium. Data cloud services are beginning to appear of part of the organization’s outreaching strategy to include ROBOs but the fear of security weaknesses, data breaches and misuses is always there. Often, concerns of the weaknesses of the cloud overcome whatever bold strategies concocted and designed.

For those organizations in between, WAN acceleration/optimization techonolgy is another option. Companies like Riverbed, Silverpeak, F5 and Ipanema have addressed the ROBOs data strategy market well several years ago, but the demand for greater data consolidation and centralization, tighter and more effective data management and data control to meet the data compliance and data governance requirements, has grown much more sophisticated and advanced. Continue reading

SMB on steroids but CIFS lord isn’t pleased

I admit it!

I am one of the guilty parties who continues to use CIFS (Common Internet File System) to represent the Windows file sharing protocol. And a lot of vendors continue to use the “CIFS” word loosely without knowing that it was a something from a bygone era. One of my friends even pronounced it as “See Fist“, which sounded even funnier when he said it. (This is for you Adrian M!)

And we couldn’t be more wrong because we shouldn’t be using the CIFS word anymore. It is so 90’s man! And the tell-tale signs have already been there but most of us chose to ignore it with gusto. But a recent SNIA Webinar titled “SMB 3.0 – New opportunities for Windows Environment” aims to dispel our incompetence and change our CIFS-venture to the correct word – SMB (Server Message Block).

A selfie photo of Dennis Chapman, Senior Technical Director for Microsoft Solutions at NetApp from the SNIA webinar slides above, wants to inform all of us that … SMB History Continue reading

Xtreme future?

EMC acquisition of XtremIO sent shockwaves across the industry. The news of the acquisition, reported costing EMC USD$430 million can be found here, here and here.

The news of EMC’s would be acquisition a few weeks ago was an open secret and rumour has it that NetApp was eyeing XtremIO as well. Looks like EMC has beaten NetApp to it yet again.

The interesting part was of course, the price. USD$430 million is a very high price to pay for a stealthy, 2-year old company which has 2 rounds of funding totaling USD$25 million. Why such a large amount?

XtremIO has a talented team of engineers; the notable ones being Yaron Segev and Shahar Frank. They have their background in InfiniBand, and Shahar Frank was the chief architect of Exanet scale-out NAS (which was acquired by Dell). However, as quoted by 451Group, XtremeIO is building an all-flash SAN array that “provides consistently high performance, high levels of flash endurance, and advanced functionality around thin provisioning, de-dupe and space-efficient snapshots“.

Furthermore, XtremeIO has developed a real-time inline deduplication engine that does not degrade performance. It does this by spreading the write I/Os over the entire array. There is little information about this deduplication engine, but I bet XtremIO has developed a real-time, inherent deduplication file system that spreads all the I/Os to balance the wear-leveling as well as having scaling performance. I bet XtremIO will dedupe everything that it stores, has a B+ tree, copy-on-write file system with a super-duper efficient hashing algorithm for address mapping (pointers) with this deduplication file system. Ok, ok, I am getting carried away here, because it is likely that I will be wrong, but I can imagine, can’t I? Continue reading

NFO for DFR

It has not caused severe pain yet but it will. Storage is cheap but as capacity grows, it will eventually hit a limit that makes storage difficult to maintain from a cost perspective.

I wrote about the lack of attention of primary storage deduplication solutions in the local industry. Perhaps deduplication has matured to a point that it has become a no-brainer or perhaps customers are already getting sick and tired of the word “dedupe”. Either way, we should not be distracted from the fact that data footprint reduction (DFR) in a generic sense or storage efficiency as a fancy marketing term, must be applied somewhere to slow down the purchase of storage capacity.

Storage is getting fatter, and storage vendors’ revenue is getting fatter along with it. While this is good for the pockets of vendors, the customers have to face higher costs associated with

  • Power, Cooling and Floorspace
  • Administration and management
  • Bandwidth
  • Resource utilization

All these are not prudent storage management practices, because fat storage is bad, just like human beings getting fatter. Similarly, storage must go on a diet and deduplication is one of the few solutions out there. However, I have spoken out that deduplication is just shrinking the container that holds the bits of data, completely unaware of what the content is. Deduplication does not shrink the data itself, and if the occurrence of the data is high, deduplication does not help in reducing the storage capacity. There is no advantage unless the data footprint reduction (DFR) technology is content aware. (Note that I am using DFS as a generic term rather than data deduplication. The reason is obvious.)

That is why data deduplication technologies does not work well with seismic files or encoded video files, because the files are already highly optimized. But there is a technology that can look deeper into such unstructured files and produce storage capacity reduction with specific algorithms for specific type of files and file objects. That technology, I believe, is the truest form of data footprint reduction and it is called Native Format Optimization (NFO).

I want to relate an old story I had experienced when I brought an EMC BURA (Back Up Recovery & Archive – a precursor to its present BRS division) senior manager to see a highly respected technical manager in Schlumberger in Malaysia a few years back. Schlumberger is the world’s largest oilfield services company and provides seismic analysis and interpretation software and seismic files are highly encoded and compressed.

As usual, the senior manager being a typical sales guy started blabbering how great Data Domain (this was just after the EMC acquisition) was, and how it can dedupe any kind of files giving 20:1 (exaggerated to 500:1 to certain text files), even for seismic files. I was signalling to the EMC senior manager to stop his bullsh*t, but he went on and on. In the end, the Schlumberger technical manager politely told the EMC senior manager to shut up, because he has little understand of what seismic files are like.

Now, back to Native Format Optimization (NFO) technology. In a nutshell, NFO plays trick with our human visual system. The goal is to reduce the size of unstructured files without reducing the visual quality of the images (text, texture, colour, resolution, depth, hue, contrast, etc) of the files. 

Have a look at these 2 files. One is optimized with NFO and one is un-optimized. Can you tell the difference?

 

The human visual system is known to be:

  • Less sensitive to high frequency of colour variation
  • More sensitive to brightness than colour variation
  • Less sensitive to background colour in lower resolution
  • More sensitive to a picture’s motion than picture’s texture

Therefore, the eyes perceive an image based on mostly the lowest quality baseline. I got this information from George Crump’s Storage Switzerland’s article.

Because NFO is already in its native form, the files does not need to be rehydrated like deduped files.

The capacity reduction savings is tremendous and because NFO approach is content aware, the benefits translates to higher cost savings in

  • Reduction of power, cooling and floorspace
  • Reduction in data management and administration tasks, especially backup
  • Improved bandwidth and improved disaster recovery
  • Higher performance
  • Delayed storage capacity purchase
  • many more

After Ocarina acquisition by Dell in 2010, a search on the web revealed that probably only one vendor in Europe has boldly continued to enhance NFO technology in their products. The company is balesio and you can read about their NFO technology here.