Listen to the podcast. Find it on iTunes/iPod. Read a full transcript or download a copy. Sponsor: VMware.

The next BriefingsDirect case study discussion targets how biotechnology services provider Acorda Therapeutics has implemented a strategic disaster recovery (DR) capability to protect its highly virtualized IT operations and data.

See  how Acorda Therapeutics’ use of advanced backup and DR best   practices  and products has helped it to manage rapid growth, cut energy   costs,  and gain the means to recover and manage applications and data   faster.  Also learn how these advanced DR benefits have led to   other data center flexibly and even migration benefits.

Sharing more detail on how modernizing DR has helped improve many aspects of Acorda Therapeutics’ responsiveness is Josh Bauer, Senior Manager of Network Operations at Acorda Therapeutics  in Hawthorne, NY. The discussion was moderated by Dana Gardner, Principal Analyst at Interarbor Solutions. [Disclosure: VMware is a sponsor of BriefingsDirect podcasts.]

Here are some excerpts:

Gardner: What do you perceive as being  different today about DR than  just a few years ago? Is this really a  fast-moving area?

Bauer: One of the most prominent changes is recovery time.   You no longer need to restore from physical tape and see recovery  times  of upwards of 24 hours, something that we hadn’t seen until  recently.  We implemented Site Recovery Manager (SRM) from VMware and we can now do that same recovery in about four hours.

We're  constantly replicating   using RecoverPoint and we can get data up to  the minute, versus tape,   where you are at the whim of whether the  backup completed on time -- did   everything go to tape, and when was it  done? It could have been two   days ago, versus now, when it's data  that’s 100 percent synced up to a   minute ago.

When we had about 80 employees, we probably barely had a terabyte, and now with 350 employees we easily have over 14 terabytes.

Gardner: I am also wondering, because you are   in the healthcare and  biotechnology field, are there aspects of the new DR   that appeal to  you from a compliance or regulatory perspective as well?

Bauer: Definitely. Four times per year we have to prove that we can recover    all of our software and data by doing a DR test. Until we had SRM, we    had to do it all from tape, from a cold facility, and it would take us  a   day, sometimes a day-and-a-half. That’s just not the best way to do    things. But now, with SRM, we can always do these tests on the fly,  even   from our office, from home, or from wherever.

Gardner: Tell me a little bit more about Acorda Therapeutics.    You were founded in 1995. Tell us what you do, so our audience can    understand the type of company you are and type of products and services    you provide.

Recent growth

Bauer: We create treatments for people with multiple sclerosis, spinal cord injuries, or other neurological disorders. We have two marketed drugs in the market right now, the most recent of which, Ampyra,    helps people with multiple sclerosis walk better, and it has been a    huge success. And that's the main reason we've been growing so much    lately.

Prior to virtualization, we were spending a   lot of time managing our infrastructure, with all those physical servers.    Once we virtualized everything, we spent way less time managing the    infrastructure and could spend more time helping the business.

In    fact, the IT department itself has become less like a computer repair    shop and more like a strategy center. I'm constantly being brought  into   projects to help the business make the right decisions when it  comes  to  any type of technology.

The next logical step would be  to  have my  team spend less time doing these four-times-a-year DR  drills  the way I  described before. With SRM it’s a few clicks. We're  saving so  much time  and we are able to do other things.

Gardner: Tell me how you got to the point today, where you can deal   with  something like 14 terabytes and moment-by-moment backup  capability?

Strategic partner

Bauer: It all really started at VMworld.    That’s been a fantastic way for me to learn what's out there, what's    coming up, and just staying in the know. That’s actually where I met International Computerware, Inc. (ICI), who is one of our strategic partners for storage and virtualization.

I    had approached them with the growth issue. We had already started   doing  virtualization on our own. I had used it at a previous company,   but I  wasn’t familiar with SRM, and it looked like it might be a nice   fit for  improving our DR. So ICI came in and they sort of held our   hands and  helped us with that project.

Specific to storage, they   have also  helped us make sure that we do better management of growth,   anticipate  our growth, and show that we have more than what we're  going  to need,  before the growth happens, and they've done some  analysis on  like what  we have. We brought them in before things got  too bad.

Since using VMware, we've noticed uptime  upwards  of three nines  monthly. Before that, when we were mostly a  physical  environment, it was  nowhere near that much. We had physical  servers  going down all the  time.

VMware immediately gained our  trust,  seeing that they came  out with this product for DR. It was a  name that  we trusted. Then, we  played with it for a while, and it  worked out  fantastically.

It's  all about trusting VMware and  then, again,  ICI, working with them. They  just know their stuff. We  have a lot of  different partners we work  with, but we prefer to use  ICI, because  they really focus on doing  things properly. It's more  about working  with someone that really knows  what they are doing. They  understand  that we have some skills, as well.  They're not trying to  sell us  something we don’t need.

95 percent virtualized

We  are 95 percent virtualized here. The only thing that’s not virtual   is  our fax server, which requires a physical fax board and that’s about    it. Everything else is virtual.

Gardner: So this is across all tiered apps, tier one, three, four?

Bauer: That’s correct, our SQL apps, our Exchange, everything you can think of is virtualized.

Gardner: I understand you're using vSphere 5. You're on vCenter SRM 5. That only came out towards the end of last year. So you just jumped right on that.

Bauer: Oh, I didn’t waste any time. We were very excited about it, especially this new option of using a failback, which wasn’t really part of SRM Version 4.

If  you ever have the very unlikely event of a a disaster, when you do a    recovery, you're now operating off of the disaster equipment or    recovery equipment. While that’s happening, people are still saving    files and generating new data. If you were to just simply turn on the    original equipment again, all that data would be lost. So you need to    fail back to re-sync everything.

With SRM Version 4, you had to    configure two one-way recovery systems. So it would take a lot more    time. But now with failback, it's a lot more smooth, kind of built-in.

Gardner: Do you actually have separate data centers that you are backing up to? What's the topology or architecture that you're using?

Bauer: We have two separate data centers, recovery and production. At the  moment they're only a few towns apart, but we are shopping   around for a  data center much further away. We hope to do that in the   next six  months or so.

Gardner: Looking to the future, one other area I wanted to hit on, which is    important to a lot of folks, especially in some overseas markets, is    this issue about energy. Did you have any impact on energy and/or    storage costs associated with the total life cycle of the data?

Bauer: We reduced the footprint by easily 75 percent by not needing so many    physical servers. That’s a pretty huge shout-out to VMware there.  Also,   we're not using that much power. We don’t need as big a data  center.  Not  as much cooling is needed. There's a whole assortment of  things,  when  you take out all the physical servers.

Gardner: Now,   looking to the future, other areas that people have described as  a  segue  from going to high virtualization, exploiting the latest   technologies  in DR, is to start thinking about desktop virtualization infrastructure (VDI) and desktop-as-a-service. They're even looking at cloud and hybrid-cloud models for hosting apps, then backing them up and recovering them in    different data centers, which you've alluded to. Do you have any    thoughts about where this could possibly lead?

Bauer: In   fact, if you were going to ask me what my next initiative was  going to   be, and you didn’t mention desktops, that’s the first thing  that would   have come to mind. We're starting to explore replacing our  laptops with   virtual desktops. I'm hoping this is something that we  could implement   next year.

Right way to go

This seems like the right way to go, because our helpdesk team spends too much time swapping out laptops or replacing laptops that are dropped on the ground. You're looking at a small thin client,    which is the fraction of the cost of a laptop. Plus, the data is no    longer kept in a laptop. There are no security or compliance issues.  You   can l just give them a thin client, and they are back in business.

It  makes everybody in this company, especially at the   top-level, nervous  to know that some sensitive data still does make it   out to the  laptops. We tell people to save everything to their network   drives,  but without using thin clients and virtual desktops, there's no   other  way to force that.

Gardner: How  about advice for   those folks that might be moving towards a more  modern DR journey, as   you described it? What would you advise to them  as they begin, and what   lessons might you have learned that you could  share?

Bauer: First off, do it. You're going to be glad that you did. The good thing    about this is that you can do it in parallel with your current DR   plans.  You don’t have to change your existing recovery plans. You can   take as  much time as you want to set it up right. And the key is to set   up a  demonstration for the key business owners and players that are   going to  make the decision on the change.

