Commvault big bet

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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Hybrid is the new Black

It is hard for enterprise to let IT go, isn’t it?

For years, we have seen the cloud computing juggernaut unrelenting in getting enterprises to put their IT into public clouds. Some of the biggest banks have put their faith into public cloud service providers. Close to home, Singapore United Overseas Bank (UOB) is one that has jumped into the bandwagon, signing up for VMware Cloud on AWS. But none will come bigger than the US government Joint Enterprise Defense Infrastructure (JEDI) project, where AWS and Azure are the last 2 bidders for the USD10 billion contract.

Confidence or lack of it

Those 2 cited examples should be big enough to usher enterprises to confidently embrace public cloud services, but many enterprises have been holding back. What gives?

In the past, it was a matter of confidence and the FUDs (fears, uncertainties, doubts). News about security breaches, massive blackouts have been widely spread and amplified to sensationalize the effects and consequences of cloud services. But then again, we get the same thing in poorly managed data centers in enterprises and government agencies, often with much less fanfare. We shrug our shoulder and say “Oh well!“.

The lack of confidence factor, I think, has been overthrown. The “Cloud First” strategy in enterprises in recent years speaks volume of the growing and maturing confidence in cloud services. The poor performance and high latency reasons, which were once an Achilles heel of cloud services, are diminishing. HPC-as-a-Service is becoming real.

The confidence in cloud services is strong. Then why is on-premises IT suddenly is a cool thing again? Why is hybrid cloud getting all the attention now?

Hybrid is coming back

Even AWS wants on-premises IT. Its Outposts offering outlines its ambition. A couple of years earlier, the Azure Stack was already made beachhead on-premises in its partnership with many server vendors. VMware, is in both on-premises and the public clouds. It has strong business and technology integration with AWS and Azure. IBM Cloud, Big Blue is thinking hybrid as well. 2 months ago, Dell jumped too, announcing Dell Technologies Cloud with plenty of a razzmatazz, using all the right moves with its strong on-premises infrastructure portfolio and its crown jewel of the federation, VMware. Continue reading

Storage Performance Considerations for AI Data Paths

The hype of Deep Learning (DL), Machine Learning (ML) and Artificial Intelligence (AI) has reached an unprecedented frenzy. Every infrastructure vendor from servers, to networking, to storage has a word to say or play about DL/ML/AI. This prompted me to explore this hyped ecosystem from a storage perspective, notably from a storage performance requirement point-of-view.

One question on my mind

There are plenty of questions on my mind. One stood out and that is related to storage performance requirements.

Reading and learning from one storage technology vendor to another, the context of everyone’s play against their competitors seems to be  “They are archaic, they are legacy. Our architecture is built from ground up, modern, NVMe-enabled“. And there are more juxtaposing, but you get the picture – “We are better, no doubt“.

Are the data patterns and behaviours of AI different? How do they affect the storage design as the data moves through the workflow, the data paths and the lifecycle of the AI ecosystem?

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The Heart of Digital Transformation is …

Businesses have taken up Digital Transformation in different ways and at different pace. In Malaysia, company boardrooms are accepting Digital Transformation as a core strategic initiative, crucial to develop competitive advantage in their respective industries. Time and time again, we are reminded that Data is the lifeblood and Data fuels the Digital Transformation initiatives.

The rise of CDOs

In line with the rise of the Digital Transformation buzzword, I have seen several unique job titles coming up since a few years ago. Among those titles, “Chief Digital Officer“, “Chief Data Officer“, “Chief Experience Officer” are some eye-catching ones. I have met a few of them, and so far, those I met were outward facing, customer facing. In most of my conversations with them respectively, they projected a front that their organization, their business and operations have been digital transformed. They are ready to help their customers to transform. Are they?

Tech vendors add more fuel

The technology vendors have an agenda to sell their solutions and their services. They paint aesthetically pleasing stories of how their solutions and wares can digitally transform any organizations, and customers latch on to these ‘shiny’ tech. End users get too fixated that technology is the core of Digital Transformation. They are wrong.

Missing the Forest

As I gather more insights through observations, and more conversations and more experiences, I think most of the “digital transformation ready” organizations are not adopting the right approach to Digital Transformation.

