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Storage changes in vSphere 5.5 announced at VMworld 2013

VMworld2013 is going on in San Francisco this week. The big news is the roll out of network virtualization in NSX and vCloud Hybrid Service (vCHS) but there were a few tidbits in the storage arena worth discussing.

Virtual SAN public beta – VSAN was released as a public beta and customers can now download a copy of VSAN from www.vsanbeta.com. VSAN will construct a pool of storage out of local attached disks and flash across two or more hosts. It uses the flash as a read-write cache for the local disks. With VSAN customers can elect to have multiple tiers of storage be supported within a single VSAN pool, as well as support different availability (replication) levels, and some other, select characteristics. VSAN can easily scale in performance and capacity by just adding more hosts that have local storage. Now all that stranded local storage and flash server level resources can be used as a VM storage pool. VMware stated that they see VSAN as usefull for tier 2/tier 3 application storage and/or backup-archive storage uses. However they showed one chart with a View Planner application simulation using a 3-host VSAN (presumably with lots of SSD and disk storage) compared against an all-flash array (vendor unknown). In this benchmark the VSAN exactly matched the all-flash external storage in performance (VMs supported). [late update] Lot’s of debate on what VSAN means to enterprise storage but it appears to be a limited in scope and mainly focused on SMB applications. Chad Sakac did a (real) lengthy post on EMC’s perspective on VSAN and Software Defined Storage if you want to know more check it out.
Virsto – VMware announced GA of Virsto which uses any external storage and creates a new global storage pool out of them. Apparently, it maps a log structured file system across the external SAN storage. By doing this it sequentializes all the random write IO coming off of ESX hosts. It supports thin provisioning, snapshot and read-write clones. One could see this as almost a write cache for VM IO activity but read IOs are also by definition spread across (extremely wide striped) across the storage pool which should improve read performance as well. You configure external storage as normal and present those LUNs to Virsto which then converts that storage pool into “vDisks” which can then be configured as VM storage. Probably more to see here but it’s available today. Before acquisition one had to install Virsto into each physical host that was going to define VMs using Virsto vDisks. It’s unclear how much Virsto has been integrated into the hypervisor but over time one would assume like VSAN this would be buried underneath the hypervisor and be available to any vSphere host.
vSphere Flash Read Cache – customers with PCIe flash cards and vCenter Ops Manager, can now use them to support a read cache for data access. vSphere Flash Read Cache is apparently vmotion aware such that as you move VMs from one ESX host to another the read cache buffer will move with it. Flash Read Cache is transparent to the VMs and can be assigned on a VMDK basis.
vSphere 5.5 low-latency support – unclear what VMware actually did but they now claim vSphere 5.5 now supports low latency applications, like FinServ apps. They claim to have reduced the “jitter” or variability in IO latency that was present in previous versions of vSphere. Presumably they shortened the IO and networking paths through the hypervisor which should help. I suppose if you have a VMDK which ends up on an SSD storage someplace one can have a more predictable response time. But the critical question is how much overhead does the hypervisor IO path add to the base O/S. When all-flash arrays now sporting latencies under 100 µsecs, adding another 10 or 100 µsecs can make a big difference. In VMware’s quest to virtualize any and all mission critical apps, low-latency apps are one of the last bastions of physical server apps left to conquer. Consider this a step to accommodate them.
vVols – VMware keeps talking about vVols as an attempt to extend their VSAN “policy driven control plane” functionality out to networked storage but there’s still no GA yet. The (VASA 2 or vVol) spec’s seem to be out for awhile now, and I have heard from at least two “major” vendors that they have support in place today but VMware still isn’t announcing formal availability yet. Unclear what the hold up is, but maybe the spec’s are more in a state of flux than what’s depicted externally.

Most of this week was spent talking about NSX, VMware’ network virtualization and vCloud Hybrid Services. When they flashed the list of NSX partners on the screen Cisco was absent. Not sure what this means but perhaps there’s some concern that NSX will take revenue away from Cisco.

As for vCHS apparently this is a VMware run public cloud with two now expanding to three data centers in US, that customers can use to support their own hybrid cloud services. VMware announced that SAVVIS is now offering vCHS services as well as VMware with data centers in NY and Chicago. There was some talk about vCHS offering object storage services like Amazon’s S3 but there was nothing specific about when. [Late update] Pat did mention that a future offering will provide DR-as-a-Service using vCHS as a target for SRM. That seems to be matching what Microsoft seems to be planning for Azzure and Hyper-V DR.

That’s about it as far as I can tell. Didn’t hear any other news on storage changes in vSphere 5.5. But this is the year of network virtualization. Can’t wait to see what they roll out next year.

