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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WekaIO controls their performance destiny

[Preamble: I have been invited by GestaltIT as a delegate to their Tech Field Day for Storage Field Day 18 from Feb 27-Mar 1, 2019 in the Silicon Valley USA. My expenses, travel and accommodation were 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]

I was first introduced to WekaIO back in Storage Field Day 15. I did not blog about them back then, but I have followed their progress quite attentively throughout 2018. 2 Storage Field Days and a year later, they were back for Storage Field Day 18 with a new CTO, Andy Watson, and several performance benchmark records.

Blowout year

2018 was a blowout year for WekaIO. They have experienced over 400% growth, placed #1 in the Virtual Institute IO-500 10-node performance challenge, and also became #1 in the SPEC SFS 2014 performance and latency benchmark. (Note: This record was broken by NetApp a few days later but at a higher cost per client)

The Virtual Institute for I/O IO-500 10-node performance challenge was particularly interesting, because it pitted WekaIO against Oak Ridge National Lab (ORNL) Summit supercomputer, and WekaIO won. Details of the challenge were listed in Blocks and Files and WekaIO Matrix Filesystem became the fastest parallel file system in the world to date.

Control, control and control

I studied WekaIO’s architecture prior to this Field Day. And I spent quite a bit of time digesting and understanding their data paths, I/O paths and control paths, in particular, the diagram below:

Starting from the top right corner of the diagram, applications on the Linux client (running Weka Client software) and it presents to the Linux client as a POSIX-compliant file system. Through the network, the Linux client interacts with the WekaIO kernel-based VFS (virtual file system) driver which coordinates the Front End (grey box in upper right corner) to the Linux client. Other client-based protocols such as NFS, SMB, S3 and HDFS are also supported. The Front End then interacts with the NIC (which can be 10/100G Ethernet, Infiniband, and NVMeoF) through SR-IOV (single root IO virtualization), bypassing the Linux kernel for maximum throughput. This is with WekaIO’s own networking stack in user space. Continue reading

StorPool – Block storage managed well

[Preamble: I have been invited by GestaltIT as a delegate to their Tech Field Day for Storage Field Day 18 from Feb 27-Mar 1, 2019 in the Silicon Valley USA. My expenses, travel and accommodation were 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]

Storage technology is complex. Storage infrastructure and data management operations are not trivial, despite what the hyperscalers like Amazon Web Services and Microsoft Azure would like you to think. As the adoption of cloud infrastructure services grow, the small and medium businesses/enterprises (SMB/SME) are usually left to their own devices to manage the virtual storage infrastructure. Cloud Service Providers (CSPs) addressing the SMB/SME market are looking for easier, worry-free, software-defined storage to elevate their value to their customers.

Managed high performance block storage

Enter StorPool.

StorPool is a scale-out block storage technology, capable of delivering 1 million+ IOPS with sub-milliseconds response times. As described by fellow delegate, Ray Lucchesi in his recent blog, they were able to achieve these impressive performance numbers in their demo, without the high throughput RDMA network or the storage class memory of Intel Optane. Continue reading

Storage and Data Management Planning crucial for Malaysian SMBs

Hybrid IT for 2019 and beyond

2019 is here.

I am especially buoyed by the strong network storage industry footing in 2018, reported by The Register last week. 2018 was certainly a blowout year for storage infrastructure and storage software, both for on-premises and the cloud computing platforms. The AWS Outposts announcement over a month ago also just affirmed that the new world is Hybrid IT. And there is plenty to look forward to in 2019.

Malaysian Economic Doldrums

Things are not as rosy for the Malaysia economy in 2019. It will be a challenging 2019 as reported by the Edge, a local business publication. The GDP (gross domestic product) of the first half of 2018 shrunk, from 5.9% in 2017, to 4.65%, and it is estimated to be 4.9% in 2019. With an inexperienced new government, a weak currency, and more competitive economies emerging in ASEAN, Malaysia small and medium businesses (SMBs) could be challenged.

The knee jerk reaction would be to cut the IT spending and revert to buying on price. This has happened too often, because there are always other operating costs that may be more pressing. Furthermore, many of the SMBs are still aimless when it comes to transforming their businesses into the digital data era, groping in the dark and sputtering to get its worth with their IT investments. Often, many are misinformed and stumbled, resulting in much higher wastage and costs.

