I just wanted to point out a great opportunity for anybody considering leveraging IBM Workload Deployer v3 to deploy Database workloads. On June 29th Rav Ahuja, a Senior Product Manager for Data Management at IBM, will be hosting a webcast entitled "Easily Deploying Private Clouds for Database Workloads". He will be joined by Chris Gruber (Product Manager, Database as a Service), Leon Katsnelson (Program Director, IM Cloud Computing Center of Competence), and Sal Vella (Vice President, Database Development and Warehousing) in this panel discussion.
As many of you already know, IBM Workload Deployer v3 comes pre-loaded with DB2 images and patterns that are configured to rapidly provision standardized database servers for any number of purposes. The servers can be deployed in standalone configurations or as part of a complete virtual system including web components with the database components. These servers can also be configured for high availability scenarios. This panel discussion will cover all of these scenarios and more.
You can read more about the webcast in this blog post by Rav Ahuja.
If you want further details about how to build and rapidly deploy databases in a private cloud, be sure to attend this free webinar on June 29th.
Among the major features of the new virtual application pattern in IBM Workload Deployer is the notion of elasticity. That is, as your application needs more resources, it gets them. When your application can meet its SLAs with fewer resources, the environment shrinks. With this kind of pattern, you enable elasticity by specifying a policy and defining the scaling trigger (i.e. CPU usage, application response times, database response times, etc.). What may have been a bit lost in some of these new announcements regarding IBM Workload Deployer is the fact that you can now leverage this core feature of cloud, elasticity, in your virtual system patterns.
If you have read this blog in the past, you probably already know that the Intelligent Management Pack is an option for virtual system patterns built using WebSphere Application Server Hypervisor Edition. When you enable the Intelligent Management Pack option, you are essentially building and deploying WebSphere Virtual Enterprise (WVE) environments. For those of you not familiar with WVE, the best way to describe it is that it provides you with application and application infrastructure virtualization capabilities. Of its many capabilities, one most germane to our discussion today is the ability for users to attach SLAs to applications and then have WVE automatically prioritize requests and manage resources in order to meet those SLAs. Inherent in this capability is the ability to dynamically start and stop application server processes (JVMs) as required. In other words, WVE provides JVM elasticity.
The fact that WVE provides JVM elasticity is nothing new. Further, IBM Workload Deployer started providing virtual machine (VM) elasticity in previous versions (when it was WebSphere CloudBurst). With this feature, you could add or remove VMs to an already deployed virtual system using dynamic virtual machine operations provided by the appliance. The catch was that the VM elasticity was a manual action and you could not link this elasticity to the same SLAs tied to your applications. Well, thanks to a new feature in WebSphere Virtual Enterprise and easy integration provided by the Intelligent Management Pack, this is no longer the case.
Starting in IBM Workload Deployer 3.0, you can take advantage of a new WVE feature called Elasticity Mode when using the Intelligent Management Pack. Elasticity mode is not unique to IBM Workload Deployer, but a concept new to the base WVE product. It allows one to define actions for how WVE should grow and shrink the set of nodes used by application server resources. Like the basic JVM elasticity capability in WVE, these node elasticity actions trigger based on SLAs tied to your applications. Consider the case that you are using elasticity mode and your application is not currently meetings its SLA. If WVE does not think it can start any more application server instances on the current set of nodes, it will grow the set of nodes per your elasticity configuration. Conversely, if WVE detects that it can meet SLAs with fewer nodes, it will shrink the resources per your elasticity configuration.
In IBM Workload Deployer, using elasticity mode becomes even easier. All you need to do is use the Intelligent Management Pack and enable the elasticity mode option in your virtual system patterns. When you do this, you get automatic integration between IBM Workload Deployer and the deployed WVE environment. What does that mean? It means that if WVE detects it needs more nodes, it will automatically call back into IBM Workload Deployer and request that the appliance provision a new VM that will serve as a node for application server processes. It also means that if WVE detects it could meet SLAs with fewer resources, it will call into IBM Workload Deployer and ask it to remove a node. All of this happens without any user scripting. All you have to do is enable this option in your patterns and configure SLAs appropriate for your applications.
