Time to Conflate Storage with Data Services

Around the year 2016, I started to put together a better structure to explain storage infrastructure. I started using the word Data Services Platform before what it is today. And I formed a pictorial scaffold to depict what I wanted to share. This was what I made at that time.

Data Services Platform (circa 2016)- Copyright Heoh Chin Fah

One of the reasons I am bringing this up again is many of the end users and resellers still look at storage from the perspective of capacity, performance and price. And as if two plus two equals five, many storage pre-sales and architects reciprocate with the same type of responses that led to the deteriorated views of the storage technology infrastructure industry as a whole. This situation irks me. A lot.

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Rethinking data processing frameworks systems in real time

“Row, row, row your boat, gently down the stream…”

Except the stream isn’t gentle at all in the data processing’s new context.

For many of us in the storage infrastructure and data management world, the well known framework is storing and retrieve data from a storage media. That media could be a disk-based storage array, a tape, or some cloud storage where the storage media is abstracted from the users and the applications. The model of post processing the data after the data has safely and persistently stored on that media is a well understood and a mature one. Users, applications and workloads (A&W) process this data in its resting phase, retrieve it, work on it, and write it back to the resting phase again.

There is another model of data processing that has been bubbling over the years and now reaching a boiling point. Still it has not reached its apex yet. This is processing the data in flight, while it is still flowing as it passes through processing engine. The nature of this kind of data is described in one 2018 conference I chanced upon a year ago.

letgo marketplace processing numbers in 2018

  • * NRT = near real time

From a storage technology infrastructure perspective, this kind of data processing piqued my curiosity immensely. And I have been studying this burgeoning new data processing model in my spare time, and where it fits, bringing the understanding back into the storage infrastructure and data management side.

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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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At the mercy of the cloud deity

Amazon Web Services (AWS) went down in the middle of last week. News of the outage were mentioned:

AWS Management Console unavailable error

Piling the misery

The AWS outage headlines attract the naysayers, the fickle armchair pundits, and the opportunists. Here are a few news articles that bring these folks to chastise the cloud giant.

Of course, I am one of these critics. I don’t deny that I am not. But I read this situation from a multicloud hyperbole of which I am not a fan. Too much multicloud whitewashing by vendors trying to pitch multicloud as a disaster recovery solution without understanding that this is easier said than done.

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Storage Elephant Compute Birds

Data movement is expensive. Not just costs, but also latency and resources as well. Thus there were many narratives to move compute closer to where the data is stored because moving compute is definitely more economical than moving data. I borrowed the analogy of the 2 animals from some old NetApp® slides which depicted storage as the elephant, and compute as birds. It was the perfect analogy, because the storage is heavy and compute is light.

“Close up of a white Great Egret perching on top of an African Elephant aa Amboseli national park, Kenya”

Before the animals representation came about I used to use the term “Data locality, Data Mobility“, because of past work on storage technology in the Oil & Gas subsurface data management pipeline.

Take stock of your data movement

I had recent conversations with an end user who has been paying a lot of dollars keeping their “backup” and “archive” in AWS Glacier. The S3 storage is cheap enough to hold several petabytes of data for years, because the IT folks said that the data in AWS Glacier are for “backup” and “archive”. I put both words in quotes because they were termed as “backup” and “archive” because of their enterprise practice. However, the face of their business is changing. They are in manufacturing, oil and gas downstream, and the definitions of “backup” and “archive” data has changed.

For one, there is a strong demand for reusing the past data for various reasons and these datasets have to be recalled from their cloud storage. Secondly, their data movement activities still mimicked what they did in the past during their enterprise storage days. It was a classic lift-and-shift when they moved to the cloud, and not taking stock of  their data movements and the operations they ran on these datasets. Still ongoing, their monthly AWS cost a bomb.

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Control your Files. Control your Sovereignty.

Data residency, data sovereignty, data localization – the trio of data compliance and governance – have been on my mind a lot lately. I am seeing a disturbing trend. “Splinternet” has taken a hurried and hastened pace. We are now seeing many countries drawing up digital boundaries in the name of data privacy and data protection with sovereign laws and regulations. Besides, these digital demarcation along the lines with data definitions, digital “colonization” is a strong undercurrent as developing countries are accepting larger and more powerful foreign powers into their playpen.

Public cloud services transcend national borders. The breakneck speed in the adoption of public cloud services is causing anxieties and concerns with conservative governments everywhere. On the flip side of the coin, commerce has certainly flourished and bloomed as global wide collaborations bring new opportunities, new markets – all for capitalism and growth.

[ Note: While we are on this debacle, the voices of decentralization are getting louder as well, but that is a topic for another day ]

Where are your data files now?

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What happened to NDMP?

The acronym NDMP shows up once in a while in NAS (Network Attached Storage) upgrade tenders. And for the less informed, NDMP (Network Data Management Protocol) was one of the early NAS data management (more like data mover specifications) initiatives to backup NAS devices, especially the NAS appliances that run proprietary operating systems code.

NDMP Logo

Backup software vendors often have agents developed specifically for an operating system or an operating environment. But back in the mid-1990s, 2000s, the internal file structures of these proprietary vendors were less exposed, making it harder for backup vendors to develop agents for them. Furthermore, there was a need to simplify the data movements of NAS files between backup servers and the NAS as a client, to the media servers and eventually to the tape or disk targets. The dominant network at the time ran at 100Mbits/sec.

