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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The engineering of Elastifile

[Preamble: I was a delegate of Storage Field Day 12. My expenses, travel and accommodation were paid for by GestaltIT, the organizer and I was not obligated to blog or promote the technologies presented in this event]

When it comes to large scale storage capacity requirements with distributed cloud and on-premise capability, object storage is all the rage. Amazon Web Services started the object-based S3 storage service more than a decade ago, and the romance with object storage started.

Today, there are hundreds of object-based storage vendors out there, touting features after features of invincibility. But after researching and reading through many design and architecture papers, I found that many object-based storage technology vendors began to sound the same.

At the back of my mind, object storage is not easy when it comes to most applications integration. Yes, there is a new breed of cloud-based applications with RESTful CRUD API operations to access object storage, but most applications still rely on file systems to access storage for capacity, performance and protection.

These CRUD and CRUD-like APIs are the common semantics of interfacing object storage platforms. But many, many real-world applications do not have the object semantics to interface with storage. They are mostly designed to interface and interact with file systems, and secretly, I believe many application developers and users want a file system interface to storage. It does not matter if the storage is on-premise or in the cloud.

Let’s not kid ourselves. We are most natural when we work with files and folders.

Implementing object storage also denies us the ability to optimally utilize Flash and solid state storage on-premise when the compute is in the cloud. Similarly, when the compute is on-premise and the flash-based object storage is in the cloud, you get a mismatch of performance and availability requirements as well. In the end, there has to be a compromise.

Another “feature” of object storage is its poor ability to handle transactional data. Most of the object storage do not allow modification of data once the object has been created. Putting a NAS front (aka a NAS gateway) does not take away the fact that it is still object-based storage at the very core of the infrastructure, regardless if it is on-premise or in the cloud.

Resiliency, latency and scalability are the greatest challenges when we want to build a true globally distributed storage or data services platform. Object storage can be resilient and it can scale, but it has to compromise performance and latency to be so. And managing object storage will not be as natural as to managing a file system with folders and files.

Enter Elastifile.

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Ryussi MoSMB – High performance SMB

I am back in the Silicon Valley as a Storage Field Day 12 delegate.

One of the early presenters was Ryussi, who was sharing a proprietary SMB server implementation of Linux and Unix systems. The first thing which comes to my mind was why not SAMBA? It’s free; It works; It has the 25 years maturity. But my experience with SAMBA, even in the present 4.x, does have its quirks and challenges, especially in the performance of large file transfers.

One of my customers uses our FreeNAS box. It’s a 50TB box for computer graphics artists and a rendering engine. After running the box for about 3 months, one case escalated to us was the SMB shares couldn’t be mapped all of a sudden. All the Windows clients were running version 10. Our investigation led us to look at the performance of SMB in the SAMBA 4 of FreeNAS.

This led to other questions such as the vfs_aio_pthread, FreeBSD/FreeNAS implementation of asynchronous I/O to overcome the performance weaknesses of the POSIX AsyncIO interface. The FreeNAS forum is flooded with sightings of missing SMB service that during large file transfer. Without getting too deep into the SMB performance issue, we decided to set the “Server Minimum Protocol” and “Server Maximum Protocol” to be SMB 2.1. The FreeNAS box at the customer has been stable now for the past 5 months.

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Let’s smoke the storage peace pipe

NVMe (Non-Volatile Memory Express) is upon us. And in the next 2-3 years, we will see a slew of new storage solutions and technology based on NVMe.

Just a few days ago, The Register released an article “Seventeen hopefuls fight for the NVMe Fabric array crown“, and it was timely. I, for one, cannot be more excited about the development and advancement of NVMe and the upcoming NVMeF (NVMe over Fabrics).

This is it. This is the one that will end the wars of DAS, NAS and SAN and unite the warring factions between server-based SAN (the sexy name differentiating old DAS and new DAS) and the networked storage of SAN and NAS. There will be PEACE.

Remember this?

nutanix-nosan-buntingNutanix popularized the “No SAN” movement which later led to VMware VSAN and other server-based SAN solutions, hyperconverged techs such as PernixData (acquired by Nutanix), DataCore, EMC ScaleIO and also operated in hyperscalers – the likes of Facebook and Google. The hyperconverged solutions and the server-based SAN lines blurred of storage but still, they are not the usual networked storage architectures of SAN and NAS. I blogged about this, mentioning about how the pendulum has swung back to favour DAS, or to put it more appropriately, server-based SAN. There was always a “Great Divide” between the 2 modes of storage architectures. Continue reading

Can CDMI emancipate an interoperable medical records cloud ecosystem?