Set it up right with a   handful  of important apps, important VMs, and then just show it to   people. Once  they see how great it works, you're definitely going to   want to change.

It's always helpful to have some outside  help. No matter how skilled   you are, it's always good to have a second  pair of eyes look at the work   that you did, if for nothing more than  to confirm that you've done   everything you could and your plans are  solid. It's helpful to have a   partner like ICI.

Listen to the podcast. Find it on iTunes/iPod. Read a full transcript or download a copy. Sponsor: VMware.

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This last fortnight there’s been a cacophony of hyperbole and at times marketing fluff from vendors and analysts with regards to Reference Architectures and Converged Infrastructures. As IBM launched PureSystems, NetApp & Cisco decided it was also a good time to reiterate their strong partnership with FlexPod.  In the midst of this, EMC decided to release their new and rather salaciously titled VSPEX. From the remnants and ashes of all these new product names and fancy launch conferences, the resultant war blogs and Twitterati battles ensued. As I poignantly watched on from the trenches in an almost Siegfried Sassoon moment, it was quickly becoming evident that there was now an even more ambiguous understanding of what distinguishes a Converged Infrastructure from a Reference Architecture, what it’s relation was with the Private Cloud and more importantly whether you, the end user should even care.

There’s a huge and justified commotion in the industry over Private Cloud because with lower costs, reduced complexity and greater data center agility, the advantages are compelling for any business looking to streamline and optimize its IT. In the pursuit of attaining such benefits and ensuring a successful Private Cloud deployment, one of the most critical components that need to be considered is that of the infrastructure and its underlying resource pools. With resource pools being the foundation of rapid elasticity and instantaneous provisioning, a Private Cloud’s success ultimately depends on the stability, reliability, scalability and performance of its infrastructure. With existent datacenters commonly accommodating legacy servers that require a refresh or new multiprocessor servers that are entrenched between an old and insufficient network infrastructure, one of the main challenges of a Private Cloud deployment is how to upgrade it without introducing risk. With this challenge and the industry’s pressing need for an economically viable answer, the solution was quickly conceived and baptized as “Converged Infrastructure”.  Sadly like all great ideas and concepts, competition and marketing fluff quickly tainted the lucidity of such an obvious solution by introducing other terms such as “Reference Architectures” and “Single Stack Solutions”. Even more confusing was the launch of vendor products that used such terms synonymously, together or as separate distinct entities. So what exactly differentiates these terms and which is the best solution to meet the infrastructure challenge of a Private Cloud deployment?

Reference Architectures for all intents and purposes are essentially just whitepaper-based solutions that are derived from previously successful configurations. Using various vendor solutions and leveraging their mutual partnerships & alliances, Reference Architectures are typically integrated and validated platforms built from server, network and storage components with an overlying hypervisor. NetApp’s FlexPod and EMC’s VSPEX fall into this category and both invariably point to their flexibility as a major benefit as they enable end users to mix and match as long as there remains a resemblance to the reference. With open APIs to various management tools, Reference Architectures are cleverly marketed as a quick, easy to deploy and risk free infrastructure solution for Private Clouds. Indeed Reference Architectures are a great solution for a low budget SMB that is looking to introduce itself to the world of Cloud. As for a company that is either in or bordering on the Enterprise space and looking to seriously deploy their workloads onto a Private Cloud, it's important to remember that sometimes things that are great on paper can still end up being a horrible mess in reality – anyone who's watched Lynch's Dune can pay testament to that.

The difficulty with Reference Architectures is that fundamentally they still have no hardened solution configuration parameters and ironically what they term an advantage i.e. flexibility, is actually their main flaw as their piece by piece approach of using solutions from many different vendors merely masquerades the same old problems. Due to being whitepaper solutions, integration of specific components is only documented as a high level overview with component ‘a’ being detailed as compatible with component ‘c’. With regards to the specifics and how these components integrate in detail, these are simply not available or realized until the Reference Architecture is cobbled together by the end user, who ultimately assumes all of the risk and financial obligation to ensure it not only works correctly but is also performing at optimum levels. This haphazard trial and error approach is counterproductive to the accelerated, pre-integrated, pretested and optimized model that is required by the infrastructure of a Private Cloud.

Furthermore Reference Architectures are based on static deployments of sizing and architecture that typically has little relation to the end users actual environment or needs, posing a problem whenever reconfiguration or resizing is required. With end users being left to resize and consequently reconfigure & reintegrate their solution, they also have to constantly find a way to integrate their existing toolsets with the open APIs. This subsequently eliminates a lot of the benefits associated with “quick time to value” as many deployment projects get caught up in the quagmire of such triviality. Added to this, once you’ve begun resizing or customizing your architecture, you’ve actually made changes that are a deviation from the proposed standard and hence no longer recognizable to the original reference. This leads to the other complication with Reference Architectures, namely support issues.

With more than 90% of support calls being related to logical configuration issues, they are more often than not an occurrence of bugs or incompatibility issues. When the vendor has no responsibility or knowledge of that logical build based on the fact that they meet your “requirements” to be flexible, the situation doesn’t bode any better than when you have a traditional infrastructure deployment. Vendor finger pointing is one the most frustrating experiences you inevitably have to face when deploying an IT infrastructure in the traditional way. Being on a 4am conference call during a Priority 1 with the different organizational silos and the numerous vendors that make up the infrastructure is a painful experience I’ve personally had to face. It’s not a pretty sight when you’re impatiently waiting for a resolution while the networking company blames the firmware on the Storage and the Storage vendor blames the bugs with the servers while all the time you are sitting their watching your CEO’s face turn into a tomato while the vein in his neck throbs incessantly. When you log a support call for your reference architecture who is actually responsible? Is it the company you bought it from or one of the many manufacturers that you used to assemble your self-built masterpiece? Furthermore which of those manufacturers or vendors will take full responsibility when you’ve ended up building, implementing and customizing the architecture yourself? Even at the point of deployment, the Reference Architecture carries elements of ambiguity for the end user ranging from which software and firmware releases to run to who is responsible for the regression testing of the logical build. For instance what if you decide to proactively update to one of your components’ latest firmware releases and then find out it’s not compatible with another of your components? Who owns the risk? Also for example if you buy a “flexible” Reference Architecture from vendor X, how will vendor X be able to distinguish what it is you’ve actually deployed and how it’s configured without having to spend an aeon on the phone doing a fact finding session, all while your key applications are down? Reference Architectures are great for a test environment or simple cheap and cheerful solution but using them as a platform to take key applications to the Cloud reeks of more 4am conference calls and exploding tomatoes.

Single Stack Infrastructures on the other hand while also sometimes marketed as a Converged Infrastructure or a “flexible” Reference Architecture (or sometimes both!) are another completely distinct offering in the market. These solutions are typically marketed as “All-in-one” solutions, and come in a various number of guises. Products such as Oracle’s Exadata and Exalogic, Dell’s vStart, HP’s CloudSystem Matrix and IBM’s PureSystems are all examples of the Single Stack solution where the vendors have tightly defined software stacks above the virtualization layer. Such solutions will also combine a bundled infrastructure and service offerings making them potential “Clouds in a Box”. While on the outset these seem ideal and quick to deploy and manage, there are actually a number of challenges with the Single Stack solution. The first challenge is that the Single Stack will always provide you their own inherent components regardless of whether they are inferior to other products in the market. So for example, instead of having network switches from the well established Cisco or Brocade, if you opt with the HP solution you’re looking at HP’s ProCurve, 3Com, H3C and TippingPoint. Worse still is if you go with the Oracle stack you’re condemned to have OracleVM as opposed to the market leading and technically superior VMware. Another challenge is that you’re also tied down to that one vendor and are now a victim of vendor lock-in. Instead of just having infrastructure that will fit your existing software toolset and service management, you will inevitably have to rip and replace these with the Single Stack’s product set. Additionally these complex and non-integrated software and hardware stacks require significant time to deploy and integrate, reducing a considerable amount of the value that comes from an accelerated deployment.

