Category Archives: MapReduce

The All-Important Storage Appliance Mindset for HPC and AI projects

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I am strong believer of using the right tool to do the job right. I have said this before 2 years ago, in my blog “Stating the case for a Storage Appliance approach“. It was written when I was previously working for an open source storage company. And I am an advocate of the crafter versus assembler mindset, especially in the enterprise and high- performance storage technology segments.

I have joined DDN. Even with DDN that same mindset does not change a bit. I have been saying all along that the storage appliance model should always be the mindset for the businesses’ peace-of-mind.

My view of the storage appliance model began almost 25 years. I came into NAS systems world via Sun Microsystems®. Sun was famous for running NFS servers on general Sun Solaris servers. NFS services on Unix systems. Back then, I remember arguing with one of the Sun distributors about the tenets of running NFS over 100Mbit/sec Ethernet on Sun servers. I was drinking Sun’s Kool-Aid big time.

When I joined Network Appliance® (now NetApp®) in 2000, my worldview of putting software on general purpose servers changed. Network Appliance®, had one product family, the FAS700 (720, 740, 760) family. All NetApp® did was to serve NFS services in the beginning. They were the NAS filers and nothing else.

I was completed sold on the appliance way with NetApp®. Firstly, it was my very first time knowing such network storage services could be provisioned with an appliance concept. This was different from Sun. I was used to managing NFS exports on a Sun SPARCstation 20 to Unix clients in the network.

Secondly, my mindset began to shape that “you have to have the right tool to the job correctly and extremely well“. Well, the toaster toasts bread very well and nothing else. And the fridge (an analogy used by Dave Hitz, I think) does what it does very well too. That is what the appliance does. You definitely cannot grill a steak with a bread toaster, just like you can’t run an excellent, ultra-high performance storage services to serve the demanding AI and HPC applications on a general server platform. You have to have a storage appliance solution for High-Speed Storage.

That little Network Appliance® toaster award given out to exemplary employees stood vividly in my mind. The NetApp® tagline back then was “Fast, Simple, Reliable”. That solidifies my mindset for the high-speed storage in AI and HPC projects in present times.

DDN AI400X2 Turbo Appliance

Costs Benefits and Risks

I like to think about what the end users are thinking about. There are investments costs involved, and along with it, risks to the investments as well as their benefits. Let’s just simplify and lump them into Cost-Benefits-Risk analysis triangle. These variables come into play in the decision making of AI and HPC projects.

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Rethinking data processing frameworks systems in real time

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“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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What the heck is Storage Modernization?

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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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Hadoop is truly dead – LOTR version

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[Disclosure: I was invited by GestaltIT as a delegate to their Storage Field Day 19 event from Jan 22-24, 2020 in the Silicon Valley USA. My expenses, travel, accommodation and conference fees were covered by GestaltIT, the organizer and I was not obligated to blog or promote the vendors’ technologies to be presented at this event. The content of this blog is of my own opinions and views]

This blog was not intended because it was not in my plans to write it. But a string of events happened in the Storage Field Day 19 week and I have the fodder to share my thoughts. Hadoop is indeed dead.

Warning: There are Lord of the Rings references in this blog. You might want to do some research. 😉

Storage metrics never happened

The fellowship of Arjan Timmerman, Keiran Shelden, Brian Gold (Pure Storage) and myself started at the office of Pure Storage in downtown Mountain View, much like Frodo Baggins, Samwise Gamgee, Peregrine Took and Meriadoc Brandybuck forging their journey vows at Rivendell. The podcast was supposed to be on the topic of storage metrics but was unanimously swung to talk about Hadoop under the stewardship of Mr. Stephen Foskett, our host of Tech Field Day. I saw Stephen as Elrond Half-elven, the Lord of Rivendell, moderating the podcast as he would have in the plans of decimating the One Ring in Mount Doom.

So there we were talking about Hadoop, or maybe Sauron, or both.

The photo of the Oliphaunt below seemed apt to describe the industry attacks on Hadoop.