Digital Transformation is not tactical. It is not a one-time, big bang action that shifts from not-digitally-transformed to digitally-transformed in a moment. It is not a sprint. It is a marathon. It is a journey that will take time to mature. IDC and its Digital Transformation MaturityScape Framework is spot-on when they first released the framework years ago.

IDC Digital Transformation Maturityscape

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Whither HPC, HPE?

HPE is acquiring Cray Inc. Almost 3 years ago, HPE acquired SGI. Back in 2017, HPE partnered WekaIO, and invested big in the latest Series C funding of WekaIO just weeks ago.

Cray, SGI and WekaIO are all strong HPC technology companies. Given the strong uptick in the HPC market, especially commercial HPC, we cannot deny HPE’s ambition to become the top SuperComputing and HPC vendor in the industry. Continue reading

Scaling new HPC with Composable Architecture

[Disclosure: I was invited by Dell Technologies as a delegate to their Dell Technologies World 2019 Conference from Apr 29-May 1, 2019 in the Las Vegas USA. Tech Field Day Extra was an included activity as part of the Dell Technologies World. My expenses, travel, accommodation and conference fees were covered by Dell Technologies, 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]

Deep Learning, Neural Networks, Machine Learning and subsequently Artificial Intelligence (AI) are the new generation of applications and workloads to the commercial HPC systems. Different from the traditional, more scientific and engineering HPC workloads, I have written about the new dawn of supercomputing and the attractive posture of commercial HPC.

Don’t be idle

From the business perspective, the investment of HPC systems is high most of the time, and justifying it to the executives and the investors is not easy. Therefore, it is critical to keep feeding the HPC systems and significantly minimize the idle times for compute, GPUs, network and storage.

However, almost all HPC systems today are inflexible. Once assigned to a project, the resources pretty much stay with the project, even when the workload processing of the project is idle and waiting. Of course, we have to bear in mind that not all resources are fully abstracted, virtualized and software-defined whereby you can carve out pieces of the hardware and deliver a percentage of that resource. Case in point is the CPU, where you cannot assign certain clock cycles of CPU to one project and another half to the other. The technology isn’t there yet. Certain resources like GPU is going down the path of Virtual GPU, and into the realm of resource disaggregation. Eventually, all resources of the HPC systems – CPU, memory, FPGA, GPU, PCIe channels, NVMe paths, IOPS, bandwidth, burst buffers etc – should be disaggregated and pooled for disparate applications and workloads based on demands of usage, time and performance.

Hence we are beginning to see the disaggregated HPC systems resources composed and built up the meet the diverse mix and needs of HPC applications and workloads. This is even more acute when a AI project might grow cold, but the training of AL/ML/DL workloads continues to stay hot

Liqid the early leader in Composable Architecture

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Connecting ideas and people with Dell Influencers

[Disclosure: I was invited by Dell Technologies as a delegate to their Dell Technologies World 2019 Conference from Apr 29-May 1, 2019 in the Las Vegas USA. My expenses, travel, accommodation and conference fees were covered by Dell Technologies, 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 just got home from Vegas yesterday after attending my 2nd Dell Technologies World as one of the Dell Luminaries. The conference was definitely a bigger one than the one last year, with more than 15,000 attendees. And there was a frenzy of announcements, from Dell Technologies Cloud to new infrastructure solutions, and more. The big one for me, obviously was Azure VMware Solutions officiated by Microsoft CEO Satya Nadella and VMware CEO Pat Gelsinger, with Michael Dell bringing together the union. I blogged about Dell jumping into the cloud in a big way.

AI Tweetup

In the razzmatazz, the most memorable moments were one of the Tweetups organized by Dr. Konstanze Alex (Konnie) and her team, and Tech Field Day Extra.

Tweetup was alien to me. I didn’t know how the concept work and I did google tweetup before that. There were a few tweetups on the topics of data protection and 5G, but the one that stood out for me was the AI tweetup.

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Dell go big with Cloud

[Disclaimer: I have been invited by Dell Technologies as a delegate to their Dell Technologies World 2019 Conference from Apr 29-May 1, 2019 in the Las Vegas USA. My expenses, travel and accommodation are covered by Dell Technologies, the organizer and I am not obligated to blog or promote their technologies presented at this event. The content of this blog is of my own opinions and views]

Talk about big. Dell Technologies just went big with the Cloud.