A true converged infrastructure is one that is not only pretested and preconfigured but also and more importantly pre-integrated; in other words it ships out as a single SKU and product to the customer. While it may use different components from different vendors, they are still components that are from market leaders and are well established in the Enterprise space. Furthermore while it may not have the “flexibility” of a Reference Architecture, it’s the rigidity and adherence to predefined standards that make the Converged Infrastructure the ideal fit for serious contenders who are looking for a robust, scalable, simply supported and accelerated Private Cloud infrastructure. The only solution that is on the market that fits that category is VCE's Vblock. By being built, tested, pre-integrated and configured before being sent to the end user as a single product, the Converged Infrastructure for the Amsterdam datacenter will be exactly the same as the deployment in Bangalore, Shanghai, Dubai, New York and London. In this instance the shipped Converged Infrastructure merely requires the end user to plug in and supply network connectivity.

With such a model, support issues are quickly resolved and vendor finger-pointing is eliminated. For example the support call is with one vendor (the Converged Infrastructure manufacturer) and they alone are the owner of the ticket because the Converged Infrastructure is their product. Moreover once a product model of a converged infrastructure has been shipped out, problems that may potentially be faced by a customer in Madrid can easily be replicated and tested on a like for like lab with the same product in London, rapidly resolving performance issues or trouble tickets.

Deploying a preconfigured, pretested and pre-integrated standardized model can also quickly eliminate issues with firmware updates and patching. With traditional deployments, keeping patches and firmwares up to date with multiple vendors, components and devices can be an operational role by itself.  You would first have to assess the criticality of each patch and relevance to each platform as well as validate firmware compatibility with other components. Additionally you’d also need to validate the patches by creating ‘mirrored’ Production Test Labs and then also have to figure out what your rollback mechanism is if there are any issues. By having a pre-integrated Converged Infrastructure all of this laborious and tedious complication is removed. All patches and firmwares can be pretested and validated on standardized platforms in labs that are exactly the same as the standardized platforms that reside in your datacenter. Instead of a multitude of updates from a multitude of vendors each year, a converged infrastructure offers the opportunity to have a single matrix that upgrades the infrastructure as a whole and risk free.

The other distinctive feature of a Converged Infrastructure is its accelerated deployment. By being shipped to the customer as a ready assembled, logically configured product and solution, typical deployments can range from only 30-45 days i.e. from procurement to production. In contrast other solutions such as Reference Architectures could take twice as long if not longer as the staging, racking and logical build is still required once delivered to the customer. It’s this speed of deployment which makes the Converged Infrastructure the ideal solution for Private Cloud deployments and an immediate reduction in your total cost of ownership, especially when the business or application owners demands an instant platform for their new projects.

The other benefit of having a company that continuously builds standardized and consistent infrastructures that are configured and deployed for key applications such as Oracle, SAP or Exchange is that you end up with an infrastructure that not only consolidates your footprint and accelerates your time to deployment but also optimizes and in most cases improves the performance of your key apps. I’ve recently seen a customer gain a 300% performance improvement with their Oracle databases once they decided to migrate them off their Enterprise Storage Arrays, SPAARC servers and SAN switches in favour of a Converged Infrastructure, i.e. the Vblock. Of course there were a number of questions, head scratching and pontifications as to what was seemingly inexplicable; “how could you provide such performance when we’ve spent months optimizing our infrastructure?” The answer is straightforward in that regardless of how good an engineering team you have, it is rare that they are solely focused on building a standardized infrastructure on a daily basis that is customized for a key application and is factoring all of the components comprehensively. 

To elaborate, typically customers will have an in house engineering department where they’ll have a Storage team, a Server team, a Network team, an Apps team, a SAN team etc. All of these silos then need to share their expertise and somehow correlate them together prior to building the infrastructure. Compare this to VCE and the Converged Infrastructure approach, where instead there are dedicated engineering teams for each step of the building process whose expertise is centred and focused upon a single enabling platform, i.e. the Vblock.  Firstly there’s the engineering team that does the physical build (including thermals, power efficiency, cooling, cabling, equipment layout for upgrade paths etc.). This is then passed on to another dedicated engineering team that takes that infrastructure and certifies the software releases as well as test the logical build configurations all the way through to the hypervisor. There’s then another engineering organization that’s sole purpose is to test applications that are commonly deployed on these Vblock infrastructures such as Oracle, SAP, Exchange, VDI etc. This enables the customer that orders for example an “Oracle Vblock” to have an infrastructure that was specifically adapted both logically and physically to not only meet the needs of their Oracle workloads but also optimize its performance. This is just a glimpse of the pre-sales aspect; post sales you have a dedicated team responsible for the product roadmap of the entire infrastructure ensuring that software or component updates are checked and advised to customers once they are deemed suitable for a production environment. The list of dedicated teams goes on but the common denominator is that they are all part of a seamless process that aims at delivering and supporting an infrastructure designed and purpose built for mission critical application optimization.

So whether you’re feeling Pure, Flexy or Spexy the key thing is to distinguish between Reference Architectures, Single Stack Solutions and the Vblock i.e. a Converged Infrastructure and align the right solution to the right business challenge. For fun and adventure I'd always purchase a kit car over a factory built car. I'd have great fun building it from all the components available to me and have it based on my Reference handbook. I could even customize my kit car with a 20 inch exhaust pipe, Dr. Dre hydraulics and fluffy dice because it's flexible just like a Reference Architecture. Alternatively because I love Audi so much I could buy an Audi car that has all of its components made by Audi. So that means ripping out the Alpine CD player for an Audi one, the BOSE speakers for Audi ones and even removing the Michelin tyres for some new Audi ones, regardless of whether they're any good or if they’re just OEM’d from a budget manufacturer - just like a Single Stack Solution. Ultimately if I'm serious about performance and reliability I'll just buy a manufactured Audi S8 that's pre-integrated and deployed from the factory with the best of breed components. Sure I can choose the colour, I can decide on the interior etc. but it's still built to a standard that's designed and engineered to perform. Much like a Converged Infrastructure, while I may choose to have a certain amount of CPU for my Server blades and a certain amount of IOPS and capacity for Storage, I still have a standardized model that's designed and engineered to perform and scale at optimum levels. For a Private or Hybrid Cloud infrastructure that successfully hosts and optimizes critical applications as well as de-risk their virtualization, the solution can only mean one thing - it's Converged.

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2011 was a year where despite the economic constraints everything Big was seemingly good; Big Data, Big Clouds, Big VMs etc. Caught in the industry’s lust for this excess, 2011 was also the year I lost count of how many overprovisioned resources to ‘Big’ Production VMs I witnessed. More often than not this was a typical reaction from System Admins trying to alleviate their fears of potential performance problems to important VMs. It was the year where I began to hear justifications such as “yes we are overprovisioning our production VMs..but apart from the cost savings, overallocating our available underlying resources to a VM isn’t a bad thing, in fact it allows it to be scalable”. Despite this 2011 was also the year where I lost count of the amount of times I had to point out that sometimes overprovisioning a VM does lead to performance problems - specifically when dealing with Virtual CPUs.

VMware refers to CPU as pCPU and vCPU. pCPU or ‘physical’ CPU in its simplest terms refers to a physical CPU core i.e. a physical hardware execution context (HEC) if hyper-threading is unavailable or disabled. If hyperthreading has been enabled then a pCPU would consitute a logical CPU. This is because hyperthreading enables a single processor core to act like two processors i.e. logical processors. So for example, if an ESX 8-core server has hyper-threading enabled it would have 16 threads that appear as 16 logical processors and that would constitute 16 pCPUs.

As for a virtual CPU (vCPU) this refers to a virtual machine’s virtual processor and can be thought of in the same vein as the CPU in a traditional physical server. vCPUs run on pCPUs and by default, virtual machines are allocated one vCPU each. However, VMware have an add-on software module named Virtual SMP (symmetric multi-processing) that allows virtual machines to have access to more than one CPU and hence be allocated more than one vCPU. The great advantage of this is that virtualized multi-threaded applications can now be deployed on multi vCPU VMs to support their numerous processes. So instead of being constrained to a single vCPU, SMP enables an application to use multiple processors to execute multiple tasks concurrently, consequently increasing throughput. So with such a feature and all the excitement of being ‘Big’ it was easily assumed by many that taking advantage of such a feature by provisioning additional vCPUs could only ever be beneficial – but if only it was that simple.

