The Return of SAN and NAS with AWS?

AWS what?

Amazon Web Services announced Outposts at re:Invent last week. It was not much of a surprise for me because when AWS had their partnership with VMware in 2016, the undercurrents were there to have AWS services come right at the doorsteps of any datacenter. In my mind, AWS has built so far out in the cloud that eventually, the only way to grow is to come back to core of IT services – The Enterprise.

Their intentions were indeed stealthy, but I have been a believer of the IT pendulum. What has swung out to the left or right would eventually come back to the centre again. History has proven that, time and time again.

SAN and NAS coming back?

A friend of mine casually spoke about AWS Outposts announcements. Does that mean SAN and NAS are coming back? I couldn’t hide my excitement hearing the return but … be still, my beating heart!

I am a storage dinosaur now. My era started in the early 90s. SAN and NAS were a big part of my career, but cloud computing has changed and shaped the landscape of on-premises shared storage. SAN and NAS are probably closeted by the younger generation of storage engineers and storage architects, who are more adept to S3 APIs and Infrastructure-as-Code. The nuts and bolts of Fibre Channel, SMB (or CIFS if one still prefers it), and NFS are of lesser prominence, and concepts such as FLOGI, PLOGI, SMB mandatory locking, NFS advisory locking and even iSCSI IQN are probably alien to many of them.

What is Amazon Outposts?

In a nutshell, AWS will be selling servers and infrastructure gear. The AWS-branded hardware, starting from a single server to large racks, will be shipped to a customer’s datacenter or any hosting location, packaged with AWS popular computing and storage services, and optionally, with VMware technology for virtualized computing resources.

Taken from https://aws.amazon.com/outposts/

In a move ala-Azure Stack, Outposts completes the round trip of the IT Pendulum. It has swung to the left; it has swung to the right; it is now back at the centre. AWS is no longer public cloud computing company. They have just become a hybrid cloud computing company. Continue reading

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, 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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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

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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My dilemma of stateful storage marriage

I should be a love match maker.

I have been spending much hours in the past few months, thinking of stateful data in stateful storage containers and how they would consummate with distributed applications containers and functions-as-a-service (aka serverless, aka Lambda). It still hasn’t made much sense, and I have not solved this problem yet. Although there were bits and pieces that coming together and the jigsaw looked well enough to give a cackled reply, what I have now is still not good enough for me. I am still searching for answers, better than the ones I have now.

The CAP theorem is in center of my mind. Distributed data, distributed states of data are on my mind. And by the looks of things, the computing world is heading towards containers and serverless computing too. Both distributed applications containers and serverless computing make a lot of sense. If we were to engage a whole new world of fog computing, edge computing, IoT, autonomous systems, AI, and other real-time computing, I would say that the future belongs to decentralization. Cloud Computing and having edge systems and devices getting back to the cloud for data is too slow. The latency of micro- or even nano-seconds is just not good enough. If we rely on the present methods to access the most relevant data, we are too late.

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Of Object Storage, Filesystems and Multi-Cloud

Data storage silos everywhere. The early clarion call was to eliminate IT data storage silos by moving to the cloud. Fast forward to the present. Data storage silos are still everywhere, but this time, they are in the clouds. I blogged about this.

Object Storage was all the rage when it first started. AWS, with its S3 (Simple Storage Service) offering, started the cloud storage frenzy. Highly available, globally distributed, simple to access, and fitted superbly into the entire AWS ecosystem. Quickly, a smorgasbord of S3-compatible, S3-like object-based storage emerged. OpenStack Swift, HDS HCP, EMC Atmos, Cleversafe (which became IBM SpectrumScale), Inktank Ceph (which became RedHat Ceph), Bycast (acquired by NetApp to be StorageGrid), Quantum Lattus, Amplidata, and many more. For a period of a few years prior, it looked to me that the popularity of object storage with an S3 compatible front has overtaken distributed file systems.

What’s not to like? Object storage are distributed, they are metadata rich (at a certain structural level), they are immutable (hence secure from a certain point of view), and some even claim self-healing (depending on data protection policies). But one thing that object storage rarely touted dominance was high performance I/O. There were some cases, but they were either fronted by a file system (eg. NFSv4.1 with pNFS extensions), or using some host-based, SAN-client agent (eg. StorNext or Intel Lustre). Object-based storage, in its native form, has not been positioned as high performance I/O storage.

A few weeks ago, I read an article from Storage Soup, Dave Raffo. When I read it, it felt oxymoronic. SwiftStack was just nominated as a visionary in the Gartner Magic Quadrant for Distributed File Systems and Object Storage. But according to Dave’s article, Swiftstack did not want to be “associated” with object storage that much, even though Swiftstack’s technology underpinning was all object storage. Strange.

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The rise of RDMA

I have known of RDMA (Remote Direct Memory Access) for quite some time, but never in depth. But since my contract work ended last week, and I have some time off to do some personal development, I decided to look deeper into RDMA. Why RDMA?

In the past 1 year or so, RDMA has been appearing in my radar very frequently, and rightly so. The speedy development and adoption of NVMe (Non-Volatile Memory Express) have pushed All Flash Arrays into the next level. This pushes the I/O and the throughput performance bottlenecks away from the NVMe storage medium into the legacy world of SCSI.

Most network storage interfaces and protocols like SAS, SATA, iSCSI, Fibre Channel today still carry SCSI loads and would have to translate between NVMe and SCSI. NVMe-to-SCSI bridges have to be present to facilitate the translation.

In the slide below, shared at the Flash Memory Summit, there were numerous red boxes which laid out the SCSI connections and interfaces where SCSI-to-NVMe translation (and vice versa) would be required.

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