Peak server, the cloud & NetApp storage for AWS

Posted on June 13, 2013June 15, 2013 by Ray in Cloud services, Cloud storage, DAS, Data, data protection, Networking, Server virtualization, Software Defined Network, SSD storage, Storage, Storage Features, Strategic Inflection Points, Strategy, Systems

I was at a conference a month or so ago and one speaker mentioned that the number of x86 servers being sold has peaked and is dropping. I can imagine a number of reasons for this and the main one being server virtualization. But this speaker had a different view and it seemed to be the cloud.

Peak server is here.

He said that three companies were purchasing over 1/2 the x86 servers these days. I feel that there should be at least four Google, Facebook, Amazon & Microsoft and maybe five, if you add in Apple.

Something has happened over the past year or so. Enterprise IT has continued along its merry way but the adoption of cloud services is starting to take off.

I have seen this before, with mainframes, then mini-computers, and now client-server. Minicomputers came out and were so easy to use and develop/deploy applications on, that people stopped creating new apps on the mainframe. Mainframes never died out, and probably have never really stopped shipping increasing MIPS every year. But the share of WW MIP installations for mainframes has been shrinking for decades and have never got going again.

Ultimately, the proprietary minicomputer was just a passing fad and only lasted about 25 years or so. It was wounded by the PC, and then killed off by proprietary Unix workstations.

Then it happened again, the new upstart this time was Windows Server and Linux. Once again it was just easier to build apps on these new and cheaper servers, than any of the older Unix servers. Of course there’s still plenty of business in proprietary Unix servers, but again I would venture to say that their share of WW installed MIPS has been shrinking for a long time.

Nowadays, the cloud is mortally wounding the server market. Server virtualization is helping a lot but it’s also enabling the cloud to eliminate many physical server sales. This is because new applications, new IT environments are being ported/moved/deployed onto the cloud.

Peak server means less enterprise networking, storage and server hardware

In this new, cloud world, customers need less servers, less networking and less enterprise class storage. Yes not every application is suitable to cloud deployment but that’s why there’s still mainframes, still Unix servers, and a continuing need for standalone, physical or virtual x86 servers in the enterprise. But their share of MIPs will start shrinking soon if it hasn’t already.

Ok, so enterprise data center share of MIPs will start shrinking vis a vis cloud data centers. But what happens to networking and storage. My view is that networking becomes software defined and there’s a component of that which operates on special purpose hardware. This will increase in shipments but the more complex, enterprise class networking equipment will flatline and never see any more substantial growth.

And up until yesterday I felt much the same about enterprise class storage. Software defined storage in my future, DAS and SSDs for the capacity and the smarts exist in software if at all. Today, most of the cloud and many service providers have been moving off enterprise class storage and onto DAS.

NetApp’s new enterprise storage in AWS

But yesterday I heard about NetApp private storage for the cloud. This is a configuration of NetApp storage installed in a CoLo facility with a “direct connection” to Amazon compute cloud. In this way, enterprise customers can maintain data stewardship/ownership/governance over their data while at the same time deploying applications onto AWS compute cloud.

This seems to be one of the sticking points to enterprise customers adopting the cloud. By having (data) storage owned lock/stock&barrel by the enterprise it seems much easier and less risky to deploy new and old applications to the cloud.

Whether this pans out and can provide enough value to cover the added expense of the enterprise class storage, only the market can decide. But this is the first time I can remember, where any vendor has articulated a role for enterprise class storage in the cloud. Let’s hope it works.

Image: PDP8/s by ajmexico

Windows Server 2012 R2 storage changes announced at TechEd

Posted on June 6, 2013September 8, 2013 by Ray in CIFS/SMB, Cloud storage, DAS, desktop virtualization, Ethernet, File Storage, RDMA, RoCE, Server virtualization, SSD storage, Storage performance

Microsoft TechEd USA is this week and they announced a number of changes to the storage services that come with Windows Server 2012 R2