The typical examples I faced entailed performance problems that were either being blamed on the Storage or the SAN and not CPU constraints especially as overall CPU utilization for the ESX server that hosted the VMs would be reported as low. Using Virtual Instruments’ VirtualWisdom I was able to quickly conclude that the problem was not at all related to the SAN or Storage but the hosts themselves. By being able to historically trend and correlate the vCenter, SAN and Storage metrics of the problematic VMs on a single dashboard it was apparent that the high number of vCPUs to each VM was the cause. This was indicated by a high reading of what is termed the 'CPU Ready' metric.

To elaborate, CPU Ready is a metric that measures the amount of time a VM is ready to run against the pCPU i.e. how long a vCPU has to wait for an available core when it has work to perform. So while it’s possible that CPU utilization may not be reported as high, if the CPU Ready metric is high then your performance problem is most likely related to CPU. In the instances that I saw, this was caused by customers assigning four vCPUs and in some cases eight to each Virtual Machine. So why was this happening?

Well firstly the hardware and its physical CPU resource is still shared. Coupled with this the ESX Server itself also requires CPU to process storage requests and network traffic etc. Then add the situation that sadly most organizations still suffer from the ‘silo syndrome’ and hence there still isn’t a clear dialogue between the System Admin and the Application owner. The consequence being that while multiple vCPUs are great for workloads that support parallelization but this is not the case for applications that don’t have built in multi-threaded structures. So while a VM with 4 vCPUs will require the ESX server to wait for 4 pCPUs to become available, on a particularly busy ESX server with other VMs this could take significantly longer than if the VM in question only had a single vCPU.

To explain this further let’s take an example of a four pCPU host that has four VMs, three with 1 vCPU and one with 4 vCPUs. At best only the three single vCPU VMs can be scheduled concurrently. In such an instance the 4 vCPU VM would have to wait for all four pCPUs to be idle. In this example the excess vCPUs actually impose scheduling constraints and consequently degrade the VM’s overall performance, typically indicated by low CPU utilization but a high CPU Ready figure. With the ESX server scheduling and prioritising workloads according to what it deems most efficient to run, the consequence is that smaller VMs will tend to run on the pCPUs more frequently than the larger overprovisioned ones. So in this instance overprovisioning was in fact proving to be detrimental to performance as opposed to beneficial. Now in more recent versions of vSphere the scheduling of different vCPUs and de-scheduling of idle vCPUs is not as contentious as it used to be. Despite this, the VMKernel still has to manage every vCPU, a complete waste if the VM’s application doesn’t use them!

To ensure your vCPU to pCPU ratio is at its optimal level and that you reap the benefits of this great feature there are some straightforward considerations to make. Firstly there needs to be dialogue between the silos to fully understand the application’s workload prior to VM resource allocation. In the case of applications where the workload may not be known, it’s key to not overprovision virtual CPUs but rather start with a single vCPU and scale out as and when is necessary. Having a monitoring platform that can historically trend the performance and workloads of such VMs is also highly beneficial in determining such factors. As mentioned earlier CPU Ready is a key metric to consider as well as CPU utilization. Correlating this with Memory and Network statistics, as well as SAN I/O and Disk I/O metrics enables you to proactively avoid any bottlenecks and correctly size your VMs and hence avoid overprovisioning. This can also be extended in considering how many VMs you allocate to an ESX Server and in ensuring that its physical CPU resources are sufficient to meet the needs of your VMs.  As businesses’ key applications become virtualized it’s an imperative that whether they are old legacy single threaded workloads or new multi threaded workloads the correct vCPU to pCPU ratio is allocated. In this instance size isn’t always everything it’s what you do with your CPU that counts.

Gardner: Clearly one of the  requirements  in game development is the need to   ramp up a lot of servers to do the builds, but then they sit there essentially unproductive    between the builds. How did you flatten that out or manage the    requirements around the workload support?

Hart: Typically,  in the early stages of   development, there is a fair amount of testing  going on, and it tends   to be quite small -- the number of staff  involved in it and the number   of build iterations.

Going on,  when the game reaches to the end of its   product life-cycle, we’re  talking multiple game iterations a day and  the  game size has gotten  very large at that point. The number of people   involved in the testing  to meet the deadlines and get the game shipped   on date is into the  hundreds and hundreds of staff.

Gardner: How has virtualization and moving your workloads into different locations evolved over the years?

Hart: We work on the idea of having a central platform for a lot of these    systems. Using virtualization to do that allowed us to scale off at    certain times. Historically, we always had an on-premise VMware platform to do this. Very recently, we’ve been looking at ways to use that resource within a cloud to cut down from some of Capex loading but also remain a little bit more agile with some of the larger titles, especially online games that are coming around.

Gardner: We’re all very familiar with the amazing video games that are being  created nowadays. And SEGA of course is particularly well-known for the Sonic the Hedgehog franchise going back a number of years. What are some of the other critical requirements that   you have from a systems architecture perspective when developing these games?

Hart: We have a lot of development studios across the world. We're working on  multiple projects.   We need to ensure that we supply them with a  highly scalable and   reliable solution in order to test, develop, and  produce the game and   the code in time. ... We’re probably   looking at  thousands of individual developers across the world.

... The  first part was dealing with the end of the   process, and that was the  testing and the game release process. Now,   we’re going to be working  back from that. The next big area that we’re   actively involved in is  getting our developers to develop online games   within the hybrid  environment.

So they’re designing the game and   the game’s  back-end servers to be optimal within the VMware  environment.  And  then, also pushing from staging to live is a very  simple process  using  the Cloud Connector.

We're restructuring and   redesigning the  IT systems within SEGA to be more of a development   operations team to  provide a service to the developers and to the   company.

Gardner: How did you start approaching that from your  IT  environment, to build the right infrastructure?

Targeting testing

Hart: One of the first areas we targeted very early on was the last process    in those steps, the testing, arguably one of the most time-consuming    processes within the development cycle.    It happens pretty much all the way through as well to ensure that the    game itself behaves as it should, it’s tested, and the customer gets   the  end-user experience they require.

The biggest technical  goal   that we had for this is being able to move large amounts of data,    un-compiled code, from different testing offices around the world to  the   staff. Historically we had some major issues in securely moving  that   data around, and this is what we started looking into cloud  solutions   for this.

For very, very large game builds, and we're talking game builds above 10 gigabytes,  it ended up being couriered within the country and then overnight file  transfer outside of the country. So, very old school methods.

We    needed both to secure that up to make sure we understood where the   game  builds were, and also to understand exactly which version each of   the  testing offices was using. So it’s gaining control, but also   providing  more security.

Gardner: So we’re seeing a lot more of the role-play games (RPG) types of games, games themselves in the cloud. That must influence   what  you're doing in terms of thinking about your future direction.

Hart: Absolutely. We’ve been looking at things like the hybrid cloud model with VMware as a development platform for our developers. That's really what  we're   working on now. We've got a number of games in the pipeline that  have   been developed on the hybrid cloud platform. It gives the  developers a   platform that is exactly the same and mirrored to what it  would   eventually be in the online space through ISPs like Colt, which should be hosting the virtual cloud platform.

Gaining cost benefits

And one of the benefits we're seeing in the VMware offering is that regardless of what data center in the world is the standard platform, it also allows us to leverage    multiple ISPs, and hopefully gain some cost benefits from that.

Very   early on we were in discussions with Colt and also VMware to understand   what technology stack they were bringing into the cloud. We started   doing a proof of concept with VMware and a professional services company, and together we were    able to come over a proof of concept to distribute our game testing    code, which previously was a very old-school distribution system. So    anything better would improve the process.

There wasn't too much    risk to the company. So we saw the opportunity to have a hybrid cloud    set up to allow us to have an internal cloud system to distribute the    codes to the majority of UK game testers and to leverage high  bandwidth   between all of our sites.

For the game testing studios around Europe and the world, we could use a hosted version of the same service which was up on the Colt Virtual Cloud Director (VCD) platform to supply this to trusted testing studios.

Gardner: When you approach this hybrid cloud model, what about managing that?   What  about having a view into what’s going on so that you know what   aspects  of the activity and requirements are being met and where?

Hart: The virtual cloud environment of vCloud Director has a web portal that allows you to manage a lot of this configuration in a central way. We’re also using VMware Cloud Connector,    which is a product that allows you to move the apps between different    cloud data centers. And doing this allows us to manage it at one    location and simply clone the same system to another cloud data center.

