Disaggregation or hyperconvergence?

[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]

There is an argument about NetApp‘s HCI (hyperconverged infrastructure). It is not really a hyperconverged product at all, according to one school of thought. Maybe NetApp is just riding on the hyperconvergence marketing coat tails, and just wanted to be associated to the HCI hot streak. In the same spectrum of argument, Datrium decided to call their technology open convergence, clearly trying not to be related to hyperconvergence.

Hyperconvergence has been enjoying a period of renaissance for a few years now. Leaders like Nutanix, VMware vSAN, Cisco Hyperflex and HPE Simplivity have been dominating the scene, and touting great IT benefits and eliminating IT efficiencies. But in these technologies, performance and capacity are tightly intertwined. That means that in each of the individual hyperconverged nodes, typically starting with a trio of nodes, the processing power and the storage capacity comes together. You have to accept both resources as a node. If you want more processing power, you get the additional storage capacity that comes with that node. If you want more storage capacity, you get more processing power whether you like it or not. This means, you get underutilized resources over time, and definitely not rightsized for the job.

And here in Malaysia, we have seen vendors throw in hyperconverged infrastructure solutions for every single requirement. That was why I wrote a piece about some zealots of hyperconverged solutions 3+ years ago. When you think you have a magical hammer, every problem is a nail. 😉

In my radar, NetApp and Datrium are the only 2 vendors that offer separate nodes for compute processing and storage capacity and still fall within the hyperconverged space. This approach obviously benefits the IT planners and the IT architects, and the customers too because they get what they want for their business. However, the disaggregation of compute processing and storage leads to the argument of whether these 2 companies belong to the hyperconverged infrastructure category.

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Pondering Redhat’s future with IBM

I woke up yesterday morning with a shocker of a news. IBM announced that they were buying Redhat for USD34 billion. Never in my mind that Redhat would sell but I guess that USD190.00 per share was too tempting. Redhat (RHT) was trading at USD116.68 on the previous Friday’s close.

Redhat is one of my favourite technology companies. I love their Linux development and progress, and I use a lot of Fedora and CentOS in my hobbies. I started with Redhat back in 2000, when I became obsessed to get my RHCE (Redhat Certified Engineer). I recalled on almost every weekend (Saturday and Sunday) back in 2002 when I was in the office, learning Redhat, and hacking scripts to be really good at it. I got certified with RHCE 4 with a 96% passing mark, and I was very proud of my certification.

One of my regrets was not joining Redhat in 2006. I was offered the job as an SE by Josep Garcia, and the very first position in Malaysia. Instead, I took up the Hitachi Data Systems job to helm the project implementation and delivery for the Shell GUSto project. It might have turned out differently if I did.

The IBM acquisition of Redhat left a poignant feeling in me. In many ways, Redhat has been the shining star of Linux. They are the only significant one left leading the charge of open source. They are the largest contributors to the Openstack projects and continue to support the project strongly whilst early protagonists like HPE, Cisco and Intel have reduced their support. They are of course, the perennial top 3 contributors to the Linux kernel since the very early days. And Redhat continues to contribute to projects such as containers and Kubernetes and made that commitment deeper with their recent acquisition of CoreOS a few months back.

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Oracle Cloud Infrastructure to prove skeptics wrong

[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

[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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My first TechFieldDay

[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]

I have attended a bunch of Storage Field Days over the years but I have never attended a Tech Field Day. This coming week, I will be attending their 17th edition, TechFieldDay 17, but my first. I have always enjoyed Storage Field Days. Everytime I joined as a delegate, there were new things to discover but almost always, serendipity happened.

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The Malaysian Openstack storage conundrum

The Openstack blippings on my radar have ratcheted up this year. I have been asked to put together the IaaS design several times, either with the flavours of RedHat or Ubuntu, and it’s a good thing to see the Openstack interest level going up in the Malaysian IT scene. Coming into its 8th year, Openstack has become a mature platform but in the storage projects of Openstack, my observations tell me that these storage-related projects are not as well known as we speak.