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Time to Advocate Common Data Personality

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The thought of it has been on my mind since Commvault GO 2019. It was sparked when Don Foster, VP of Storage Solutions of Commvault answered a question posted by one of the analysts. What he said made a connection, as I was searching for the better insights to how Commvault and Hedvig would end up to be together.

Data Deluge is a swamp thing now

Several years ago, I heard Stephen Brobst, CTO of Teradata brought up the term “Data Swamp“. It was the anti- part of the Data Lakes, and this was back when Data Lakes and Hadoop were all the rage. His comments were raw, honest and it was leading to the truth out there.

Source: https://www.deviantart.com/rhineville/art/God-that-Crawls-Detail-2-291228644

I was enamoured by his thoughts at the time, and today, his comments about the Data Swamp manifested itself. Continue reading →

Commvault big bet

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I woke up at 2.59am in the morning of Sept 5th morning, a bit discombobulated and quickly jumped into the Commvault call. The damn alarm rang and I slept through it, but I got up just in time for the 3am call.

As I was going through the motion of getting onto UberConference, organized by GestaltIT, I was already sensing something big. In the call, Commvault was acquiring Hedvig and it hit me. My drowsy self centered to the big news. And I saw a few guys from Veritas and Cohesity on my social media group making gestures about the acquisition.

I spent the rest of the week thinking about the acquisition. What is good? What is bad? How is Commvault going to move forward? This is at pressing against the stark background from the rumour mill here in South Asia, just a week before this acquisition news, where I heard that the entire Commvault teams in Malaysia and Asia Pacific were released. I couldn’t confirm the news in Asia Pacific, but the source of the news coming from Malaysia was strong and a reliable one.

What is good?

It is a big win for Hedvig. Nestled among several scale-out primary storage vendors and little competitive differentiation, this Commvault acquisition is Hedvig’s pay day.

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Oracle Cloud Infrastructure to prove skeptics wrong

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[Preamble: I have been invited by  GestaltIT as a delegate to their TechFieldDay from Oct 17-19, 2018 in the Silicon Valley USA. My expenses, travel and accommodation are covered by GestaltIT, the organizer and I was not obligated to blog or promote their technologies presented at this event. The content of this blog is of my own opinions and views]

The much maligned Oracle Cloud is getting a fresh reboot, starting with their Oracle Cloud Infrastructure (OCI), and significant enhancements and technology updates were announced at the Oracle Open World this week. I had the privilege to hear about Oracle Cloud’s new attack plan when they presented at Tech Field Day 17 last week.

Oracle Cloud has not have the best of days in recent months. Thomas Kurian’s resignation as their President of Product Development was highly publicized in a disagreement with CTO and founder, Larry Ellison over cloud software strategy. Then there was an on-going lawsuit about how Oracle was misrepresenting their cloud revenue growth, which puts Oracle in a bad light.

On the local front here in Malaysia, I have heard from the grapevine of the aggressive nature of Oracle personnel pushing partners and customers to adopt their cloud services using legal scare tactics on their database licensing. A buddy of mine, who was previously the cloud business development manager at CTC Global, also shared Oracle’s cloud shortcomings compared to Amazon Web Service and Microsoft Azure a year ago.

Oracle Cloud Infrastructure team aimed to turnover the bad perceptions, starting with the delegates of Tech Field Day 17, including yours truly.Their strategy was clear. Oracle Cloud Infrastructure runs the highest performance and the highest enterprise grade Infrastructure-as-a-Service (IaaS), bar none. Unlike the IBM Cloud, which in my opinion is a wishy-washy cloud service platform, Oracle Cloud’s ambition is solid.

They did a demo on JDEdwards EnterpriseOne application, and they continue to demonstrate their prowess running the highest performance computing experience ever, for all enterprise-grade workload. And that enterprise pedigree is clear.

Just this week, Amazon Prime Day had an outage. Amazon is in the process of weaning Oracle database from their entire ecosystem by 2020, and this outage clearly showed that the Oracle database and the enterprise applications would only run best on Oracle Cloud Infrastructure.