In    that regard, the configuration very much was in a single place for us    in the way that we designed the proof of concept. It actually helped    things, and the previous process wasn’t ideal anyway. So it was a    dramatic improvement.

One of the immediate benefits was  around the design process. It's very   obvious that we were tightening  up security within our build delivery  to  the testing studios. Nothing  was with a courier on a bike anymore,  but  within a secured transaction  between the two offices.

Risk greatly reduced

Also    from a security perspective, we understood exactly what game assets   and  builds were in each location. So it really helped the product    development teams to understand what was where and who was using what,    and so from a risk point of view it’s greatly reduced.

In terms of stats and the amount of data throughput, it’s pretty large, and we’ve been moving terabytes pretty much weekly nowadays. Now we’re going completely live with the distribution network.

So    it’s been a massive success. All of the UK testing studios are using    the build delivery system day to day, and for the European ones we’ve    got about half the testing studios on board that build delivery system    now, and it’s transparent to them.

VMware was very  good at allowing us to understand  the technology and  that's one of the  benefits of working with a  professional services  reseller. In terms  of gotchas,  there weren't too  many. There were a lot  of good surprises that came  up and allowed us  to open the door to a lot  of other VMware  technologies.

Now, we're also looking at alternating a lot of processes within vCenter Orchestrator and other VMware products. They really gave us a good stepping stone into the VMware catalogue, rather than just vSphere, which we were using previously. That was very handy for us.

Gardner: I’d like to just pause here for a second. Your use of vSphere 4.1  must have been an important   stepping stone to be able to have the  dynamic ability to ramp up and   down your environments, your support  infrastructure, but also skills.

Hart: Absolutely. We already have a fair footprint in Amazon Web Services (AWS),    and it was a massive skill jump that we needed to train members of  the   staff in order to use that environment. With the VMware  environment,  as  you said, we already have a large amount of skill set  using vSphere.  We  have a large team that supports our corporate  infrastructure and  we've  actually got VMware in our co-located public  environment as well.  So it  was very, very assuring that the skills  were immediately  transferable.

Gardner: Now that you've done this, any words   of wisdom, 20/20 hindsight, that  you might share with others who are   considering moving more  aggressively into private cloud, hybrid cloud,   and ultimately perhaps  the full PaaS value?

Hart: Just get some hands-on experience and play with the cloud stack from  VMware. It’s inexpensive to have a go and just get to know the  technology stack.

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Hi All,

     This is my First blog about VMware vcloud Director...I hope it's usefull to you for better understanding about VMware vCloud Director...

     National Institute of Standards and Technology (NIST), cloud computing is defined as a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned

and released with minimal management effort or service provider interaction.

 

     Cloud Computing is a revolution that will define IT beginning in the second decade of the 21st Century. This new form of computing is perfectly poised to provide solutions to a host of business problems within organizations large and small. Cloud Computing will be the catalyst for the long predicted notion of "ubiquitous computing." So just what "is" Cloud Computing, and why it is so different from what has come before? The following pages will detail four main areas in which Cloud Computing allows businesses to break from the past:

Virtualization – The ability to increase computing efficiency.

 

Democratization of Computing – Bringing enterprise scale infrastructure to small and mid-size businesses.

 

Scalability and Fast Provisioning – Bringing web scale IT at a rapid pace.

 

           Commoditization of Infrastructure – Enabling IT to focus on the strategic aspects of its role.

 

This cloud model promotes availability and is composed of three service models and four deployment models.

 

1. Infrastructure as a Service (IaaS). In this environment, the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications.

 

2. Software as a Service (SaaS), in which the consumer is given access to software running in the provider’s environment.

 

3Platform as a Service (PaaS), in which the consumer can use the provider’s hardware to run applications created with the specific programming languages and tools supported by that provider.

 

Cloud environments may be separated into four categories based on the consumers they serve:

 

Private cloud—The cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on premise or off premise.

 

 

Community cloud—The cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizatio  or a third party and may exist  on premise or off premise.

 

Public cloud—The cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services.

 

Hybrid cloud—The cloud infrastructure is a composition of two or more clouds (private,community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).

 

Many enterprises and IT service providers are developing cloud service offerings for public and private environments.

 

All above given information related to Cloud Computing it's essential for better understand to VMware vCloud Director 1.5...

 

VMware vCloud Director:  The VMware vCloud solution is a suite of products designed to enable an IT organization to build a private cloud on top of a vSphere environment. The product suite consists of vCloud Director 1.5, VMware vShield Edge 5.0 and VMware vCenter chargeback1.6.2.

 

 

vCloud Director a single instance of vCloud Director is known as a “cell.” A cell consists of the vCloud Director components installed on a supported system. In larger implementations, multiple cells can be deployed with a front-end IP load balancer to direct end-user traffic to the correct cell.

vCloud Director stores information about managed objects, users and other metadata in a database. The current release of vCloud Director supports Oracle and Microsoft SQL Server for database platforms. In most environments, the vCloud Director and database components are installed on separate virtual machines for  proper load handling.

vCenter Server :   

 

Each vCloud Director cell can connect to one or more vCenter Server instances to access resources for running workloads. Each attached vCenter Server instance provides resources, such as CPU and memory, which can be  leveraged by vCloud Director.You have to deploy vcloud VM over vCenter by Installabe Package or OVF Appliance , you can donwnlaod trial Package by www.vmware.com.

 

VMware ESXi  hosts:

 

  VMware ESXi hosts provide the compute power for vCloud Director. ESXi hosts are placed in groups of resources, such as clusters or resource pools. These groups and their associated storage are then made available to vCloud Director. Add Esxi Host in Cluster and make a Resource Pool, if you are seeing no option for enabling Resource Pool, edit the cluster setting and select DRS option enable. 

 

VMware vShield Manager:

VMware vShield Manager provides a central point of control for managing, deploying, reporting, logging and integrating vShield as well as third-party security services. Working in conjunction with vCenter Server, VMware vShield Manager enables role-based access control and separation of duties as part of a unified framework for managing virtualization security.

 

vShield Edge secures the perimeter, or edge, around a virtual datacenter. vShield Edge secures the edge of a virtual datacenter with firewalling, VPN, NAT, DHCP, and Web load-balancing capabilities. vShield Edge allows cloud infrastructures to be scaled in a rapid and secure manner.

vCloud Director Components:--->

 

 

 

Gardner: Is  there a  fundamental change in how we approach the data that’s  coming  from IT  systems in order to get a better monitoring and  analysis  capability?

Kumar: The data has to be analyzed in  real-time. By real-time I mean in  streaming mode before the data hits  the disk. You need to be able to  analyze it and make decisions. That's  actually  a very efficient way of  analyzing information. Because you  avoid a  lot of data sync issues and  duplicate data, you can react  immediately  in real time to remediate  systems or provide very early  warnings in  terms of what is going wrong.

The challenges in doing  this streaming-mode analysis are scale and speed. The traditional  approaches with pure relational databases alone are not equipped to  analyze data in this manner. You need new   thinking and new approaches to  tackle this analysis problem.

Gardner: Also for issues of  security, offeners are trying different types of attacks.  So  this needs to be in real-time as well?

Kumar: You might be familiar with advanced persistent threats (APTs).    These are attacks where the attacker tries their best to be  invisible.   These are not the brute-force attacks that we have  witnessed in the   past. Attackers may hijack an account or gain access  to a server, and   then over time, stealthily, be able to collect or  capture the   information that they are after.

These  kinds of threats cannot be   effectively handled only by looking  at  data historically, because  these  are activities that are happening  in  real-time.

These kinds of threats cannot be   effectively  handled only by looking at data historically, because  these  are  activities that are happening in real-time, and there are  very,  very  weak signals that need to be interpreted, and there is a  time  element  of what else is happening at that time.   This too calls for  streaming-mode analysis.

If you notice, for   example, someone  accessing a server, a database administrator accessing a   server for  which they have an admin account, it gives you a certain   amount of  feedback around that activity. But if on the other hand, you   learn  that a user is accessing a database server for which they don’t   have  the right level of privileges, it may be a red flag.

You   need  to be able to connect this red flag that you identify in one   instance  with the same user trying to do other activity in different   kinds of  systems. And you need to do that over long periods of time in   order to  defend yourself against APTs.