To me, this exciting new feature brings out the best of elasticity capabilities in both IBM Workload Deployer and WebSphere Virtual Enterprise. The result is a single management plane that gives you both VM and JVM elasticity for your cloud-based application environments. Best of all, elasticity actions map directly to SLAs for your applications. After all, when it comes to cloud, it's the application that really matters!
The soon to be released IBM Workload Deployer is already being integrated with many IBM products. One of these is the Rational Application Developer. I created a short video demonstration of a simple scenario that includes multiple phases of an application from development to production using IBM Workload Deployer. The scenario starts with the Solutions Architect creating a workload application pattern for a stock trading application. It then moves to the developer working in Rational Application Developer and demonstrates this integration that allows the developer to access the workload pattern, publish the application that she has built in Rational Application Developer into the pattern, and then deploy the pattern to the test cloud. All of this without leaving the Rational Application Developer user interface. The scenario then continues with the test team adding policies and validating the application before the deployment manager finally makes some final adjustments and adds places the application into the production cloud.
As I have mentioned before, IBM Workload Deployer v3.0 introduces choices in pattern-based deployment models. One of those models, virtual system patterns, is a carry over from the WebSphere CloudBurst Appliance. When you use virtual system patterns in IBM Workload Deployer, you can take advantage of all of the techniques you put to use in WebSphere CloudBurst. This is certainly good news for current WebSphere CloudBurst users, but it goes a bit further. Instead of simply maintaining the status quo with virtual system patterns, which would have been reasonable considering the introduction of virtual application patterns, we chose to continue to expand on your customization options for this pattern deployment model. In particular, I want to discuss three new features in IBM Workload Deployer that may help you to better construct and manage virtual system patterns.
The first new feature is one that I have been eagerly awaiting. In the new version of the appliance, we provide you with the ability to specify part and script package ordering in your pattern. This means that, within the virtual system pattern editor, you can tell IBM Workload Deployer in which order to start the virtual machines in your pattern, and you can specify in which order to invoke the script packages within the pattern during deployment. This eliminates the need for special script invocation orchestration logic in your pattern (I had customers resorting to a semaphore like approach using a shared file system), and it allows you to be more declarative about the virtual machine bring-up process. There are constraints, specifically with the part ordering. Some images will impose an implied part start-up order that you cannot change. For instance, deployment manager parts in the WebSphere Application Server Hypervisor Edition image must start before custom node parts. The good news is the pattern editor will not allow you to specify a part start-up order that violates these constraints. The image below shows an example of the ordering view in the virtual system pattern editor.
Another new feature that may influence the way you build virtual system patterns is the introduction of Add-Ons. You can think of Add-Ons as special script packages that you can include in your virtual system pattern that perform system-level configuration actions. Specifically, you can include add-ons in your virtual system pattern to add an operating system user, add a virtual disk, or add a NIC during the deployment process. You include Add-Ons in your pattern by simply dragging and dropping them onto a part in your pattern, just as you do with script packages today. The difference between script packages and Add-Ons is that IBM Workload Deployer will ensure the invocation of all Add-Ons before any other scripts run during deployment. We include default Add-On implementations for adding a user, disk, and NIC.
The last new feature I want to talk about today has more to do with how you manage or govern the deployment of virtual system patterns. In WebSphere CloudBurst 2.0, we introduced the idea of Environment Profiles as a way to extend your customization reach into the deployment process. Initially, these profiles gave you the ability to directly assign IP addresses to virtual machines in your deployment, declaratively specify virtual machine naming formats, and easily split a single pattern deployment across multiple cloud groups. In IBM Workload Deployer, you will be able to use these same profiles to set resource consumption limits for pattern deployments. In particular, you will be able to set cumulative limits for virtual CPU, memory, storage, and software licenses used by deployments tied to a specific profile, thereby giving you finer-grained control over cloud resource consumption. The picture below shows the new resource limit aspects of environment profiles.