The Microsoft Factor

Day 1 of Dell Technologies World 2019 (DTW19) started with a big surprise to many, including yours truly when Michael Dell, together with Pat Gelsinger invited Microsoft CEO, Satya Nadella on stage.

There was nothing new about Microsoft working with Dell Technologies. Both have been great partners since the PC days, but when they announced Azure VMware Solutions to the 15,000+ attendees of the conference, there was a second of disbelief, followed by an ovation of euphoria.

VMware solutions will run native on Microsoft Azure Cloud. The spread of vSphere, VSAN, vCenter, NSX-T and VMware tools and environment will run on Azure Bare Metal Infrastructure at multiple Azure locations. How big is that. Continue reading

Lift and Shift Begone!

I am excited. New technologies are bringing the data (and storage) closer to processing and compute than ever before. I believe the “Lift and Shift” way would be a thing of the past … soon.

Data is heavy

Moving data across the network is painful. Moving data across distributed networks is even more painful. To compile the recent first image of a black hole, an amount of 5PB or more had to shipped for central processing. If this was moved over a 10 Gigabit network, it would have taken weeks.

Furthermore, data has dependencies. Snapshots, clones, and other data relationships with applications and processes render data inert, weighing it down like an anchor of a ship.

When I first started in the industry more than 25 years ago, Direct Attached Storage (DAS) was the dominating storage platform. I had a bulky Sun MultiDisk Pack connected via Fast SCSI to my SPARCstation 2 (diagram below):

Then I was assigned as the implementation engineer for Hock Hua Bank (now defunct) retail banking project in their Sibu HQ in East Malaysia. It was the first Sun SPARCstorage 1000 (photo below), running a direct attached Fibre Channel 0.25 Gbps FCAL (Fibre Channel Arbitrated Loop). It was the cusp of the birth of SAN (Storage Area Network).

Photo from https://www.cca.org/dave/tech/sys5/

The proliferation of SAN over the next 2 decades pushed DAS into obscurity, until SAS (Serial Attached SCSI) came about. Added to the mix was the prominence of Cloud Storage. But on-premises storage and Cloud Storage didn’t always come together. There was always a valley between the 2, until the public clouds gained a stronger foothold in the minds of IT and businesses. Today, both on-premises storage and cloud storage are slowly cosying as one Data Singularity, thanks to vision and conceptualization of data fabrics. NetApp was an early proponent of the Data Fabric concept 4 years ago. Continue reading

Figuring out storage for Kubernetes and containers

Oops! I forgot about you!

To me, containers and container orchestration (CO) engines such as Kubernetes, Mesos, Docker Swarm are fantastic. They scale effortlessly and are truly designed for cloud native applications (CNA).

But one thing irks me. Storage management for containers and COs. It was as if when they designed and constructed containers and the containers orchestration (CO) engines, they forgot about the considerations of storage and storage management. At least the persistent part of storage.

Over a year ago, I was in two minds about persistent storage, especially when it comes to the transient nature of microservices which was so prevalent and were inundating the cloud native applications landscape. I was searching for answers in my blog. The decentralization of microservices in containers means mass deployment at the edge, but to have the pre-processed and post-processed data stick to the persistent storage at the edge device is a challenge. The operative word here is “STICK”.

Two different worlds

Containers were initially designed and built for lightweight applications such as microservices. The runtime, libraries, configuration files and dependencies are all in one package. They were meant to do simple tasks quickly and scales to thousands easily. They could be brought up and brought down in little time and did not have to bother about the persistent data stored by the host. The state of the containers were also not important to the application tasks at hand.

Today containers like Docker have matured to run enterprise applications and the state of the container is important. The applications must know the state and the health of the container. The container could be in online mode, online but not accepting data mode, suspended mode, paused mode, interrupted mode, quiesced mode or halted mode. Each mode or state of the container is important to the running applications and the container can easily brought up or down in an instance of a command. The stateful nature of the containers and applications is critical for the business. The same situation applies to container orchestration engines such as Kubernetes.

Container and Kubernetes Storage

Docker provides 3 methods to local storage. In the diagram below, it describes:

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