Gardner: It's always been difficult to gain accurate analysis of large-scale IT  operations, but  it seems that this is getting more difficult. Why?

Kumar: If you look at trends, there are on average about 10 virtual machines (VMs) to a physical server.    Predictions are that this is going to increase to about 50 to 1,  maybe   higher, with advances in hardware and virtualization  technologies. The increase in density of VMs is a complicating   factor  for capacity planning, capacity management, performance   management,  and security.

In a very short period of time, you have in effect    seen a doubling of the size of the IT management problem. So there are  a   huge number of VMs to manage and that introduces complexity and a  lot   of data that is created.

Cloud computing

Cloud computing is another big trend. All analyst research and customer feedback suggests that we're  moving to a hybrid model, where you have some workloads on a public  cloud, some in a private cloud, and some running in a traditional data center. For this, monitoring has to work in a distributed environment, across multiple controlling parties.

Last    but certainly not the least, in a hybrid environment, there is    absolutely no clear perimeter that you need to defend from a security    perspective. Security has to be pervasive.

Given these new    realities, it's no longer possible to separate performance monitoring    aspects from security monitoring aspects, because of the distributed    nature of the problem. ... So change is happening much more quickly and  rapidly   than ever before. At the very least, you need monitoring and  management   that can keep pace with today’s rate of change.

At the very least, you need monitoring and management   that can keep pace with today’s rate of change.

The  basic problem you need to address is one of analysis.   Why is that? As we  discussed earlier, the scale of systems is really   high. The pace of  change is very high. The sheer number of   configurations that need to be  managed is very large. So there's data   explosion here.

Since you  have a plethora of information coming   at you, the challenge is no longer  collection of that information.  It's  how you analyze that information  in a holistic manner and provide   consumable and actionable data to your  business, so that you're able  to  actually then prevent problems in the  future or respond to any  issues  in real-time or in near real-time.

You  need to nail the   real-time analytics problem and this has to be the  centerpiece of any   monitoring or management platform going forward.

Advances in IT

Gardner: So we have the modern data center, we have issues of complexity and    virtualization, we have scale, we have data as a deluge, and we need to    do something fast in real-time and consistently to learn and relearn   and  derive correlations.

It turns out that there are some   advances  in IT over the past several years that have been applied to   solve  other problems that  can be brought to bear here. You've looked  at what's being done with big data and in-memory  architectures, and you've also looked at some of the great work that’s  been done in services-oriented architecture (SOA) and CEP, and you've put these together in an interesting way.

Big data is   about volume, the velocity or the speed with which the data comes in and   out, and the variety or the number of different data types and sources   that are being indexed and managed.

Kumar: Clearly there is a big-data angle to this.

Doug Laney, a META and a Gartner analyst, probably put it best when he highlighted that big data is    about volume, the velocity or the speed with which the data comes in and    out, and the variety or the number of different data types and sources   that are being indexed and managed.

For    example, in an IT management paradigm, a single configuration setting    can have a security implication, a performance implication, an    availability implication, and even a capacity implication in some cases.    Just a small change in data has multiple decision points that are    affected by it. From our angle, all these different types of criteria    affect the big data problem.

Couple of approaches

There  are a couple of approaches.   Some companies are doing some really  interesting work around big-data   analysis for IT operations.

They  primarily focus on gathering the   data, heavily indexing it, and  making it available for search, thereby   derive analytical results. It  allows you to do forensic analysis that   you were not easily able to  with traditional monitoring systems.

The   challenge with that  approach is that it swings the pendulum all the  way  to the other end.   Previously we had a very rigid, well-defined   relational data-models  or data structures, and the index and search   approach is much more of a  free form. So the pure index-and-search type of an approach is sort of the other end of the spectrum.

What    you really need is something that incorporates the best of both  worlds   and puts that together, and I can explain to you how that can  be   accomplished with a more modern architecture. To start with, we  can't do   away with this whole concept of a model or a relationship  diagram or   entity relationship map. It's really critical for us to  maintain that.

What   you really need is something that incorporates the best of both worlds   and puts that together.

I’ll    give you an example. When you say that a server is part of a  network   segment, and a server is connected to a switch in a particular  way,  it  conveys certain meaning. And because of that meaning, you can  now   automatically apply policies, rules, patterns, and automatically    exploit the meaning that you capture purely from that relationship. You    can automate a lot of things just by knowing that.

If you stick    to a pure index-and-search approach, you basically zero out a lot of    this meaning and you lose information in the process. Then it's the    operators who have to handcraft these queries to have to then    reestablish this meaning that’s already out there. That can get very,    very expensive pretty quickly.

Our approach to this big-data   analytics  problem is to take a hybrid approach. You need a flexible and   extensible  model that you start with as a foundation, that allows you   to then  apply meaning on top of that model to all the extended data   that you  capture and that can be kept in flat files and searched and   indexed. You  need that hybrid approach in order to get a handle on this   problem.

Gardner: Why do you need  to think about the architecture that  supports  this big data capability  in order for it to actually work in  practical  terms?

Kumar: You start with a fully  virtualized  architecture, because it allows  you not only to scale  easily, ... but you're able to reach  into these  multiple disparate environments and  capture and analyze and  bring that  information in. So virtualized  architecture is absolutely  essential.

Auto correlate

Maybe    more important is the ability for you to auto-correlate and analyze    data, and that analysis has to be distributed analysis. Because  whenever   you have a big data problem, especially in something like IT    management, you're not really sure of the scale of data that you need  to   analyze and you can never plan for it.

Think of it as applying a MapReduce type of algorithm to IT management problems, so that you can do    distributed analysis, and the analysis is highly granular or specific.    In IT management problems, it's always about the specificity with which    you analyze and detect a problem that makes all the difference  between   whether that product or the solution is useful for a customer  or not.

In  IT management problems, it's always about the specificity with which     you analyze and detect a problem that makes all the difference.

A major advantage of distributed  analytics is that you're freed from   the scale-versus-richness trade-off,  from the limits on the type of   events you can process. If I wanted to  do more complex events and   process more complex events, it's a lot  easier to add compute capacity   by just simply adding VMs and scaling  horizontally. That’s a big  aspect  of automating deep forensic analysis  into the data that you're   receiving.

I want to add a little bit  more about the richness  of  CEP. It's not just around capturing data and  massaging it or  looking  at it from different angles and events. When we  say CEP, we  mean it is  advanced to the point where it starts to capture  how people  would  actually rationalize and analyze a problem.

The  only way   you can automate your monitoring systems end-to-end and get  more of  the  human element out of it is when your CEP system is able to  capture   those nuances that people in the NOC and SOC would normally use to rationalize when they look at events. You not    only look at a stream of events, you ask further questions and then    determine the remedy.

No hard limits

To    do this, you should have a rich data set to analyze, i.e. there    shouldn’t be any hard limits placed on what data can participate in the    analysis and you should have the flexibility to easily add new data    sources or types of data. So it's very important for the architecture to    be able to not only event on data that are is stored in in  traditional   models or well-defined relational models, but also event  against data   that’s typically serialized and indexed in flat file databases.

Gardner: What's the  payoff if you do this  properly?

Kumar: It is no surprise that our  customers don’t come to  us saying we have a big data problem, help us  solve a big data problem,  or we have a complex event problem.

Customers say they are so  interconnected that they want these managed  on a common platform.

Their   needs are really around  managing security, performance and   configurations. These are three  interconnected metrics in a virtualized   cloud environment. You can't  separate one from the other. And   customers say they are so  interconnected that they want these managed   on a common platform. So  they're really coming at it from a   business-level or outcome-focused  perspective.

What AccelOps   does under the covers, is apply  techniques such as big-data analysis,   complex driven processing, etc.,  to then solve those problems for the   customer. That is the key payoff --  that customer’s key concerns that I   just mentioned are addressed in a  unified and scalable manner.

An   important factor for customer  productivity and adoption is the  product  user-interface. It is not of  much use if a product leverages  these  advanced techniques but makes the  user interface complicated --  you end  up with the same result as before.  So we’ve designed a UI that’s very easy to use, requires one or two clicks to get the    information you need; a UI-driven ability to compose rich events and   event  patterns. Our customers find this very valuable, as they do not   need  super-specialized skills to work with our product.