Virtual system patterns are key in the deployment model choices for IBM Workload Deployer. Not only did we carry the concept over from WebSphere CloudBurst to IBM Workload Deployer, but we made it even better. Expect this trend to continue!
More and more, I am getting a question about how to bring existing WebSphere environments into IBM Workload Deployer. While "bringing in an environment" can mean any number of things, let's take it to mean that a user wants to import their existing WebSphere cells, applications, and configuration into IBM Workload Deployer as a pattern they can subsequently deploy. While there may not be a big red easy button in the appliance that lets you point to an existing environment and import it, there are a couple of techniques that one can employ. I have covered both techniques before, but since I'm getting the question with increasing frequency, I felt like it was time for recap.
The first option is to use a combination of IBM Workload Deployer and Rational Automation Framework for WebSphere. This is a use case I have spoken about numerous times at conferences and in blog posts and articles. In fact, you can read a little about it here. In this sense, RAFW provides excellent capabilities to point at an existing cell, and import everything about it. This includes WebSphere configuration, applications, shared libraries, and more. Once imported as a RAFW project, you can use the IBM Workload Deployer integration script package provided by RAFW to replay that configuration on top of deployments created by the appliance.
The second option is something I talk about a little less frequently. This option revolves around the use of a sample script (provided for free in our samples gallery) that you can run against existing WebSphere cells. The invocation of this script produces IBM Workload Deployer script packages that you can use in patterns to apply the configuration of the target cell to your new cloud-based deployments. Under the covers the utility script and resultant script packages use backupConfig and restoreConfig respectively. They do ensure the update of the cell, node, and host names during the restoreConfig execution (which happens automatically during pattern deployment). Beyond that, the use of the script is subject to the same limitations and rules in place for the use of the backupConfig and restoreConfig commands. You can read more about this capability, watch it in action, and download it for free.
I hope this is all useful information for those of you looking for ways to import existing environments into IBM Workload Deployer as patterns. If you have any questions, please let me know!
WebSphere configuration management practices are common items of conversation that comes up when I am talking with users about IBM Workload Deployer (formerly WebSphere CloudBurst). This conversation can take on so many different avenues that it is hard to capture all of them in a short blog post. So, for the sake of this post, let's consider two facets of WebSphere configuration management. The first facet is addressing the need to consistently arrive at the same configuration across multiple deployments of a given WebSphere environment. The second facet involves managing the configuration of a deployed environment over time to protect against living drift. What is the best way to tackle these two challenges? Well, it comes down to picking the right tool for the job.
When it comes to ensuring consistency of initial WebSphere configuration from deployment to deployment, there is really no better means than patterns-based deployments enabled by IBM Workload Deployer. Whether you are using a virtual system or virtual application pattern, the bottom line is that you are representing your middleware application environments as a single, directly deployable unit. When you need to stand that environment up, you simply deploy the pattern. The deployment encapsulates the installation, configuration, and integration of the environment, and your applications if you so choose. The benefit of this approach is that once you get your pattern nailed down, you can be extremely confident that the initial configuration of your environments is extremely consistent from deploy to deploy. Basically, no more bad deployments because someone forgot to run configuration step 33 out of 100!
Because we talk about the benefits of consistency provided by our IBM Workload Deployer patterns, users often ask what IBM Workload Deployer does in terms of configuration governance for deployed environments. In other words, they ask how IBM Workload Deployer helps them to track configuration changes or compare the configuration of a deployed environment to a known good one. The honest answer is that this is a bit beyond the functional domain of the appliance. While IBM Workload Deployer does allow you to manage the deployed environment (apply fixes, update deployed applications, snapshot, etc.), it does not layer some of the common configuration governance concerns on top of that. However, there is a good reason why the appliance does not focus on that. It's because Rational Automation Framework for WebSphere does!
