Data virtualization – Silverton Consulting

Primary data’s path to better data storage presented at SFD8

Posted on November 5, 2015 by Ray in Block Storage, DAS, data access, data mobility, File Storage, NFS, Storage architecture, Storage virtualization, Strategic Inflection Points

A couple of weeks ago we met with Primary Data, Lance Smith, CEO, David Flynn, CTO and Kaycee Lai, SVP Product & Sales who were presenting at Storage Field Day 8 (SFD8, videos of their sessions available here). Primary Data has just emerged out of stealth late last year and has ~$60M in funding. Also they have Steve Wozniak (of Apple fame) as Chief Scientist, but he wasn’t at the SFD8 session 🙁

Primary Data seems out to change the world. At first I thought this was just another form of storage virtualization but they are laser focused on data virtualization or what they call data mobility. It differs from pure storage virtualization by being outside the data path. (I have written about data virtualization before as well as the data hypervisor a long time ago). Nowadays they seem to be using the tag line of data in motion.

Why move data?

David has a theory behind the proliferation of startup storage companies. The spectrum behind capacity and performance has gotten immense, over time, which has provided an opening for a number of companies to address these widening needs.

David believes that caching at the storage system or in the servers is an attempt to address this issue by “loaning” the data from the storage silo to the cache. This is trying to supply a lower cost $/IOP for the data. Similar considerations are apparent at the other side where customer’s use archive or backup services to take advantage of much cheaper $/GB storage.

However, given the difficulty of moving data around in present day storage environments, customer data has become essentially immobile. Primary Data is trying to bring about a data mobility revolution and allow data to move over this spectrum of performance and capacity of storage with ease. Doing so easily, will provide significant benefits as customers can more fully take advantage of the various levels of performance and capacity in their data center storage environments.

Primary Data architecture

Primary Data is providing data mobility by using their meta-data service called the DataSphere appliance and their client software running on host servers called the Data Portal. Their offering can be best explained in three layers:

Data virtualization layer – provides continuity of identity and continuity of access across multiple physical storage systems. That is the same data (identity continuity) can be accessed wherever it resides (access continuity) by server applications. Such access and identity must transcend access protocols and interfaces. The Data Portal client software intercepts the server data activity and does control plane activity using the DataSphere appliance and performs IO directly using the physical storage.
Objective based data management – supplies a data affinity service. That is data can have a temporary location relationship with physical storage depending on the current performance (R:W, IOPS, bandwidth, latency) and protection (durability, availability, disaster recoverability, security, copy-ability, version-ability) characteristics of the data. These data objectives are matched to the capabilities or service catalog of the storage infrastructure and data objectives can change over time
Analytics in the loop – detects the performance and other characteristics of the storage and data in real-time. That is by monitoring the storage IO activity Primary Data can determine the actual performance attribute of the storage. Similarly, by monitoring the applications IO characteristics over time the system can determine the performance objectives of its data. The system also takes advantage of SMI-S to define some of the other characteristics of the storage systems.

How does Primary Data work?

Primary Data has taken advantage of parallel NFS extensions (pNFS) in NFSv4 to externalize and separate the storage control plane from the IO data plane. This works well for native Linux where the main developer of the Linux file system stack is on their payroll. IMG_5608rz

In Windows they put a filter driver in front of SMB to split off the control from data IO plane. Something similar is done for VMware ESX servers to supply the control-data plane split but in this case there is a software defined Data Portal that goes along with the DataSphere Service client that can do it all within the same ESX server. Another alternative exists and that is to use the Data Portal appliance as a storage virtualization service but then the IO data path goes through the portal.

According to their datasheet they currently support data virtualization services for NetApp cDOT and 7-mode, EMC Isilon OneFS7.2, and Nexenta 4.x&5.0 but plan on more.

They are not quite GA yet, but are close.

Comments?

Data virtualization surfaces

Posted on January 9, 2015 by Ray in Block Storage, Cloud services, Clustered storage, DAS, Data, data access, data protection, Data QoS, Distributed computing, File Storage, Object storage, SSD storage, Storage, Storage virtualization, Strategy, Systems

There’s a new storage startup out of stealth, called Primary Data and it’s implementing data (note, not storage) virtualization.

They already have $60M in funding with some pretty highpowered talent from Fusion IO, namely David Flynn, Rick White and Steve Wozniak (the ‘Woz’) (also of Apple fame).

There have been a number of attempts at creating a virtualization layers for data namely ViPR (See my post ViPR virtues, vexations but no storage virtualization) but Primary Data is taking a different tack to the problem.

Data virtualization explained

Essentially they want to separate the data plane from the control plane (See my Data Hypervisor post and comments for another view on this).