I was one of the speakers at the Openstack Malaysia 8th Summit over a month ago. I started my talk with question – “Can anyone name the 4 Openstack storage projects?“. The response from the floor was “Swift, Cinder, Ceph and … (nobody knew the 4th one)” It took me by surprise when the floor almost univocally agreed that Ceph is one of the Openstack projects but we know that Ceph isn’t one. Ceph? An Openstack storage project?

Besides Swift, Cinder, there is Glance (depending on how you look at it) and the least known .. Manila.

I have also been following on many Openstack Malaysia discussions and discussion groups for a while. That Ceph response showed the lack of awareness and knowledge of the Openstack storage projects among the Malaysian IT crowd, and it was a difficult issue to tackle. The storage conundrum continues to perplex me because many whom I have spoken to seemed to avoid talking about storage and viewing it like a dark art or some voodoo thingy.

I view storage as the cornerstone of the 3 infrastructure pillars  – compute, network and storage – of Openstack or any software-defined infrastructure stack for that matter. So it is important to get an understanding the Openstack storage projects, especially Cinder.

Cinder is the abstraction layer that gives management and control to block storage beneath it. In a nutshell, it allows Openstack VMs and applications consume block storage in a consistent and secure way, regardless of the storage infrastructure or technology beneath it. This is achieved through the cinder-volume service which is a driver most storage vendors integrate with (as shown in the diagram below).

Diagram in slides is from Mirantis found at https://www.slideshare.net/mirantis/openstack-architecture-43160012

Diagram in slides is from Mirantis found at https://www.slideshare.net/mirantis/openstack-architecture-43160012

Cinder-volume together with cinder-api, and cinder-scheduler, form the Block Storage Services for Openstack. There is another service, cinder-backup which integrates with Openstack Swift but in my last check, this service is not as popular as cinder-volume, which is widely supported by many storage vendors with both Fibre Channel and iSCSi implementations, and in a few vendors, with NFS and SMB as well. Continue reading

Industry 4.0 secret gem with Dell

[Preamble: I have been invited by Dell Technologies as a delegate to their upcoming Dell Technologies World from Apr 30-May 2, 2018 in Las Vegas, USA. My expenses, travel and accommodation will be paid by Dell Technologies, 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]

This may seem a little strange. How does Industry 4.0 relate to Dell Technologies?

Recently, I was involved in an Industry 4.0 consortium called Data Industry 4.0 (di 4.0). The objective of the consortium is to combine the foundations of 5S (seiri, seiton, seiso, seiketsu, and shitsuke), QRQC (Quick Response Quality Control) and Kaizen methodologies with the 9 pillars of Industry 4.0 with a strong data insight focus.

Industry 4.0 has been the latest trend in new technologies in the manufacturing world. It is sweeping the manufacturing industry segment by storm, leading with the nine pillars of Industry 4.0:

  • Horizontal and Vertical System Integration
  • Industrial Internet of Things
  • Simulation
  • Additive Manufacturing
  • Cloud Computing
  • Augmented Reality
  • Big Data and Analytics
  • Cybersecurity
  • Autonomous Robots

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Own the Data Pipeline

[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]

I am a big proponent of Go-to-Market (GTM) solutions. Technology does not stand alone. It must be in an ecosystem, and in each industry, in each segment of each respective industry, every ecosystem is unique. And when we amalgamate data, the storage infrastructure technologies and the data management into the ecosystem, we reap the benefits in that ecosystem.

Data moves in the ecosystem, from system to system, north to south, east to west and vice versa, random, sequential, ad-hoc. Data acquires different statuses, different roles, different relevances in its lifecycle through the ecosystem. From it, we derive the flow, a workflow of data creating a data pipeline. The Data Pipeline concept has been around since the inception of data.

To illustrate my point, I created one for the Oil & Gas – Exploration & Production (EP) upstream some years ago.

 

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