To overcome this, Network Appliance® and PDC Solutions/Legato® developed the NDMP protocol, allowing proprietary NAS devices to run a standardized client-server architecture with the NDMP server daemon in the NAS and the backup service running as an NDMP client. Here is a simplified look at the NDMP architecture.

NDMP Client-Server Architecture

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The Starbucks model for Storage-as-a-Service

Starbucks™ is not a coffee shop. It purveys beyond coffee and tea, and food and puts together the yuppie beverages experience. The intention is to get the customers to stay as long as they can, and keep purchasing the Starbucks’ smorgasbord of high margin provisions in volume. Wifi, ambience, status, coffee or tea with your name on it (plenty of jokes and meme there), energetic baristas and servers, fancy coffee roasts and beans et. al. All part of the Starbucks™-as-a-Service pleasurable affair that intends to lock the customer in and have them keep coming back.

The Starbucks experience

Data is heavy and they know it

Unlike compute and network infrastructures, storage infrastructures holds data persistently and permanently. Data has to land on a piece of storage medium. Coupled that with the fact that data is heavy, forever growing and data has gravity, you have a perfect recipe for lock-in. All storage purveyors, whether they are on-premises data center enterprise storage or public cloud storage, and in between, there are many, many methods to keep the data chained to a storage technology or a storage service for a long time. The storage-as-a-service is like tying the cow to the stake and keeps on milking it. This business model is very sticky. This stickiness is also a lock-in mechanism.

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Don’t go to the Clouds. Come back!

Almost in tandem last week, Nutanix™ and HPE appeared to have made denigrated comments about Cloud First mandates of many organizations today. Nutanix™ took to the annual .NEXT conference to send the message that cloud is wasteful. HPE campaigned against a UK Public Sector “Cloud First” policy.

Cloud First or Cloud Not First

The anti-cloud first messaging sounded a bit funny and hypocritical when both companies have a foot in public clouds, advocating many of their customers in the clouds. So what gives?

That A16Z report

For a numbers of years, many fear criticizing the public cloud services openly. For me, there are the 3 C bombs in public clouds.

  • Costs
  • Complexity
  • Control (lack of it)

Yeah, we would hear of a few mini heart attacks here and there about clouds overcharging customers, and security fallouts. But vendors then who were looking up to the big 3 public clouds as deities, rarely chastise them for the errors. Until recently.

The Cost of Cloud, a Trillion Dollar Paradox” released by revered VC firm Andreessen Horowitz in May 2021 opened up the vocals of several vendors who are now emboldened to make stronger comments about the shortcomings of public cloud services. The report has made it evident that public cloud services are not panacea of all IT woes.

The report has made it evident that public cloud services are not panacea of all IT woes. And looking at the trends, this will only get louder.

Use ours first. We are better

It is pretty obvious that both Nutanix™ and HPE have bigger stakes outside the public cloud IaaS (infrastructure-as-a-service) offerings. It is also pretty obvious that both are not the biggest players in this cloud-first economy. Given their weights in the respective markets, they are leveraging their positions to swing the mindsets to their turf where they can win.

“Use our technology and services. We are better, even though we are also in the public clouds.”

Not a zero sum game

But IT services and IT technologies are not a zero sum game. Both on-premises IT services and complementary public cloud services can co-exist. Both can leverage on each other’s strengths and support each other’s weaknesses, if you know how to blend and assimilate the best of both worlds. Hybrid cloud is the new black.

Gartner Hype Cycle

The IT pendulum swings. Technology hype goes fever pitch. Everyone thinks there is a cure for cancer. Reality sets in. They realize that they were wrong (not completely) or right (not completely). Life goes on. The Gartner® Hype Cycle explains this very well.

The cloud is OK

There are many merits having IT services provisioned in the cloud. Agility, pay-per-use, OPEX, burst traffic, seemingly unlimited resources and so. You can read more about it at Benefits of Cloud Computing: The pros and cons. Even AWS agrees to Three things every business needs from hybrid cloud, perhaps to the chagrin of these naysayers.

I opined that there is no single solution for everything. There is no Best Storage Technology Ever (a snarky post). And so, I believe there is nothing wrong of Nutanix™ and HPE, and maybe others, being hypocritical of their cloud and non-cloud technology offerings. These companies are adjusting and adapting to the changing landscapes of the IT environments, but it is best not to confuse the customers what tactics, strategy and vision are. Inconsistencies in messaging diminishes trust.

 

 

What the heck is Storage Modernization?

We often hear the word “modernization” thrown around these days. The push is to get the end user to refresh their infrastructure, and the storage infrastructure market is rife with modernization word. Is your storage ripe for “modernization“?

Many possibilities to modernize storage

To modernize, it has to be relative to legacy storage hardware, and the operating environment that came with it. But if the so-called “legacy” still does the job, should you modernize?

Big Data is right

When the word “Big Data” came into prominence a while back, it stirred the IT industry into a frenzy. At one point, Apache Hadoop became the poster elephant (pun intended) for this exciting new segment. So many Vs came out, but I settled with 4 Vs as the framework of my IT conversations. The 4Vs we often hear are:

  • Volume
  • Velocity
  • Variety
  • Veracity

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