The data plane consists of those storage system activities that actually perform IO or read and writes.
The control plane is those storage system activities that do everything else that has to be done by a storage system, including provisioning, monitoring, and managing the storage.

Separating the data plane from the control plane offers a number of advantages. EMC ViPR does this but it’s data plane is either standard storage systems like VMAX, VNX, Isilon etc, or software defined storage solutions. Primary Data wants to do it all.

Their meta data or control plane engine is called a Data Director which holds information about the data objects that are stored in the Primary Data system, runs a data policy management engine and handles data migration.

Primary Data relies on purpose-built, Data Hypervisor (client) software that talks to Data Directors to understand where data objects reside and how to go about accessing them. But once the metadata information is transferred to the client SW, then IO activity can go directly between the host and the storage system in a protocol independent fashion.

[The graphic above is from my prior post and I assumed the data hypervisor (DH) would be co-located with the data but Primary Data has rightly implemented this as a separate layer in host software.]

Data Hypervisor protocol independence?

As I understand it this means that customers could use file storage, object storage or block storage to support any application requirement. This also means that file data (objects) could be migrated to block storage and still be accessed as file data. But the converse is also true, i.e., block data (objects) could be migrated to file storage and still be accessed as block data. You need to add object, DAS, PCIe flash and cloud storage to the mix to see where they are headed.

All data in Primary Data’s system are object encapsulated and all data objects are catalogued within a single, global namespace that spans file, block, object and cloud storage repositories

Data objects can reside on Primary storage systems, external non-Primary data aware file or block storage systems, DAS, PCIe Flash, and even cloud storage.

How does Data Virtualization compare to Storage Virtualization?

There are a number of differences:

Most storage virtualization solutions are in the middle of the data path and because of this have to be fairly significant, highly fault-tolerant solutions.
Most storage virtualization solutions don’t have a separate and distinct meta-data engine.
Most storage virtualization systems don’t require any special (data hypervisor) software running on hosts or clients.
Most storage virtualization systems don’t support protocol independent access to data storage.
Most storage virtualization systems don’t support DAS or server based, PCIe flash for permanent storage. (Yes this is not supported in the first release but the intent is to support this soon.)
Most storage virtualization systems support internal storage that resides directly inside the storage virtualization system hardware.
Most storage virtualization systems support an internal DRAM cache layer which is used to speed up IO to internal and external storage and is in addition to any caching done at the external storage system level.
Most storage virtualization systems only support external block storage.

There are a few similarities as well:

They both manage data migration in a non-disruptive fashion.
They both support automated policy management over data placement, data protection, data performance, and other QoS attributes.
They both support multiple vendors of external storage.
They both can support different host access protocols.

Data Virtualization Policy Management

A policy engine runs in the Data Directors and provides SLAs for data objects. This would include performance attributes, protection attributes, security requirements and cost requirements. Presumably, policy specifications for data protection would include RAID level, erasure coding level and geographic dispersion.

In Primary Data, backup becomes nothing more than object snapshots with different protection characteristics, like offsite full copy. Moreover, data object migration can be handled completely outboard and without causing data access disruption and on an automated policy basis.

Primary Data first release

Primary Data will be initially deployed as an integrated data virtualization solution which includes an all flash NAS storage system and a standard NAS system. Over time, Primary Data will add non-Primary Data external storage and internal storage (DAS, SSD, PCIe Flash).

The Data Policy Engine and Data Migrator functionality will be separately charged for software solutions. Data Directors are sold in pairs (active-passive) and can be non-disruptively upgraded. Storage (directors?) are also sold separately.

Data Hypervisor (client) software is available for most styles of Linux, Openstack and coming for ESX. Windows SMB support is not split yet (control plane/data plane) but Primary data does support SMB. I believe the Data Hypervisor software will also be released in an upcoming version of the Linux kernel.

They are currently in testing. No official date for GA but they did say they would announce pricing in 2015.

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Comments?

Disclosure: We have done work for Primary Data over the past year.

Photo Credits:

Screen shot of beta test system supplied by Primary Data
Graphic created by SCI for prior Data Hypervisor post

Data hypervisor

Posted on August 14, 2012 by Ray in Block Storage, Clustered storage, DAS, Data grid, data logistics, Data QoS, Data transmission, Disk storage, File Storage, Server virtualization, Storage architecture, Storage Features, Storage virtualization, Strategic Inflection Points, System effectiveness

(c) 2012 Silverton Consulting, Inc. All rights reserved

With all this talk of software defined networking and server virtualization where does storage virtualization stand. I blogged about some problems with storage virtualization a week or so ago in my post on Storage Utilization is broke and this post takes it to the next level. Also I was at a financial analyst conference this week in Vail where I heard Mark Lewis of Tekrocket but formerly of EMC discuss the need for a data hypervisor to provide software defined storage.

