Category Archives: Performance Benchmark

Is General Purpose Object Storage disenfranchised?

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[Disclosure: I am 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 will be covered by GestaltIT, the organizer and I am 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 is NOT an advertisement for coloured balls.

This is the license to brag for the vendors in the next 2 weeks or so, as we approach the 2020 new year. This, of course, is the latest 2019 IDC Marketscape for Object-based Storage, released last week.

My object storage mentions

I have written extensively about Object Storage since 2011. With different angles and perspectives, here are some of them:

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Green Storage? Meh!

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Something triggered my thoughts a few days ago. A few of us got together talking about climate change and a friend asked how green was the datacenter in IT. With cloud computing booming, I would say that green computing isn’t really the hottest thing at present. That in turn, leads us to one of the most voracious energy beasts in the datacenter, storage. Where is green storage in the equation?

What is green?

Over the past decade, several storage related technologies were touted as more energy efficient. These include

  • Tape – when tapes are offline, they do not consume power and do not require cooling
  • Virtualization – Virtualization reduces the number of servers and desktops, and of course storage too
  • MAID (Massive Array of Independent Disks) – the arrays spin down the HDDs if idle for a period of time
  • SSD (Solid State Drives) – Compared to HDDs, SSDs consume much less power, and overall reduce the cooling needs
  • Data Footprint Reduction – Deduplication, compression and other technologies to reduce copies of data
  • SMR (Shingled Magnetic Recording) Drives – Higher areal density means less drives but limited by physics.

The largest gorilla in storage technology

HDDs still dominate the market and they are the biggest producers of heat and vibration in a storage array, along with the redundant power supplies and fans. Until and unless SSDs dominate, we have to live with the fact that storage disk drives are not green. The statistics from Statistica below forecasts that in 2021, the shipment of SSDs will surpass HDDs.

Today the areal density of HDDs have increased. With SMR (shingled magnetic recording), the areal density jumped about 25% more than the 1Tb/inch (Terabit per inch) in the CMR (conventional magnetic recording) drives. The largest SMR in the market today is 16TB from Seagate with 18TB SMR in the horizon. That capacity is going to grow significantly when EAMR (energy assisted magnetic recording) – which counts heat assisted and microwave assisted – drives enter the market next year. The areal density will grow to 1.6Tb/inch with a roadmap to 4.0Tb/inch. Continue reading →

Storage Performance Considerations for AI Data Paths

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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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Figuring out storage for Kubernetes and containers

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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

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[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

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[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 →

From the past to the future

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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

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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, Weka.io, 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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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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