There is a local saying here:

Good thing No Cheap; Cheap thing No Good

And the saying is very apt to describe that there is value in investing well, and the price factor should not always be the main determinant criteria of buying IT infrastructure, software and services.

Many of these SMBs also lack experienced IT staff to manage their IT environment. There is also a hurried urgency to modernize IT, because a well-planned and executed IT strategy and operations would definitely increase their Competitive Advantage. Continue reading

From the past to the future

2019 beckons. The year 2018 is coming to a close and I look upon what I blogged in the past years to reflect what is the future.

The evolution of the Data Services Platform

Late 2017, I blogged about the Data Services Platform. Storage is no longer the storage infrastructure we know but has evolved to a platform where a plethora of data services are served. The changing face of storage is continually evolving as the IT industry changes. I take this opportunity to reflect what I wrote since I started blogging years ago, and look at the articles that are shaping up the landscape today and also some duds.

Some good ones …

One of the most memorable ones is about memory cloud. I wrote the article when Dell acquired a small company by the name of RNA Networks. I vividly recalled what was going through my mind when I wrote the blog. With the SAN, NAS and DAS, and even FAN (File Area Network) happening during that period, the first thing was the System Area Network, the original objective Infiniband and RDMA. I believed the final pool of where storage will be is the memory, hence I called it the “The Last Bastion – Memory“. RNA’s technology became part of Dell Fluid Architecture.

True enough, the present technology of Storage Class Memory and SNIA’s NVDIMM are along the memory cloud I espoused years ago.

What about Fibre Channel over Ethernet (FCoE)? It wasn’t a compelling enough technology for me when it came into the game. Reduced port and cable counts, and reduced power consumption were what the FCoE folks were pitching, but the cost of putting in the FC switches, the HBAs were just too great as an investment. In the end, we could see the cracks of the FCoE story, and I wrote the pre-mature eulogy of FCoE in my 2012 blog. I got some unsavoury comments writing that blog back then, but fast forward to the present, FCoE isn’t a force anymore.

Weeks ago, Amazon Web Services (AWS) just became a hybrid cloud service provider/vendor with the Outposts announcement. It didn’t surprise me but it may have shook the traditional systems integrators. I took the stance 2 years ago when AWS partnered with VMware and juxtaposed it to the philosophical quote in the 1993 Jurassic Park movie – “Life will not be contained, … Life finds a way“.

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Sexy HPC storage is all the rage

HPC is sexy

There is no denying it. HPC is sexy. HPC Storage is just as sexy.

Looking at the latest buzz from Super Computing Conference 2018 which happened in Dallas 2 weeks ago, the number of storage related vendors participating was staggering. Panasas,, Excelero, BeeGFS, are the ones that I know because I got friends posting their highlights. Then there are the perennial vendors like IBM, Dell, HPE, NetApp, Huawei, Supermicro, and so many more. A quick check on the SC18 website showed that there were 391 exhibitors on the floor.

And this is driven by the unrelentless demand for higher and higher performance of computing, and along with it, the demands for faster and faster storage performance. Commercialization of Artificial Intelligence (AI), Deep Learning (DL) and newer applications and workloads together with the traditional HPC workloads are driving these ever increasing requirements. However, most enterprise storage platforms were not designed to meet the demands of these new generation of applications and workloads, as many have been led to believe. Why so?

I had a couple of conversations with a few well known vendors around the topic of HPC Storage. And several responses thrown back were to put Flash and NVMe to solve the high demands of HPC storage performance. In my mind, these responses were too trivial, too irresponsible. So I wanted to write this blog to share my views on HPC storage, and not just about its performance.

The HPC lines are blurring

I picked up this video (below) a few days ago. It was insideHPC Rich Brueckner interview with Dr. Goh Eng Lim, HPE CTO and renowned HPC expert about the convergence of both traditional and commercial HPC applications and workloads.

I liked the conversation in the video because it addressed the 2 different approaches. And I welcomed Dr. Goh’s invitation to the Commercial HPC community to work with the Traditional HPC vendors to help push the envelope towards Exascale SuperComputing.

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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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Cohesity SpanFS – a foundational shift

[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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