Azure DRaaS – Microsoft is attempting to democratize DR by supporting a new DR-as-a-Service (DRaaS). They now have an Azure service that operates in conjunction with Windows Server 2012 R2 that provides orchestration and automation for DR site failover and fail back to/from remote sites. Windows Server 2012 R2 uses Hyper-V Replica to replicate data across to the other site. Azure DRaaS supports DR plans (scripts) to identify groups of Hyper-V VMs which need to be brought up and their sequencing. VMs within a script group are brought up in parallel but different groups are brought up in sequence. You can have multiple DR plans, just select the one to execute. You must have access to Azure to use this service. Azure DR plans can pause for manual activities and have the ability to invoke PowerShell scripts for more fine tuned control. There’s also quite a lot of setup that must be done, e.g. configure Hyper-V hosts, VMs and networking at both primary and secondary locations. Network IP injection is done via mapping primary to secondary site IP addresses. The Azzure DRaaS really just provides the orchestration of failover or fallback activity. Moreover, it looks like Azure DRaaS is going to be offered by service providers as well as private companies. Currently, Azure’s DRaaS has no support for SAN/NAS replication but they are working with vendors to supply an SRM-like API to provide this.
Hyper-V Replica changes – Replica support has been changed from a single fixed asynchronous replication interval (5 minutes) to being able to select one of 3 intervals: 15 seconds; 5 minutes; or 30 minutes.
Storage Spaces Automatic Tiering – With SSDs and regular rotating disk in your DAS (or JBOD) configuration , Windows Server 2012 R2 supports automatic storage tiering. At Spaces configuration time one dedicates a certain portion of SSD storage to tiering. There is a scheduled Windows Server 2012 task which is then used to scan the previous periods file activity and identify which file segments (=1MB in size) that should be on SSD and which should not. Then over time file segments are moved to an appropriate tier and then, performance should improve. This only applies to file data and files can be pinned to a particular tier for more fine grained control.
Storage Spaces Write-Back cache – Another alternative is to dedicate a certain portion of SSDs in a Space to write caching. When enabled, writes to a Space will be cached first in SSD and then destaged out to rotating disk. This should speed up write performance. Both write back cache and storage tiering can be enabled for the same Space. But your SSD storage must be partitioned between the two. Something about funneling all write activity to SSDs just doesn’t make sense to me?!
Storage Spaces dual parity – Spaces previously supported mirrored storage and single parity but now also offers dual parity for DAS. Sort of like RAID6 in protection but they didn’t mention the word RAID at all. Spaces dual parity does have a write penalty (parity update) and Microsoft suggests using it only for archive or heavy read IO.
SMB3.1 performance improvements of ~50% – SMB has been on a roll lately and R2 is no exception. Microsoft indicated that SMB direct using a RAM DISK as backend storage can sustain up to a million 8KB IOPS. Also, with an all-flash JBOD, using a mirrored Spaces for backend storage, SMB3.1 can sustain ~600K IOPS. Presumably these were all read IOPS.
SMB3.1 logging improvements – Changes were made to SMB3.1 event logging to try to eliminate the need for detail tracing to support debug. This is an ongoing activity but one which is starting to bear fruit.
SMB3.1 CSV performance rebalancing – Now as one adds cluster nodes, Cluster Shared Volume (CSV) control nodes will spread out across new nodes in order to balance CSV IO across the whole cluster.
SMB1 stack can be (finally) fully removed – If you are running Windows Server 2012, you no longer need to install the SMB1 stack. It can be completely removed. Of course, if you have some downlevel servers or clients you may want to keep SMB1 around a bit longer but it’s no longer required for Server 2012 R2.
Hyper-V Live Migration changes – Live migration can now take advantage of SMB direct and its SMB3 support of RDMA/RoCE to radically speed up data center live migration. Also, Live Migration can now optionally compress the data on the current Hyper-V host, send compressed data across the LAN and then decompress it at target host. So with R2 you have three options to perform VM Live Migration traditional, SMB direct or compressed.
Hyper-V IO limits – Hyper-V hosts can now limit the amount of IOPS consumed by each VM. This can be hierarchically controlled providing increased flexibility. For example one can identify a group of VMs and have a IO limit for the whole group, but each individual VM can also have an IO limit, and the group limit can be smaller than the sum of the individual VM limits.
Hyper-V supports VSS backup for Linux VMs – Windows Server 2012 R2 has now added support for non-application consistent VSS backups for Linux VMs.
Hyper-V Replica Cascade Replication – In Windows Server 2012, Hyper V replicas could be copied from one data center to another. But now with R2 those replicas at a secondary site can be copied to a third, cascading the replication from the first to the second and then the third data center, each with their own replication schedule.
Hyper-V VHDX file resizing – With Windows Server 2012 R2 VHDX file sizes can now be increased or reduced for both data and boot volumes.
Hyper-V backup changes – In previous generations of Windows Server, Hyper-V backups took two distinct snapshots, one instantaneously and the other at quiesce time and then the two were merged together to create a “crash consistent” backup. But with R2, VM backups only take a single snapshot reducing overhead and increasing backup throughput substantially.
NVME support – Windows Server 2012 R2 now ships with a Non-Volatile Memory Express (NVME) driver for PCIe flash storage. R2’s new NVME driver has been tuned for low latency and high bandwidth and can be used for non-clustered storage spaces to improve write performance (in a Spaces write-back cache?).
CSV memory read-cache – Windows Server 2012 R2 can be configured to set aside some host memory for a CSV read cache. This is different than the Spaces Write-Back cache. CSV caching would operate in conjunction with any other caching done at the host OS or elsewhere.