I now believe what we really need for true storage virtualization is a renewed focus on data hypervisor functionality. The data hypervisor would need both a control plane and a data plane in order to function properly. Ideally the control plane would set up the interface and routing for the data plane hardware and the server and/or backend storage would be none the wiser.

DMs everywhere

I envision a scenario where a customer’s application data is packaged with a data hypervisor which runs on a commodity data switch hardware with data plane and control plane software running on it. Sort of creating (virtual) data machines or DMs.

All enterprise and nowadays most midrange storage provide most of the functionality of a storage control plane such as defining units of storage, setting up physical to logical storage mapping, incorporating monitoring, and management of the physical storage layer, etc. So control planes are pervasive in today’s storage but proprietary.

In addition most storage systems have data plane functionality which operates to connect a host IO request to the actual data which resides in backend storage or internal cache. But again although data planes are everywhere in storage today they are all proprietary to a specific vendor’s storage system.

Data switch needed

But in order to utilize a data hypervisor and create a more general purpose control plane layer, we need a more generic data plane layer that operates on commodity hardware. This is different from today’s SAN storage switches or DCB switches but similar in a some ways.

The functions of the data switch/data plane layer would be to take routing instructions from the control plane layer and direct the server IO request to the proper storage unit using the data plane layer. Somewhere in this world view, probably at the data plane level it would introduce data protection services like RAID or other erasure coding schemes, point in time copy/clone services and replication services and other advanced storage features needed by enterprise storage today.

Also it would need to provide some automated storage movement across and within tiers of physical storage and it would connect server storage interfaces at the front end to storage interfaces at the backend. Not unlike SAN or DCB switches but with much more advanced functionality.

Ideally data switch storage interfaces could attach to dedicated JBOD, Flash arrays as well as systems using DAS storage. In addition, it would be nice if the data switch could talk to real storage arrays on SAN, IP/SANs or NFS&CIFS/SMB storage systems.

The other thing one would like out of a data switch is support for a universal translator that would map one protocol to another, such as iSCSI to SAS, NFS to FC, or FC to NFS and any other combination, depending on the needs of the server and the storage in the configuration.

Now if the data switch were built on top of commodity x86 hardware and software with the data switch as just a specialized application that would create the underpinnings for a true data hypervisor with a control and data plane that could be independent and use anybody’s storage.

Data hypervisor

Assuming all this were available then we would have true storage virtualization. With these capabilities, storage could be repurposed on the fly, added to, subtracted from, and in general be a fungible commodity not unlike server processing MIPs under VMware or Hyper-V.

Application data would then needed to be packaged into a data machine which would offer all the host services required to support host data access. The data hypervisor would handle the linkages required to interface with the control and data layers.

Applications could be configured to utilize available storage at ease and storage could grow, shrink or move to accommodate the required workload just as easily as VMs can be deployed today.

How we get there

Aside from the VMware, Citrix, Microsoft thrusts towards virtual storage there are plenty of storage virtualization solutions that can control most backend enterprise SAN storage. However, the problem with these solutions is that in general the execute only on a specific vendors hardware and don’t necessarily talk to DAS or JBOD storage.

In addition, not all of the current generation storage virtualization solutions are unified. That is most of these today only talk FC, FCoE or iSCSI and don’t support NFS or CIFS/SMB.

These don’t appear to be insurmountable obstacles and with proper allocation of R&D funding, could all be solved.

However the more problematic is that none of these solutions operate on commodity hardware or commodity software.

The hardware is probably the easiest to deal with. Today many enterprise storage systems are built ontop of x86 processor storage controllers. Albeit sometimes they incorporate specialized packaging for redundancy and high availability.

The harder problem may be commodity software. Although the genesis for a few storage virtualization systems might come from BSD or other “commodity” software operating systems. They have been modified over the years to no longer represent anything that can run on standard off the shelf operating systems.

Then again some storage virtualization systems started out with special home grown hardware and software. As such, converting these over to something more commodity oriented would be a major transition.

But the challenge is how to get there from here and would anyone want to take this on. The other problem is that the value add that storage vendors supply currently would be somewhat eroded. Not unlike what happened to proprietary Unix systems with the advent of VMware.

But this will not take place overnight and the company that takes this on and makes a go at it can have a significant software monopoly that would be hard to crack.

Perhaps it will take a startup to do this but I believe the main enterprise storage vendors are best positioned to take this on.

Comments?