Key metrics

What  we've built is a platform that monitors data center performance,    security, and configurations. The three key interconnected metrics in    virtualized cloud environments. Most of our customers really want that    combined and integrated platform. Some of them might choose to start    with addressing security, but they soon bring in the performance    management aspects into it also. And vice versa.

And we take a  holistic cross-domain perspective -- we span server, storage, network,  virtualization and applications. What   we've really built is a common  consistent platform that addresses  these  problems of performance,  security, and configurations, in a  holistic  manner and that’s the main  thing that our customers buy from  us today.

Free trial download

Most of our customers start off with the free trial download. It’s a very simple process. Visit www.accelops.com/download and download a virtual appliance trial that you can install in your data center within your firewall very quickly and easily.

Getting    started with the AccelOps product is pretty simple. You fire up the    product and enter the credentials needed to access the devices to be    monitored. We do most of it agentlessly, and so you just enter the    credentials, the range that you want to discover and monitor, and that’s    it. You get started that way and you hit Go.

We  do most of it agentlessly, and so you just enter the   credentials,   the range that you want to discover and monitor, and that’s   it.

The  product then   uses this information to determine what’s in the  environment. It   automatically establishes relationships between them,  automatically   applies the rules and policies that come out of the box  with the   product, and some basic thresholds that are already in the  product that   you can actually start measuring the results. Within a  few hours of   getting started, you'll have measurable results and  trends and graphs   and charts to look at and gain benefits from it.

Gardner: It   seems that as we move toward cloud and mobile that at some point  or   another organizations will hit the wall and look for this  automation   alternative.

Kumar: It’s about automation and distributed   analytics and about getting very  specific with the information that you   have, so that you can make  absolutely more predictable, 99.9 percent   correct of decisions and do  that in an automated manner. The only way   you can do that is if you  have a platform that’s rich enough and   scalable and that allows you to  then reach that ultimate goal of   automating most of the management of  these diverse and disparate   environments.

That’s something  that's sorely lacking in products   today. As you said, it's all  brute-force today. What we have built is a   very elegant, easy-to-use  way of managing your IT problems, whether  it’s  from a security  standpoint, performance management standpoint, or   configuration  standpoint, in a single integrated platform. That's   extremely  appealing for our customers, both enterprise and cloud-service    providers.

I also want to take this opportunity to encourage  those of your listening or reading this podcast to come meet our team at  the 2011 Gartner Data Center Conference, Dec. 5-9, at Booth 49 and  learn more. AccelOps is a silver sponsor of the conference.

• A Technical Look at How Parallel Processing Brings Vast New Capabilities to Large-Scale Data Analysis
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• Delivering Data Analytics Through Workday SaaS ERP Applications Empowers Business Managers at Actual Decision Points

The stakes have never been  higher for keeping applications and business up and running.

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Gardner: We have heard a lot about IT as a service. How have you at Southwest been able to  keep IT squarely in the role of enablement?

Young: As we are taking a look and trying to be what travelers want in an    airline, and we are constantly looking for ways to improve Southwest    Airlines and make it better for our customers, that's really where virtualization and IT as a service comes into play.

People want to be able to get on Southwest.com,   make a reservation, log on to their Rapid Rewards or our Loyalty   Program, and they  want to be able to do it when they want to do it, when   they need to  do it, from wherever they are. And it’s just great to be   able to  provide that service.

We provide that to them at any   point in  time that they want in a reliable manner. And that's really   what it  gets right down to -- to make the functions and the solutions   that we  provide ubiquitous so people don’t really need to think about   anything  other than, "I need to do this and I can do it now."

At your fingertips

Gardner: I travel quite a bit and it seems to me that things have changed a lot  in the last few years.   One of the nice things is that information  seems to be at your   fingertips more than ever. I never seem to be out  of the loop now as a   traveler. I can find out changes probably as  quickly as the folks at the   gate.

So how has this transfer of  information been possible?  How  have you been able to keep up with the  demands and the expectations  of  the travelers?

Young: If we talk about information and the  flow of  information through  applications and services, it really starts  to  segment the core  technical aspects of that so the customer and our   employees don’t  really need to think about it. When they want to get  the  flight at the  gates, the passenger is on a flight leg, etc., they  can  go ahead and  get that at any moment in time.

... The same is true   of how we provide IT as a  service. What we want to be able to do is   provide IT whenever they  want it, whenever they need it, at the right   cost point, and to meet  their needs. We've got some of the best   customers in the world and  they like to do things for themselves. We   want to allow them to do  that for themselves and be able to provide our   employees the same.

Gardner: How in  IT have you been able to create common infrastructures,  reduce   redundancy, and then yet still ramp up to meet all your  requirements?

Significant volume

Young: What   we've been able to do and how we have been able to meet some  of those   challenges is through a number of different VMware products.  One of the   core products is VMware itself, if we talk about vSphere, vMotion, etc., to be able to provide that virtualization. You can get a 1-to-10 virtualization depending on which type of servers and blades you're using, which helps us on the infrastructure side of the house   to  maintain that and have the storage, physical, and electrical   capacity  in our data centers.

But it also allows us, as we're moving, consolidating, and expanding these different data centers, to be able to move that virtual machine (VM) seamlessly between points. Then, it doesn’t matter where it’s running.

That    allows us the capacity. So if we have a fare sale and I need to add    capacity on some of our services, it gives our us and our team that run    the infrastructure the ability to bring up new services on new VMs    seamlessly. It plugs right into how we're doing things, so that internal    cloud allows us not to experience blips.

It's been a great add for us from a capacity management perspective and being able to get the right capacity, with the right    applications, at the right time. It allows us to manage that in such a    way that it’s transparent to our end-users so they don’t notice any  of   this is going on in the background, and the experience is not  different.

...  We started our virtualized   environments about 18 months ago. We went  from a very small amount of   virtualization to what we coined our  Server 2.0 strategy, which was   really the combination of  commodity-based hardware blades with VMware on   that.

And that  allowed us last year in the first and second   quarter to grow from  several hundred VMs to over several thousand, which   is where we're at  today in the production environment. If you talk   about production,  development, and test, production is just one of those   environments.

It  has allowed us to scale that very rapidly   without having to add a  thousand physical servers. And it has been a   tremendous benefit for us  in managing our power, space, and cooling in   the data center,    along with allowing our engineers who are doing the day-to-day work  to   have a single way to manage it, deploy, and move stuff around even   more  automatically. They don’t have to mess with that anymore, VMware   just  takes care of the different products that are part of the VMware   Suite.

Gardner: And your  confidence, has it risen to the  level where you're looking at  70, 80,  90, even more percent of  virtualization? How do you expect to  end that  journey?

Ready for the evolution

Young: I would love to be at 100 percent virtualized. That would be   fantastic.  I think unfortunately we still have some manufacturers and   software  vendors -- and we call them vendors, because typically we   don’t say  partners -- who decide they are not going to support their   software  running in the virtualized environment. That can create   problems,  especially when you need to keep some of those systems up 24 x   7, 365,  with 99.95 percent availability.

We're hoping that    changes, but the goal would be to move as much as we can, because if I    take a look at virtualization, we are kind of our internal private    cloud. What that’s really doing is getting us ready for the evolution    that’s going to happen over the next, 5, 7, or 10 years, where you may    have applications and data deployed out in a cloud, a virtual private cloud, public cloud if the security becomes good enough, where you've got to bring all that stuff together.

If you need to have huge amounts of capacity and two applications are not co-located that need to talk back and forth, you've got to be much more  efficient   on the calls and the communications and make that seamless  for the   customer.

This is giving us the platform to start  learning more   and start developing those solutions that don’t need to  be collocated in   a data center or in one or two data centers, but can  really be pushed   wherever it makes sense. That could be from wherever  the most efficient   data center is from a green technology perspective,  use the least   electricity and cooling power, to alternate energy, to  what makes sense   at the time of the year.

That is a huge add  and a huge win for  us  in the IT community to be able to start  utilizing some of that   virtualization and even across physical  locations.

Gardner: Is there a   centralization feature to this that also is paying dividends?

Young: That’s a huge cornerstone of the suite of tools that we've been able   to  get through VMware is being able to deploy custom solutions and  even   some of the off-the-shelf solutions on a standard platform,  standard   operating systems, standard configurations, standard  containers for the   web, etc. It allows us to deploy that stuff within  minutes, whereas it   used to take engineers manually going to configure  each thing   separately. That’s been a huge savings.