That’s about it. Some of the MVPs had a preview of R2 up in Redmond, but all of this was to be announced in TechEd, New Orleans, this week.

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Image: Microsoft TechEd by BetsyWeber

EMCworld 2013 Day 3

Posted on May 8, 2013 by Ray in Block Storage, Disk storage, Distributed computing, File Storage, Server virtualization, SSD storage, Storage architecture, Storage Features, Storage performance, Strategic Inflection Points

Rich Napolitano, President Unified Storage Division got up and showed some technology demonstrations of what they had working in their labs. Rich had some of his long time engineers up on the stage to show what was running in their labs.

First up was a dual controller, dual processors per controller 8 core processing chips (32cores in all) running against an all SSD backend. The configuration was up for a short time but it seemed like 96 SSDs, so an all-flash VNX array. They used Iometer, random-8KB IO to drive almost 975K IOPS at sub-msec. response time. They hit 1M IOPS with just slightly above 1 msec. response time. You could see the processor utilization of the 32 cores going up as the workload reached higher levels. Couldn’t see precisely but all the cores were running at ~70-80% busy at the 1Miops level and it seemed like the system performance was entering the knee-of-the-curve
Next up was the new VNX data app store demonstration. Similar to iPhone and Android App stores. EMC has identified a select set of apps that can be run directly on VNX hardware. The current demonstration had two versions of anti-virus, Recover Point Virtual Appliance (vRPA), (v?)VPLEX, CloudAccess and MySQL server. The engineers showed how AV software could be installed and be running on the VNX as well as how vRPA could be installed and provide onboard replication services.
Then, they demonstrated a VNX virtual appliance (vVNX?) which was able to run on white box server which I think was running ESX. In this case, vVNX was running with onboard DAS storage but had all the advanced functionality of VNX
Finally, they showed a vVNX running in a cloud services environment. Not sure if this was VMware vCloud or some other compute cloud but Rich stated that they will support many clouds. With vVNX running in the cloud accessing storage behind the compute engine it’s unclear what the performance would be and how one would access the storage (file or iSCSI no doubt) but it did open up new possibilities as to where one could run VNX services.

It’s readily apparent that the next iteration of VNX software seems focused on taking advantage of multi-core processing (called MCx) to boost storage system performance, providing a virtualized environment within the VNX engine to run specialized data services and supplying a new vVNX functionality which can be deployed just about anywhere you would want.

That’s all for the public sessions, spent much of the rest of the day in NDA sessions.

I had a good time at EMCworld 2013, seeing old friends again and meeting new ones and thank EMC for inviting me. For information on previous days at EMCworld 2013 please see my Day 1 and Day 2 posts.

EMCworld 2013 Day 2

Posted on May 7, 2013 by Ray in Cloud services, desktop virtualization, Information economy, Internet traffic, Mobile computing, R&D measures, Server virtualization, Software Defined Network, Visionary leadershp

The first session of the day was with Joe Tucci EMC Chairman and CEO. He talked about the trends transforming IT today. These include Mobile, Cloud, Big Data and Social Networking. He then discussed IDC’s 1st, 2nd and 3rd computing platform framework where the first was mainframe, the second was client-server and the third is mobile. Each of these platforms had winers and losers. EMC wants definitely to be one of the winners in the coming age of mobile and they are charting multiple paths to get there.

Mainly they will use Pivotal, VMware, RSA and their software defined storage (SDS) product to go after the 3rd platform applications. Pivotal becomes the main enabler to help companies gain value out of the mobile-social networking-cloud computing data deluge. SDS helps provide the different pathways for companies to access all that data. VMware provides the software defined data center (SDDC) where SDS, server virtualization and software defined networking (SDN) live, breathe and interoperate to provide services to applications running in the data center.

Joe started talking about the federation of EMC companies. These include EMC, VMware, RSA and now Pivotal. He sees these four brands as almost standalone entities whose identities will remain distinct and seperate for a long time to come.

Joe mentioned the internet of things or the sensor cloud as opening up new opportunities for data gathering and analysis that dwarfs what’s coming from mobile today. He quoted IDC estimates that says by 2020 there will be 200B devices connected to the internet, today there’s just 2 to 3B devices connected.

Pivotal’s debut

Paul Maritz, Pivotal CEO got up and took us through the Pivotal story. Essentially they have three components a data fabric, an application development fabric and a cloud fabric. He believes the mobile and internet of things will open up new opportunities for organizations to gain value from their data wherever it may lie, that goes well beyond what’s available today. These activities center around consumer grade technologies which 1) store and reason over very large amounts of data; 2) use rapid application development; and 3) operate at scale in an entirely automated fashion.