PREFACE: This is just a thought, an idea. I am by no means an expert in this area. I have researched this to inspire a thought process of how we can bring together 2 disparate worlds of medical records and imaging with the emerging cloud services for healthcare.

Healthcare has been moving out of its archaic shell in the past few years, and digital healthcare technology and services are booming. And this movement is part of the digital transformation which could eventually lead to a secure and compliant distribution and collaboration of health data, medical imaging and electronic medical records (EMR).

It is a blessing that today’s medical imaging industry has been consolidated with the DICOM (Digital Imaging and Communications in Medicine) standard. DICOM dictates the how medical imaging information and pictures are used, stored, printed, transmitted and exchanged. It is also a communication protocol which runs over TCP/IP, and links up different service class providers (SCPs) and service class users (SCUs), and the backend systems such as PACS (Picture Archiving & Communications Systems) and RIS (Radiology Information Systems).

Another well accepted standard is HL7 (Health Level 7), a similar Layer 7, application-level communication protocol for transferring and exchanging clinical and administrative data.

The diagram below shows a self-contained ecosystem involving the front-end HIS (Hospital Information Systems), and the integration of healthcare, medical systems and other DICOM modalities.

Hospital Enterprise

(Picture courtesy of Meddiff Technologies)

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The reverse wars – DAS vs NAS vs SAN

It has been quite an interesting 2 decades.

In the beginning (starting in the early to mid-90s), SAN (Storage Area Network) was the dominant architecture. DAS (Direct Attached Storage) was on the wane as the channel-like throughput of Fibre Channel protocol coupled by the million-device addressing of FC obliterated parallel SCSI, which was only able to handle 16 devices and throughput up to 80 (later on 160 and 320) MB/sec.

NAS, defined by CIFS/SMB and NFS protocols – was happily chugging along the 100 Mbit/sec network, and occasionally getting sucked into the arguments about why SAN was better than NAS. I was already heavily dipped into NFS, because I was pretty much a SunOS/Solaris bigot back then.

When I joined NetApp in Malaysia in 2000, that NAS-SAN wars were going on, waiting for me. NetApp (or Network Appliance as it was known then) was trying to grow beyond its dot-com roots, into the enterprise space and guys like EMC and HDS were frequently trying to put NetApp down.

It’s a toy”  was the most common jibe I got in regular engagements until EMC suddenly decided to attack Network Appliance directly with their EMC CLARiiON IP4700. EMC guys would fondly remember this as the “NetApp killer“. Continue reading

Why demote archived data access?

We are all familiar with the concept of data archiving. Passive data gets archived from production storage and are migrated to a slower and often, cheaper storage medium such tapes or SATA disks. Hence the terms nearline and offline data are created. With that, IT constantly reminds users that the archived data is infrequently accessed, and therefore, they have to accept the slower access to passive, archived data.

The business conditions have certainly changed, because the need for data to be 100% online is becoming more relevant. The new competitive nature of businesses dictates that data must be at the fingertips, because speed and agility are the new competitive advantage. Often the total amount of data, production and archived data, is into hundred of TBs, even into PetaBytes!

The industries I am familiar with – Oil & Gas, and Media & Entertainment – are facing this situation. These industries have a deluge of files, and unstructured data in its archive, and much of it dormant, inactive and sitting on old tapes of a bygone era. Yet, these files and unstructured data have the most potential to be explored, mined and analyzed to realize its value to the organization. In short, the archived data and files must be democratized!

The flip side is, when the archived files and unstructured data are coupled with a slow access interface or unreliable storage infrastructure, the value of archived data is downgraded because of the aggravated interaction between access and applications and business requirements. How would organizations value archived data more if the access path to the archived data is so damn hard???!!!

An interesting solution fell upon my lap some months ago, and putting A and B together (A + B), I believe the access path to archived data can be unbelievably of high performance, simple, transparent and most importantly, remove the BLOODY PAIN of FILE AND DATA MIGRATION!  For storage administrators and engineers familiar with data migration, especially if the size of the migration is into hundreds of TBs or even PBs, you know what I mean!

I have known this solution for some time now, because I have been avidly following its development after its founders left NetApp following their Spinnaker venture to start Avere Systems.

avere_220

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