If you find yourself wanting to actively track configuration changes, periodically (and automatically at specified intervals) compare configuration changes to a 'golden' baseline, import configurations of a known good environment, apply common configuration across a number of cells, then the capabilities of RAFW would likely be of interest to you. It can do all this and give you an incredible toolbox of out-of-the-box application deployment and configuration capabilities for WebSphere environments. In my mind, for those that spend a good deal of time dealing with WebSphere configuration, whether it be deploying applications, configuring containers, or debugging inadvertent changes, an examination of RAFW functionality is a must.
Now it is time for a bit of disclaimer/clarification. I am not suggesting that you pick one or the other when it comes to IBM Workload Deployer and RAFW. In fact, there are many scenarios where 1+1=3 with these two solutions, and I have written about it many, many times (including this article). That said, I think it is important to highlight the relative strengths of each product, so that it is easier to map it back to your pain points. In honesty, many of the users I talk with have challenges in getting the initial configuration right AND managing it over time. That kind of problem beckons for the integrated IBM Workload Deployer/RAFW solution.
Of course, technology only gets you so far when it comes to these kinds of problems. It would be disingenuous of me to suggest otherwise. It has always been and will continue to be important to establish clear and rigorous processes around the way you deploy, manage, and change environments. This just gives you an idea of some of the tools you can leverage to aid in the implementation of those processes.
One of the fundamental tenants of IBM Workload Deployer is a choice of cloud deployment models. Starting in v3.0, users will be able to deploy to the cloud using virtual appliances (OVA files), virtual system patterns, or virtual application patterns. The ability to provision plain virtual appliances is a way to rapidly bring your own images, as they currently exist, into the provisioning realm of the appliance. As such, I think the use cases and basis for deciding to use this deployment model are fairly evident. However, when comparing the two patterns-based approaches, virtual system patterns and virtual application patterns, the decision requires a bit more scrutiny.
Our pattern approach is a good thing for you, the user. Basically, when we refer to patterns in the context of cloud, we are referring to the encapsulation of installation, configuration, and integration activities that make deploying and managing environments in a cloud much easier. Regardless of what kind of pattern you end up using, you benefit from treating a potentially complex middleware infrastructure environment or middleware application as a single atomic unit throughout its lifecycle (creation, deployment, and management). In turn, you benefit from decreased costs (administrative and operational) and increased agility via rapid, meaningful deployments of your environments. That said, it is imperative to understand the differences between virtual system and virtual application patterns, and more importantly, it is important to understand what those differences mean to you. Let's start by considering the admittedly simple 'Cloud Tradeoff' continuum below.
In the above graph, the X-axis represents the degree to which you have customization control over the resultant environment. The degree of control gets lower as we move from left to right. The left Y-axis represents total cost of ownership (TCO), which decreases as we move up the axis. The right Y-axis represents time to value, which similarly decreases as we go up the axis. Naturally, enterprises want to move up the Y-axis, but, and it can be quite a big but, they are sometimes hesitant to relinquish much control (move to the right on the X-axis) in order to do so. In that light, I think it helps to explore our two patterns-based approaches a bit more.
The most important thing to understand about this continuum is that the X-axis really represents the customization control ability from the point of view of the deployer and consumer of the environment. An example is probably the best way to explain. Let's consider a fairly simple web service application that we want to deploy to the cloud. If we were to use a virtual system pattern to achieve this, we would probably start by using parts from the WebSphere Application Server Hypervisor Edition image to layout our topology. We may have a deployment manager, two custom nodes, and a web server. After establishing the topology, we would add custom script packages to install the web service application and then configure any resources the application depended on. Users that wanted to deploy the virtual system pattern would access it, provide configuration details such as the WAS cell name, node names, virtual resource allocation, and custom script parameters, and then deploy. Once deployed, users could access the environment and middleware infrastructure as they always have. That means they could run administrative scripts, access the administrative console provided by the deployed middleware software, and any other thing one would normally do. The difference in using virtual system patterns is not necessarily the operational model for deployed environments (though IBM Workload Deployer makes some things, like patching environments, much easier). Instead, the difference is primarily in the delivery model for these environments.