He mentioned that humans are a serious risk to continuous availability. Automation is the answer to the human problem for the “always on”, consumer grade technologies needed in the future.

Parts of Pivotal come from VMware, Greenplum and EMC with some available today in specific components. However by YE they will come out with Pivotal One which will be the first framework with data, app development and cloud fabrics coupled together.

Paul called Pivotal Labs as the special forces of his service organization helping leading tech companies pull together the awesome apps needed for the technology of tomorrow, consisting of Extreme programming, Agile development and very technically astute individuals. Also, CETAS was mentioned as an analytics-as-a-service group providing such analytics capabilities to gaming companies doing log analysis but believes there’s a much broader market coming.

Paul also showed some impressive numbers on their new Pivotal HD/HAWQ offering which showed it handled many more queries than Hive and Cloudera/Impala. In essence, parts of Pivotal are available today but later this year the whole cloud-app dev-big data framework will be released for the first time.

Next up was a media-analyst event where David Goulden, EMC President and COO gave a talk on where EMC has come from and where they are headed from a business perspective.

Then he and Joe did a Q&A with the combined media and analyst community. The questions were mostly on the financial aspects of the company rather than their technology, but there will be a more focused Q&A session tomorrow with the analyst community.

Joe was asked about Vblock status. He said last quarter they announced it had reached a $1B revenue run rate which he said was the fastest in the industry. Joe mentioned EMC is all about choice, such as Vblock different product offerings, VSpex product offerings and now with ViPR providing more choice in storage.

Sometime today Joe had mentioned that they don’t really do custom hardware anymore. He said of the 13,000 engineers they currently have ~500 are hardware engineers. He also mentioned that they have only one internally designed ASIC in current shipping product.

Then Paul got up and did a Q&A on Pivotal. He believes there’s definitely an opportunity in providing services surrounding big data and specifically mentioned CETAS as offering analytics-as-a-service as well as Pivotal Labs professional services organization. Paul hopes that Pivotal will be $1B revenue company in 5yrs. They already have $300M so it’s well on its way to get there.

Next, there was a very interesting media and analyst session that was visually stimulating from Jer Thorp, co-founder of The Office for Creative Research. And about the best way to describe him is he is a data visualization scientist.

He took some NASA Kepler research paper with very dry data and brought it to life. Also he did a number of analyzes of public Twitter data and showed twitter user travel patterns, twitter good morning analysis, twitter NYT article Retweetings, etc. He also showed a video depicting people on airplanes around the world. He said it is a little known fact but over a million people are in the air at any given moment of the day.

Jer talked about the need for data ethics and an informed data ownership discussion with people about the breadcrumbs they leave around in the mobile connected world of today. If you get a chance, you should definitely watch his session.

Next Juergen Urbanski, CTO T-Systems got up and talked about the importance of Hadoop to what they are trying to do. He mentioned that in 5 years, 80% of all new data will land on Hadoop first. He showed how Hadoop is entirely different than what went before and will take T-Systems in vastly new directions.

Next up at EMCworld main hall was Pat Gelsinger, VMware CEO’s keynote on VMware. The story was all about Software Defined Data Center (SDDC) and the components needed to make this happen. He said data was the fourth factor of production behind land, capital and labor.

Pat said that networking was becoming a barrier to the realization of SDDC and that they had been working on it for some time prior to the Nicera acquisition. But now they are hard at work merging the organic VMware development with Nicera to create VMware NSX a new software defined networking layer that will be deployed as part of the SDDC.

Pat also talked a little bit about how ViPR and other software defined storage solutions will provide the ease of use they are looking for to be able to deploy VMs in seconds.

Pat demo-ed a solution specifically designed for Hadoop clusters and was able to configure a hadoop cluster with about 4 clicks and have it start deploying. It was going to take 4-6 minutes to get it fully provisioned so they had a couple of clusters already configured and they ran a pseudo Hadoop benchmark on it using visual recognition and showed how Vcenter could be used to monitor the cluster in real time operations.

Pat mentioned that there are over 500,000 physical servers running Hadoop. Needless to say VMware sees this as a prime opportunity for new and enhanced server virtualization capabilities.

That’s about it for the major keynotes and media sessions from today.

Tomorrow looks to be another fun day.

EMCworld 2013 day 1

Posted on May 6, 2013 by Ray in Block Storage, Cloud services, Cloud storage, DAS, Disk storage, Distributed computing, File Storage, Information economy, Market dynamics, Mobile computing, Object storage, Server virtualization, Software Defined Network, SSD storage, Storage, Storage architecture, Storage virtualization, Strategic Inflection Points, System effectiveness

Lines for coffee at the Cafe were pretty long this morning and I missed my opportunity to have breakfast to do some work. But eventually made my way to the press room and got some food and coffee.

