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

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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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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