The other  thing is, once   you get the configuration right and you have it  automated, you don’t   have to worry about people taking some human  missteps. Those are going   to happen, and you've got to go back and  redo something. That   elimination of error and the speed at which we  can do that is helping.   As you expand your server footprints and the  number of VMs and servers   you have without having to add to your  staff, you can actually do more   with the same number of or fewer  staff.

Gardner: How you feel about desktop virtualization?

Young: What’s really driven us to take a look  at  it is that around our  environment we can control security on virtual   desktops, etc., very  clearly, very quickly and deliver that in a great   service.

New mobile devices

The    other thing that’s leading to this is, not just what we talked about   in  security, is the plethora of brand new mobile devices -- iPhones, iPads, Android devices, Galaxy. HP has a new device. RIM has a new device. We need to be able to deliver our services in a  more   ubiquitous manner. The virtual desktop allows us to go ahead and   deliver  some of those where I don’t need to control the hardware. I   just  control the interface, which can protect our systems virtually,   and it’s  really pretty neat.

I was on one of my devices the   other day and  was able to go in via virtual desktop that was set up to   be able to use  some of the core systems without having all that stuff   loaded on my  machine, and that was via the Internet. So it worked out   phenomenally  well.

Now, there are some issues that you have to   do depending on  whether you're doing collocation and facility, but you   can easily get  through some of that with the right virtualization  setup  and networking.

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Generally I.T. folk, whether in Storage, Virtualization, Change Management or Project Management love the use of acronyms and synonyms to express key concepts amongst each other. What other industry would allow an individual to spurt a line such as “Have SOX seen the BCP and CAB approval for our VDC’s DR SAN and will this then be added to the CMDB by CoB today?” without immediately flinching or bringing in a logopaedics specialist for help. More often than not, I.T. folk have also used these synonyms and acronyms as smokescreens to prevent outsiders from realizing “well this I.T. stuff is actually quite easy to understand and quite straightforward”.

Hence no surprise that when the seemingly simple concept of Cloud Computing took off, so did the emergence of an abundance of acronyms and synonyms reaping a new breed of I.T. professionals who were the only ones that could correctly understand them i.e. ‘The Cloud Specialist’. Despite this, the beauty of the Cloud (or as most people are starting to realise the synonym for the Internet) is that it not only encompasses the I.T.industry and their business demands but also the average end user who’s only experience with I.T. is their iPhone and its App Store. So while EMC’s extensive airport advertising may have initially confused a lot of tourists into thinking that the ‘Journey to the Cloud’ was a slogan for an up and coming budget airline, the general public are certainly now becoming aware of ‘The Cloud’. End users are now bombarded with Clouds from Microsoft claiming that Windows 7 is your ‘Path to the Cloud’, Pizza Restaurants offering free access to ‘the Cloud’ and Apple iPhone owners having iCloud enforced upon them (no comment on the security issues of your email contacts and personal photos being uploaded to Apple’s database).  So while the idea of Public, Private and Hybrid Clouds become more familiar and understood even amongst the masses, it’s with surprise that I often find people within the IT industry who are still unaware or unsure of Cloud Service acronyms such as IaaS, PaaS, SaaS, Maas, Caas or Xaas.

To understand why there are so many acronyms with the Cloud, it is important to appreciate that the Cloud has a number of services which each of these classify. The first of these, IaaS (Infrastructure as a Service) is when the consumer does not deal with the infrastructure, instead the responsibility of the equipment is outsourced to the Service Provider. The Service Provider not only owns the equipment but will also be responsible for its running and maintenance, where the consumer will be charged on a ‘pay as you use’ basis. IaaS is often offered as a horizontally integrated service that includes not only the server and storage but also the connectivity domains. For example while the consumer may deploy and run their own applications and operating systems, the Iaas provider would typically provide the replication, backup and archiving (Storage), the powerful computing requirements (Server) or the network load balancing and firewalls (Connectivity domains).

PaaS provides the capability for consumers to have applications deployed without the burden and cost of buying and managing the hardware and software.  In other words these are either consumer created or acquired web applications or services that are entirely accessible from the Internet. Usually created with programming languages and tools supported by the service provider these web applications enable the consumer to have control over the deployed applications and in some circumstances the application-hosting environment but without the complexity of the infrastructure i.e. the servers, operating systems or storage. Offering a quick time to market and services that can be provisioned as an integrated solution over the web, PaaS facilitates immediate business requirements such as application design, development and testing at a fraction of the normal cost.

Software as a service (SaaS) is the ability for a consumer to use on demand software that is provided by the service provider via a thin client device e.g. a web browser over the Internet. With SaaS the consumer has not only no management or control of the infrastructure such as the storage, servers, network, or operating systems, but also no control over the application’s capabilities. Culled from what were originally referred to as (ASPs) Application Service Providers, SaaS is a quick and efficient delivery model for key business applications such as customer relationship management (CRM), enterprise resource planning (ERP), HR and payroll.

Monitoring as a Service (MaaS) is at present still an emerging piece of the Cloud jigsaw but an integral one for the future. In the same way that businesses realised that their infrastructure and key applications required monitoring tools that would ensure the proactive elimination of any downtime risks, Monitoring as a Service provides the option to offload a large majority of those costs by having it run as a service as opposed to a fully invested in house tool. So for example by logging on to a thin client or central web based dashboard which is hosted by the service provider, the consumer can monitor the status of their key applications regardless of location. Add the advantages of an easy set up and purchasing process and MaaS could be a key pay as you use model for the de-risking of applications that are initially being migrated to the Cloud.

Communication as a Service (CaaS), enables the consumer to utilize Enterprise level VoIP, VPNs, PBX and Unified Communications without the costly investment of purchasing, hosting and managing the infrastructure. With the service provider responsible for the management and running of these services also, the other advantage the consumer has is that they needn’t require their own trained personnel, bringing significant OPEX as well as CAPEX costs.

Finally XaaS or ‘anything as a service’ is the delivery of IT as a Service through hybrid Cloud computing and is a reference to either one or a combination of Software as a Service (SaaS), Infrastructureas a Service (IaaS), Platform as a Service (PaaS) Communications as a service (CaaS) or monitoring as a service (Maas). XaaS is quickly emerging as a term that is being readily recognized as services that were previously separated on either private or public Clouds are becoming transparent and integrated.

So as the term ‘The Cloud’ finally breaks into the minds of the masses and takes meaning, the next phase will be to take the numerous services that are offered by the Cloud, mature them and enable consumers to fully understand their benefits. From Enterprise to SMB to end users, Cloud Services will inevitably bring immense benefits and cost savings. All that is now required is for consumers to know what all those unnecessarily complicated acronyms mean!

Some nice Labs

LAB 4 - Failover

In this lab we tested fault tolerant on a VM with no down time, is setup in a cluster which is the boundary. If the cluster fails fault tolerant will also fail.

We tested also a failover on vCenter if the disaster hits the fan, vCenter Heartbeat can solve the problem. With heartbeat you build a vCenter and SQL cluster which is active/passive. Especially interesting is to user heartbeat when you use stretch clustering.

And lastly we test backup software from VMware which is simple and easy to use, perhaps not have all the function that the big backup software has but for smaller/mid company’s it good enough. Its use the snapshot function so you can user incremental and you can ship the data to NFS store like a Datadomain backup disk device unit.

LAB 5 - SRM

Interesting product, what is nice in the new version is that you can run all the tests, failover and failback which are great. You have the replication functionality or you use the storage replication software. Also get a clear view if the VM is protected or not again a disaster.

Another interesting topic is DA versus DR.

DA: Disaster avoidance for VMware is stretch clustering

DR: Disaster Recovery for VMware is SRM.

LAB 22 - VMware View

Great product, easy to user for the user and VMware has built a complete concept around this.

In this lab we had a look at the broke, composer, view manager and the security gateway.

The security gateway was a nice setup with no AD connection and striped down Windows server.

And you can now run View on most of the device out there.

Lab 9 - Performance troubleshooting

In this lab we look at some of the most commonly user troubleshooting scenarios and one of the cool thing was the storage DRS to spread the datastore load and the IOPS setting on the VM disks.