Spent the morning in Analyst sessions mostly under NDA but it seems safe to say that EMC sees plenty of opportunity ahead.

The first session Q&A with BRS executives and customers was enlightening but the main message from the customers was that data protection is hard, legacy systems often can’t adjust quick enough and sometimes a completely new architecture is warranted. The executives were upbeat about current BRS business and where they were headed in the future.

Rest of the morning was with Jeremy Burton EVP Product, Operations and Marketing and John Roese, the new SVP and CTO of EMC (6 months on the job). Jeremy talked about an IDC insight that there’s a new world emerging so-called 3rd platform applications based on mobile and consumer grade technology with literally billions of users, millions of apps built on mobile-cloud-bigdata-social infrastructure which complements the 2nd platform built on lan/wan, client server frameworks.

For an example of this environment Jeremy mentioned that AT&T provisions 12PB of storage a month.

What’s needed for this new platform is a new type of storage built for the 3rd platform but taking advantage of current enterprise storage characteristics. This is ViPR (more on that later)

John comes by way of Huawei, Nortel and myriad others and offers a broad insight to the way forward for EMC. It looks like a bright future ahead if they can do half of what John has outlined.

John talked about the intersections between the carrier market (or services), enterprise IT and consumer market. There is convergence between these regions and at each of these intersections new technology is going to answer many of the problems which exist. For instance in the carrier space:

The amount of information they gather is frightening they know everything about you. Pivotal will be the key here because its good at 1) ability to correlate information across different information sources. Most carriers have a whole bunch of disparate information stores; and 2) It’s not just focused on Big Data as a non-realtime problem but also provides realtime analytics as well.
Capital costs are going down but $/bits are going way down. VMware & Software defined data center is the right way to drive down costs. Today servers are ~50% virtualized but networking is not virtualized at all.
Customers are dissatisfied with service providers (carriers). Again Pivotal is key here. One carrier customer was focused on customer churn and tried to figure out how to minimize this. They used Gemfire’ high speed infrastructure that could watchc all transactions on cell tower infrastructure pick out dropped calls, send it to Greenplum and correlate this with the customer attributes (good or bad), and within 100msec supply an interaction with the customer in to apologize and offer some services to make it better.
Internet is the new wild west –use at your own risk, spoofing websites, respond to email could be anyone, chaos to security. RSA can become the trusted internet provider by looking at the internet holistically, combining information from many customers, aggregating and sharing these interactions to deterimine the trust of every transaction. Trust is becoming a new big data problem.
Hybrid and public cloud is their biggest opportunity but they don’t know how to attack it. VMware and SDDC will evolve to provide orchestrated movement from private to public and closed to open.

The thinking seems pretty straightforward given what they are trying to accomplish and the framework he applied to EMC’s strategy going forward made a lot of sense.

Brian Gallagher did a keynote on enterprise storage new functions and features which covered VMAX, VPLEX, RecoverPoint, and XtremIO/SF/SW. Mentioned RecoverPoint virtual appliance and sort of a statement of direction on being able to move application functionality directly on VMAX. He kind of demoed this with VPLEX running on VMAX.

He also talked about FAST speed of reaction versus the competition, mentioned that FAST provides information about the storage tiering to up to 4 different VMAX arrays. Showed a comparison of VMAX 10K against another prime competitor that looked downright embarrassing. And talked about VMAX cloud edition.

After that 1 on 1 meetings all under strict NDA. But then the big Keynote with Jeremy again and David Goulden President and COO on ViPR. They have implemented software defined storage (SDS). Last week I did a post on SDS trying to layout some of the problems and promises of SDS (please see The promise of SDS post).

But what I missed was the data path transformation that ViPR can do to provide object and HDFS access to traditional and commodity storage systems. ViPR starts out primarily in the control layer providing automated provisioning, self management, across heterogeneous storage pools. With ViPR one can define virtual storage arrays and then configure virtual storage pools across those arrays regardless of the physical infrastructure underneath them.

More on ViPR in a separate post but suffice it to say EMC has been working on this for awhile now. But how it’s positioned with VPLEX and the other storage virtualization capabilities in VMAX and other products is another matter. But it seems they are carving out a space for ViPR between and above the current storage solutions.

End of day one is in the Expo and then cocktail parties… stay tuned for day 2.