Using a virtual application pattern to support the same web service application results in a markedly different experience from both a deployment and management standpoint. In using this approach, a user would start by selecting a suitable virtual application pattern based on the application type. This may be one shipped by IBM, such as the IBM Workload Deployer Pattern for Web Applications, or it may be one created by the user through the extensibility mechanisms built into the appliance. After selecting the appropriate pattern, a user would supply the web service application, define functional and non-functional requirements for the application via policies, and then deploy. The virtual application pattern and IBM Workload Deployer provide the knowledge necessary to install, configure, and integrate the middleware infrastructure and the application itself. Once deployed, a user manages the resultant application environment through a radically simplified lens provided by IBM Workload Deployer. It provides monitoring and ongoing management of the environment in a context appropriate for the application. This means that there are typically no administrative consoles (as in the case of the virtual application pattern IBM ships), and users can only alter well-defined facets of the environment. It is a substantial shift in the mindset of deploying and managing middleware applications.
Okay, with that explanation in the bag, let's revisit the diagram I inserted above. I hope it's clear that, all things being equal, virtual application patterns indeed provide the lowest TCO and shortest TTV because of the degree to which they encapsulate the steps involved in setting up complex middleware application environments. So, let's get back to my assertion that the customization control continuum really applies to the deployer and consumer. Why do I say that? It's simple. In the case of either the virtual system pattern or the virtual application pattern, the pattern composer has quite a bit of liberty in how they construct things. Sure, we enable you right out of the chute by shipping pre-built, pre-configured IBM Hypervisor Edition images, as well as pre-built virtual system and virtual application patterns. The key is though, that the IBM Workload Deployer's design and architecture also enables you to build your own patterns -- be they the virtual system or virtual application type. With anywhere from a little to a lot of work, you can build virtual system and virtual application patterns tailored to your use cases and needs.
At this point, you may be saying, "Well now you have really confused things! How am I supposed to decide what kind of patterns-based approach fits my needs?" I have some advice in that regard. First, map your needs to things that we enable with the assets you get right out of the box with IBM Workload Deployer. If your application fits into the functional scope of one of the virtual application patterns that we ship, use it. If you can support the application by using IBM Hypervisor Edition images, virtual system patterns, and custom scripts, do it. In this way, you benefit most from the value offered by IBM Workload Deployer. However, if you find that you cannot use any of the assets we provide right out of the box (e.g. you want to deploy your environment on software not offered in IBM Hypervisor Edition form or in a virtual application pattern), then ask yourself one simple question: "What do I want my user's experience to be?"
In this sense, I primarily mean a user to be a deployer or consumer of your patterns. You need to decide whether you favor the middleware infrastructure centric approach afforded by virtual system patterns, or if you prefer the application centric approach proffered by virtual application patterns. There is no way to answer this generically for all potential IBM Workload Deployer users. Instead, you have to look at your use case, understand what's available to help you accomplish that use case, and finally, decide on what you want your user's experience to be. I hope this helps!
Application-centric cloud computing is the main thrust behind the new capabilities of IBM Workload Deployer v3.0. But what does that really mean? After all, application-centricity is really just a concept. Granted, it is an important concept, but it is fairly meaningless until it is put into action or implemented. IBM Workload Deployer does just that with its new Virtual Application Patterns (VAPs).
VAPs are the embodiment of the workload pattern approach I briefly discussed in an overview post a few weeks back. The idea with a VAP is to give the user an interface through which they can provide their application, specify dependencies, declare functional and non-functional requirements and then deploy. Of course application middleware is a part of the overall solution, but IBM Workload Deployer has the smarts to build, configure, and integrate the necessary infrastructure in order to support the user's application. This is completely hidden from the user, so they are liberated to focus on the application and its requirements.
