Object Storage becoming storage lingua franca of Edge-Core-Cloud

Data Fabric was a big buzzword going back several years. I wrote a piece talking about Data Fabric, mostly NetApp®’s,  almost 7 years ago, which I titled “The Transcendence of Data Fabric“. Regardless of storage brands and technology platforms, and each has its own version and interpretations, one thing holds true. There must be a one layer of Data Singularity. But this is easier said than done.

Fast forward to present. The latest buzzword is Edge-to-Core-Cloud or Cloud-to-Core-Edge. The proliferation of Cloud Computing services, has spawned beyond to multiclouds, superclouds and of course, to Edge Computing. Data is reaching to so many premises everywhere, and like water, data has found its way.

Edge-to-Core-to-Cloud (Gratitude thanks to https://www.techtalkthai.com/dell-technologies-opens-iot-solutions-division-and-introduces-distributed-core-architecture/)

The question on my mind is can we have a single storage platform to serve the Edge-to-Core-to-Cloud paradigm? Is there a storage technology which can be the seamless singularity of data? 7+ years onwards since my Data Fabric blog, The answer is obvious. Object Storage.

The ubiquitous object storage and the S3 access protocol

For a storage technology that was initially labeled “cheap and deep”, object storage has become immensely popular with developers, cloud storage providers and is fast becoming storage repositories for data connectors. I wrote a piece called “All the Sources and Sinks going to Object Storage” over a month back, which aptly articulate how far this technology has come.

But unknown to many (Google NASD and little is found), object storage started its presence in SNIA (it was developed in Carnegie-Mellon University prior to that) in the early 90s, then known as NASD (network attached secure disk). As it is made its way into the ANSI T10 INCITS standards development, it became known as Object-based Storage Device or OSD.

The introduction of object storage services 16+ years ago by Amazon Web Services (AWS) via their Simple Storage Services (S3) further strengthened the march of object storage, solidified its status as a top tier storage platform. It was to AWS’ genius to put the REST API over HTTP/HTTPS with its game changing approach to use CRUD (create, retrieve, update, delete) operations to work with object storage. Hence the S3 protocol, which has become the de facto access protocol to object storage.

Yes, I wrote those 2 blogs 11 and 9 years ago respectively because I saw that object storage technology was a natural fit to the burgeoning new world of storage computing. It has since come true many times over.

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Ridding consumer storage mindset for Enterprise operations

I cut my teeth in Enterprise Storage for 3 decades. On and off, I get the opportunity to work on Cloud Storage as well, mostly more structured storage infrastructure services such as blocks and files, in cloud offerings on AWS, Azure and Alibaba Cloud. I am familiar with S3 operations (mostly the CRUD operations and HTTP headers stuff) too, although I have yet to go deep with S3 with Restful API. And I really wanted to work on stuff with the S3 Select when the opportunity arises. (Note: Homelab project to-do list)

Along with the experience is the enterprise mindset of designing and crafting storage infrastructure and data management practices that evolve around data. Understanding the characteristics of data and the behaviours data in motion is part of my skills repertoire, and I continue to have conversations with organizations, small and large alike every day of the week.

This week’s blog was triggered by an article by Tech Republic® Jack Wallen‘s interview with Fedora project leader Matthew Miller. I have been craning my neck waiting for the full release of Fedora 36 (which now has been pushed to May 10th 2022), and the Tech Republic®’s article, “The future of Linux: Fedora project leader weighs in” touched me. Let me set the context of my expanded commentaries here.

History of my open source experience- bringing Enterprise to the individual

I have been working with open source software for a long time. My first Linux experience was Soft Landing Linux in the early 90s. It was a bunch of diskettes I purchased online while dabbling with FreeBSD® on the sides. Even though my day job was on the SunOS, and later Solaris®, having the opportunity to build stuff and learn the enterprise ways with Sun Microsystems® hardware and software were difficult at my homelab. I did bring home a SPARCstation® 2 once but the CRT monitor almost broke my computer table at that time.

Having open source software on 386i (before x86) architecture was great (no matter how buggy they were) because I got to learn hardcore enterprise technology at home. I am a command line person, so the desktop experience does not bother me much because my OS foundation is there. Open source gave me a world I could master my skills as an individual. For an individual like me, my mindset is always on the Enterprise.

The Tech Republic interview and my reflections

I know the journey open source OSes has taken at the server (aka Enterprise) level. They are great, and are getting better and better. But at the desktop (aka consumer) level, the Linux desktop experience has been an arduous one even though the open source Linux desktop experience is so much better now. This interview reflected on that.

There were a few significant points that were brought up. Those poignant moments explained about the free software in open source projects, how consumers glazed over (if I get what Matt Miller meant) the cosmetics of the open source software without the deeper meaningful objectives of the software had me feeling empty. Many assumed that just because the software is open source, it should be free or of low costs and continue to apply a consumer mindset to the delivery and the capability of the software.

Case in point is the way I have been seeing many TrueNAS®/FreeNAS™ individuals who downloaded the free software and using them in consumer ways. That is perfectly fine but when they want to migrate their consumer experience with the TrueNAS® software to their critical business operations, things suddenly do not look so rosy anymore. From my experience, having built enterprise-grade storage solutions with open source software like ZFS on OpenSolaris/OpenIndiana, FreeNAS™ and TrueNAS® for over a decade plus gaining plenty of experience on many proprietary and software-defined storage platforms along this 30 year career, the consumer mindsets do not work well in enterprise missions.