The promise of software defined storage

Posted on May 3, 2013May 3, 2013 by Ray in Server virtualization, Software Defined Network, Storage, Storage performance, Storage utilization, Storage virtualization, System effectiveness

Data hypervisor, software defined storage, data plane, control plane — (c) 2012 Silverton Consulting, Inc. All rights reserved

Not sure why but all the hype around software defined storage seems to be reaching a crescendo. Possible due to conference season coming up but it started earlier this year. I attended an SNW analyst session that was talking about software defined storage had on its panel technical people from HDS, IBM, Data Core and VMware. It seems the distinction between storage virtualization and software defined storage is getting slimmer every time we talk about it. I have written before about software defined storage (see my Data Hypervisor post).

Server, networking and storage virtualization today

Server virtualization makes an awful lot of sense, has made lots of money and arguably been around for decades now especially in mainframe systems. Servers have so much power today that dedicating one to a single workload just doesn’t make any sense anymore.

Network virtualization from OpenFlow and others also makes a lot of sense (see OpenFlow the next wave in networking and OpenFlow part 2, Cisco’s response posts). Here we aren’t necessarily boosting network utilization as much as changing resource allocation to deal with altered traffic flows. That and the fact that provisioning, monitoring and other management characteristics can now be under pragmatic control from the user makes these systems very appealing. Especially, to organizations that exhibit varying network activity over time.

Storage virtualization has been around for a long time too and essentially places a storage system abstraction layer on top of a group of other, heterogeneous storage systems. This provides a number of capabilities such as allowing data to be migrated from one storage system to another without host knowledge or intervention. Other storage virtualization features include, centralized, management, common storage features, different storage personalities (protocols), etc. But just being able to migrate data from one storage system to another without host intervention or knowledge provides an awful lot of value, especially to large data centers which refresh technology frequently.

Software defined storage compared to server virtualization

Software defined storage seems to imply some ability to marry storage virtualization services to RESTful and other APIs which would allow programatic storage provisioning, monitoring and management. This would allow data centers to manage and control their storage without involving storage administrators in day-to-day activities.

When I compare this to server virtualization the above described capabilities really don’t increase storage utilization much. Yes, by automating provisioning or even running thin provisioning one can potentially boost storage capacity utilization but you really haven’t increased the IO utilization much by doing this.

Looking under the covers of most storage systems one might find that CPU cores are pretty idle, but data paths and storage devices are typically running flat out. One problem is that today’s enterprise storage subsystems are already highly shared across applications and users. So there is really no barrier to sharing these resources as widely as they can. As such, storage system IOPS and/or bandwidth utilization is already pretty high. I would say a typical enterprise application environment storage subsystem performance usually runs above 30% and reaching 50% or more during peak time periods. Increasing IOPS utilization much beyond that risks seriously impacting peak performance periods.

Now if somehow one could migrate slower data around a complex to lower performing storage when there’s no need for high performance and higher performing data to higher performing storage when there is a need then that could help increase performance utilization considerably. But, many storage systems already do this internally through automated storage tiering and even some can do this across storage systems using storage virtualization.

But the underlying problem here is that in takes a lot of time, resources and effort to move TBs of data around a data center, especially when its doing other work. So other than something akin to storage tiering across storage systems we are unlikely to see much increase in storage performance utilization with a gaggle of multiple storage systems. I suppose in the future moving TB of data may take much less time & resources than today but then the problem becomes moving PB of data around.

Software defined storage compared to network virtualization

When I compare the above capabilities to network virtualization it doesn’t look very similar. There’s really no way to change the storage performance to optimize it for one direction (or application) at this instant and then move storage performance around to another application a couple of hours later. Yes, again automated storage tiering can do this, and yes some of these systems can tier across storage systems using storage virtualization but in general barring storage tiering there’s nothing like this available today.

Maybe if inside a storage system the data paths could somehow be programatically reconfigured to offer say more internal bandwidth to the Device-to-Cache path vs. the Cache-to-Frontend path. Changing or reconfiguring data path resources like this could certainly optimize the internal performance of a storage system and this would be a worthwhile feature of any software defined storage. Knowing which is more important to one application and less important to all the others will take some smarts, across the storage system and host O/S but it’s certainly feasible. So, with RESTful interfaces, APIs or application hints data paths could be reconfigurations on demand to support applications that are all vieing for IO activity.

With these sorts of capabilities software defined storage starts to look a little more like software defined networking.

Software defined storage on its own

But in the end we always reach a fundamental limit of IO capabilities in today’s storage systems which is the devices. Yes you can have 2000 or more devices in high-end storage today and yes you can have all-flash arrays. However, most storage systems are configured to keep whatever devices they have pretty busy as much of the time as possible.

Until we create some sort of storage device that can provide more performance than most applications can ever use, even when they are shared via a storage system, software defined storage capabilities will be limited. Today’s SSDs have certainly boosted performance considerably but this just means that most applications that warrant all flash arrays are performing faster. It just so happens that some applications can take all the performance you throw at them and still want more.