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The Network is Still the Computer

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[Preamble: I have been invited by  GestaltIT as a delegate to their TechFieldDay from Oct 17-19, 2018 in the Silicon Valley USA. My expenses, travel and accommodation are covered by GestaltIT, the organizer and I was not obligated to blog or promote their technologies presented at this event. The content of this blog is of my own opinions and views]

Sun Microsystems coined the phrase “The Network is the Computer“. It became one of the most powerful ideologies in the computing world, but over the years, many technology companies have tried to emulate and practise the mantra, but fell short.

I have never heard of Drivescale. It wasn’t in my radar until the legendary NFS guru, Brian Pawlowski joined them in April this year. Beepy, as he is known, was CTO of NetApp and later at Pure Storage, and held many technology leadership roles, including leading the development of NFSv3 and v4.

Prior to Tech Field Day 17, I was given some “homework”. Stephen Foskett, Chief Cat Herder (as he is known) of Tech Field Days and Storage Field Days, highly recommended Drivescale and asked the delegates to pick up some notes on their technology. Going through a couple of the videos, Drivescale’s message and philosophy resonated well with me. Perhaps it was their Sun Microsystems DNA? Many of the Drivescale team members were from Sun, and I was previously from Sun as well. I was drinking Sun’s Kool Aid by the bucket loads even before I graduated in 1991, and so what Drivescale preached made a lot of sense to me.Drivescale is all about Scale-Out Architecture at the webscale level, to address the massive scale of data processing. To understand deeper, we must think about “Data Locality” and “Data Mobility“. I frequently use these 2 “points of discussion” in my consulting practice in architecting and designing data center infrastructure. The gist of data locality is simple – the closer the data is to the processing, the cheaper/lightweight/efficient it gets. Moving data – the data mobility part – is expensive.

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Hammering Next Gen Hybrid Clouds

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[Preamble: I have been invited by  GestaltIT as a delegate to their TechFieldDay from Oct 17-19, 2018 in the Silicon Valley USA. My expenses, travel and accommodation are paid by GestaltIT, the organizer and I was not obligated to blog or promote their technologies presented at this event. The content of this blog is of my own opinions and views]

Hammerspace came out of stealth 2 days ago. Their objective? To rule the world of data for hybrid clouds and multi-clouds, and provide “unstructured data anywhere on-demand“. That is a bold statement, for a company that is relatively unknown, except for its deep ties with the now defunct Primary Data. Primary Data’s Chairman, David Flynn, is the head honcho at Hammerspace.

The Hammerspace technology has come the right time in my opinion because the entire cloud, multi-cloud and hybrid cloud stories have become fractured, siloed. The very thing that cloud computing touted to fix has brought back the same set of problems. At the same time, not every application was developed for the cloud. Applications rely on block storage services, or NAS protocols, or the de facto S3 protocols for storage repositories. However, the integration and communication between applications break down when these on-premises applications are moving to the cloud, or when applications residing the cloud are moved back to on-premises for throughput delivery, or even applications residing at the edge.

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Cohesity SpanFS – a foundational shift

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[Preamble: I was a delegate of Storage Field Day 15 from Mar 7-9, 2018. My expenses, travel and accommodation were paid for by GestaltIT, the organizer and I was not obligated to blog or promote the technologies presented at this event. The content of this blog is of my own opinions and views]

Cohesity SpanFS impressed me. Their filesystem was designed from ground up to meet the demands of the voluminous cloud-scale data, and yes, the sheer magnitude of data everywhere needs to be managed.

We all know that primary data is always the more important piece of data landscape but there is a growing need to address the secondary data segment as well.

Like a floating iceberg, the piece that is sticking out is the more important primary data but the larger piece beneath the surface of the water, which is the secondary data, is becoming more valuable. Applications such as file shares, archiving, backup, test and development, and analytics and insights are maturing as the foundational data management frameworks and fast becoming the bedrock of businesses.

The ability of businesses to bounce back after a disaster; the relentless testing of large data sets to develop new competitive advantage for businesses; the affirmations and the insights of analyzing data to reduce risks in decision making; all these are the powerful back engine applicability that thrust businesses forward. Even the ability to search for the right information in a sea of data for regulatory and compliance reasons is part of the organization’s data management application.

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