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

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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Considerations of Hadoop in the Enterprise

I am guilty. I have not been tendering this blog for quite a while now, but it feels good to be back. What have I been doing? Since leaving NetApp 2 months or so ago, I have been active in the scenes again. This time I am more aligned towards data analytics and its burgeoning impact on the storage networking segment.

I was intrigued by an article posted by a friend of mine in Facebook. The article (circa 2013) was titled “Never, ever do this to Hadoop”. It described the author’s gripe with the SAN bigots. I have encountered storage professionals who throw in the SAN solution every time, because that was all they know. NAS, to them, was like that old relative smelled of camphor oil and they avoid NAS like a plague. Similar DAS was frowned upon but how things have changed. The pendulum has swung back to DAS and new market segments such as VSANs and Hyper Converged platforms have been dominating the scene in the past 2 years. I highlighted this in my blog, “Praying to the Hypervisor God” almost 2 years ago.

I agree with the author, Andrew C. Oliver. The “locality” of resources is central to Hadoop’s performance.

Consider these 2 models:

moving-compute-storage

In the model on your left (Moving Data to Compute), the delivery process from Storage to Compute is HEAVY. That is because data has dependencies; data has gravity. However, if you consider the model on your right (Moving Compute to Data), delivering data processing to the storage layer is much lighter. Compute or data processing is transient, and the data in the compute layer is volatile. Once compute’s power is turned off, everything starts again from a clean slate, hence the volatile stage.

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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

Praying to the hypervisor God

I was reading a great article by Frank Denneman about storage intelligence moving up the stack. It was pretty much in line with what I have been observing in the past 18 months or so, about the storage pendulum having swung back to DAS (direct attached storage). To be more precise, the DAS form factor I am referring to are physical server hardware that houses many disk drives.

Like it or not, the hypervisor has become the center of the universe in the IT space. VMware has become the indomitable force in the hypervisor technology, with Microsoft Hyper-V playing catch-up. The seismic shift of these 2 hypervisor technologies are leading storage vendors to place them on to the altar and revering them as deities. The others, with the likes of Xen and KVM, and to lesser extent Solaris Containers aren’t really worth mentioning.

This shift, as the pendulum swings from networked storage back to internal “direct-attached” storage are dictated by 4 main technology factors:

  • The x86 server architecture
  • Software-defined
  • Scale-out architecture
  • Flash-based storage technology

Anyone remember Thumper? Not the Disney character from the Bambi movie!

thumper-bambi-cartoon-character

When the SunFire X4500 (aka Thumper) was first released in (intermission: checking Wiki for the right year) in 2006, I felt that significant wound inflicted in the networked storage industry. Instead of the usual 4-8 hard disk drives in the all the industry servers at the time, the X4500 4U chassis housed 48 hard disk drives. The design and architecture were so astounding to me, I even went and bought a 1U SunFire X4150 for my personal server collection. Such was my adoration for Sun’s technology at the time.

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No Flash in the pan

The storage networking market now is teeming with flash solutions. Consumers are probably sick to their stomach getting a better insight which flash solution they should be considering. There are so much hype, fuzz and buzz and like a swarm of bees, in the chaos of the moment, there is actually a calm and discerning pattern slowly, but surely, emerging. Storage networking guys would probably know this thing well, but for the benefit of the other readers, how we view flash (and other solid state storage) becomes clear with the picture below: Flash performance gap

(picture courtesy of  http://electronicdesign.com/memory/evolution-solid-state-storage-enterprise-servers)

Right at the top, we have the CPU/Memory complex (labelled as Processor). Our applications, albeit bytes and pieces of them, run in this CPU/Memory complex.

Therefore, we can see Pattern #1 showing up. Continue reading