I suppose if SSDs cost were to come down to match NL-SAS storage prices and still maintain the 100X faster IOP rate, then maybe a storage system built on such devices could be more “software defined” than others. And maybe that’s where everyone is headed, believing NAND/SSD price trends will drive costs down so much that everyone can have all the IOPS performance they will ever need out of a single storage system.

Yet, this still just looks like shared storage we have today, only more of it. So we return back to our roots and see that software defined storage is just another way to add more storage sharing. Storage virtualization is nice, new more programmatical storage systems is even better but faster-cheaper storage devices is best of all.

So what we really need is much cheaper SSDs to realize the full promise of software defined storage. In the mean time opening up APIs and providing RESTful interfaces to provide programatic interfaces to provisioning, monitoring, managing and tuning storage system data paths and other performance characteristics are all we can hope for.

Comments?

Thinly provisioned compute clouds

Posted on March 13, 2013 by Ray in Cloud services, Distributed computing, Processing performance, Server virtualization, Strategic Inflection Points

Thin provisioning has been around in storage since StorageTek’s Iceberg hit the enterprise market in 1995. However, thin provisioning has never taken off for system servers or virtual machines (VMs).

But recently a paper out of MIT Making cloud computing more efficient discusses some recent research that came up with the idea of monitoring system activity to model and predict application performance.

So how does this enable thinly provision VMs?

With a model like this in place, one could concievably provide a thinly provisioned virtual server that could guarantee a QoS and still minimize resource consumption. For example, have the application VM just consume the resources needed at any instant in time which could be adjusted as demands on the system change. Thus, as an application needs grew, more resources could be supplied and as needs shrink, resources could be given up for other uses.

With this sort of server QoS, certain classes of application VMs would need to have variable or no QoS to be sacrificed in times of need to those that required guaranteed QoS. But in a cloud service environment a multiplicity of service classes like these could be supplied at different price points.

Thin provisioning grew up in storage because it’s relatively straightforward for a storage subsystem to understand capacity demands at any instant in time. A storage system only needs to monitor data write activity and if a data block was written or consumed then it would be backed by real storage. If it had never been written, then it was relatively easy to fabricate a block of zeros if it ever was read.

Prior to thinly provisioned storage, fat provisioning required that storage be configured to the maximum capacity required of it. Similarly, with fully (or fat) provisioned VMs, they must be configured for peak workloads. With the advent of thin provisioning on storage wasted resources (capacity in the case of storage) could be shared across multiple thinly provisioned volumes (LUNs) thereby freeing up these resources for other users.

Problems with server thin provisioning

I see some potential problems with the model and my assumptions as to how thinly provisioned VM would wore. First, the modeled performance is a lagging indicator at best. Just as system transactions start to get slower, a hypervisor would need to interrupt the VM to add more physical (or virtual) resources. Naturally during the interruption system performance would suffer.

It would be helpful if resources could be added to a VM dynamically, in real time without impacting the applications running in the VM. But it seems to me that adding physical or virtual CPU cores, memory, bandwidth, etc., to a VM would require at least some sort of interruption to a pair of VMs [the one giving up the resource(s) and the one gaining the freed up resource(s)].

Similar issues occur for thinly provisioned storage. As storage is consumed for a thinly provisioned volume, allocating more physical capacity takes some amount of storage subsystem resources and time to accomplish.

How does the model work?

It appears that the software model works by predicting system performance based on a limited set of measurements. Indeed, their model is bi-modal. That is there are two approaches:

Black box model – tracks server or VM indictors such as “number and type of user requests” as well as system performance and uses AI to correlate the two. This works well for moderate fluctuations in demand but doesn’t help when requests for services falls beyond those boundaries.
Grey box model – is more sophisticated and is based on an understanding of a specific database functionality, such as how frequently they flush host buffers, commit transactions to disk logs, etc. In this case, they are able to predict system performance when demand peaks at 4X to 400X current system requirements.

They have implemented the grey box model for MySQL and are in the process of doing the same for PostGres.

Model validation and availability

They tested their prediction algorithm against published TPC-C benchmark results and were able to come within 80% accuracy for CPU use and 99% accuracy for disk bandwidth consumption.

It appears that the team has released their code as open source. At least one database vendor, Teradata is porting it over to their own database machine to better allocate physical resources to data warehouse queries.

It seems to me that this would be a natural for cloud compute providers and even more important for hypervisor solutions such as vSphere, Hyper-V, etc. Anyplace one could use more flexibility in assigning virtual or physical resources to an application or server would find use for this performance modeling.

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Now, if they could just do something to help create thinly provisioned highways, …

Image: Intel Team Inside Facebook Data Center By IntelFreePress