And over the years, I have been seeing this newer generation of infrastructure people taking less and less interest in learning the enterprise ways or going deep dive into the workings of the open source platforms I have mentioned. Yet, they have lofty enterprise expectations while carrying a consumer mindset. More and more, I am seeing a greying crew of storage practitioners with enterprise experiences dealing with a new generation of organizations and end users with consumer practices and mindsets.

Open Source Word Cloud

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All the Sources and Sinks going to Object Storage

The vocabulary of sources and sinks are beginning to appear in the world of data storage as we witness the new addition of data processing frameworks and the applications in this space. I wrote about this in my blog “Rethinking data. processing frameworks systems in real time” a few months ago, introducing my take on this budding new set of I/O characteristics and data ecosystem. I also started learning about the Kappa Architecture (and Lambda as well), a framework designed to craft and develop a set of amalgamated technologies to handle stream processing of a series of data in relation to time.

In Computer Science, sources and sinks are considered external entities that often serve as connectors of input and output of disparate systems. They are often not in the purview of data storage architects. Also often, these sources and sinks are viewed as black boxes, and their inner workings are hidden from the views of the data storage architects.

Diagram from https://developer.here.com/documentation/get-started/dev_guide/shared_content/topics/olp/concepts/pipelines.html

The changing facade of data stream processing presents the constant motion of data, the continuous data being altered as it passes through the many integrated sources and sinks. We are also see much of the data processed in-memory as much as possible. Thus, the data services from a traditional storage model of SAN and NAS may straggle with the requirements demanded by this new generation of data stream processing.

As the world of traditional data storage processing is expanding into data streams processing and vice versa, and the chatter of sources and sinks can no longer be ignored.

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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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Celebrating MinIO

Essentially MinIO is a web server …

I vaguely recalled Anand Babu Periasamy (AB as he is known), the CEO of MinIO saying that when I first met him in 2017. I was fresh “playing around” with MinIO and instantly I fell in love with software technology. Wait a minute. Object storage wasn’t supposed to be so easy. It was not supposed to be that simple to set up and use, but MinIO burst into my storage universe like the birth of the Infinity Stones. There was a eureka moment. And I was attending one of the Storage Field Days in the US shortly after my MinIO discovery in late 2017. What an opportunity!

I could not recall how I made the appointment to meeting MinIO, but I recalled myself taking an Uber to their cosy office on University Avenue in Palo Alto to meet. Through Andy Watson (one of the CTOs then), I was introduced to AB, Garima Kapoor, MinIO’s COO and his wife, Frank Wessels, Zamin (one of the business people who is no longer there) and Ugur Tigli (East Coast CTO) who was on the Polycom. I was awe struck.

Last week, MinIO scored a major Series B round funding of USD103 million. It was delayed by the pandemic because I recalled Garima telling me that the funding was happening in 2020. But I think the delay made it better, because the world now is even more ready for MinIO than ever before.

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A conceptual distributed enterprise HCI with open source software

Cloud computing has changed everything, at least at the infrastructure level. Kubernetes is changing everything as well, at the application level. Enterprises are attracted by tenets of cloud computing and thus, cloud adoption has escalated. But it does not have to be a zero-sum game. Hybrid computing can give enterprises a balanced choice, and they can take advantage of the best of both worlds.

Open Source has changed everything too because organizations now has a choice to balance their costs and expenditures with top enterprise-grade software. The challenge is what can organizations do to put these pieces together using open source software? Integration of open source infrastructure software and applications can be complex and costly.

The next version of HCI

Hyperconverged Infrastructure (HCI) also changed the game. Integration of compute, network and storage became easier, more seamless and less costly when HCI entered the market. Wrapped with a single control plane, the HCI management component can orchestrate VM (virtual machine) resources without much friction. That was HCI 1.0.

But HCI 1.0 was challenged, because several key components of its architecture were based on DAS (direct attached) storage. Scaling storage from a capacity point of view was limited by storage components attached to the HCI architecture. Some storage vendors decided to be creative and created dHCI (disaggregated HCI). If you break down the components one by one, in my opinion, dHCI is just a SAN (storage area network) to HCI. Maybe this should be HCI 1.5.

A new version of an HCI architecture is swimming in as Angelfish

Kubernetes came into the HCI picture in recent years. Without the weights and dependencies of VMs and DAS at the HCI server layer, lightweight containers orchestrated, mostly by, Kubernetes, made distribution of compute easier. From on-premises to cloud and in between, compute resources can easily spun up or down anywhere.

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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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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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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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The future of Fibre Channel in the Cloud Era

The world has pretty much settled that hybrid cloud is the way to go for IT infrastructure services today. Straddled between the enterprise data center and the infrastructure-as-a-service in public cloud offerings, hybrid clouds define the storage ecosystems and architecture of choice.

A recent Blocks & Files article, “Broadcom server-storage connectivity sales down but recovery coming” caught my attention. One segment mentioned that the server-storage connectivity sales was down 9% leading me to think “Is this a blip or is it a signal that Fibre Channel, the venerable SAN (storage area network) protocol is on the wane?

Fibre Channel Sign

Thus, I am pondering the position of Fibre Channel SANs in the cloud era. Where does it stand now and in the near future? Continue reading