If we scratch a bit further beneath the surface of a VAP, we see that these patterns contain three primary pieces. These primary pieces are components, links, and policies, and they are fundamental to understanding how virtual application patterns work. Let's start with the building blocks of VAPs, components. Put simply, components represent different resources and functionality profiles that make up your application environment. As an example, the IBM Workload Deployer Pattern for Web Applications is a VAP that contains components for an EAR file, WAR file, message queue, and any number of other components that are typical requirements for a web application. The components will certainly vary based on the workload type (i.e. the components included in a web application VAP would be different than those included in a batch application VAP), but they are the foundation of any VAP.
From the ground up, the next logical element we come to in the VAP is a link. A link is a way to declare a dependency or integration point between two components. As an example, consider a VAP with a WAR file component and a database component. You might draw a link between the WAR component and the database component to indicate that your web application uses or otherwise depends on the database. IBM Workload Deployer interprets this link, and takes it as a directive to configure the integration between the two components as a part of deployment. In this case, that may mean configuring a data source in the application's container. This is just a simple example, and an application may have any number of links between components.
Finally, we come to the policy element within the VAP. A policy is a way for a user to specify functional and non-functional requirements for their application environment. Users attach policies to the VAP, or to components in their VAP, and IBM Workload Deployer interprets and enforces those policies. In the context of a web application, one example of a policy could be a scaling policy. The scaling policy might indicate scaling requirements for the application that included minimum application instances, maximum application instances, and conditions that triggered scaling activities. IBM Workload Deployer would use the information in a scaling policy within a VAP to appropriately manage the deployed, running environment. Other examples of a scaling policy may include a JVM policy that provides configuration directives for the java virtual machines in your application environment or a logging policy that defines logging configuration options. In any case, the policy element allows VAP builders to influence the configuration and management of the application environment.
In the example VAP below you can see the use of components (Enterprise Application, Database, User Registry, Messaging Service), links (blue lines between components), and policies (Scaling Policy, JVM Policy):
In total, when I look at a VAP a particular word sticks out to me: declarative. VAPs really enable declarative, application-centric cloud computing. What do I mean? By declarative, I mean you are telling IBM Workload Deployer what you want, but not necessarily how you want it done. It is the job of IBM Workload Deployer to take care of the how. This shift in approach to application environments enables the potential for significant savings, and more importantly to me, lays the foundation for a more agile, flexible approach to deploying and managing application environments.
There will be more in the weeks and months to come on IBM Workload Deployer, so stay tuned. I also want to put a plug in for a new blog from Jason McGee. For those that do not know Jason, he is an IBM Distinguished Engineer, and the lead architect behind IBM Workload Deployer. Be sure to check out his blog for insights on this new offering, as well as for all things cloud.
When one uses IBM Workload Deployer (previously WebSphere CloudBurst) to deploy a virtual system pattern, they benefit from a completely automated deployment process. The automation includes the creation and placement of virtual machines, injection of IP addresses, initiation of internal processes, and invocation of included scripts. Most of these processes are straightforward and require little more than a brief overview. However, the placement of virtual machines stands out, and it's inner workings are the subject of quite a few questions when I discuss the appliance. With that in mind, I thought I would provide a little more information on how the placement algorithm in IBM Workload Deployer works.
The placement subsystem in IBM Workload Deployer considers three primary elements: compute resource, availability, and license optimization. Compute resource availability is the gating factor for placement. That means that IBM Workload Deployer first looks at the available CPU, memory, and storage resource in the collection of hypervisors making up the cloud group(s) you are targeting for deployment. If a particular hypervisor cannot provide enough resource based on the amount you requested for your deployment, then it is automatically taken out of the eligible hosts pool. It is important to note that IBM Workload Deployer will overcommit CPU, and it will overcommit storage if you direct it to do so. It will not overcommit memory because that could severely degrade the performance of the application(s) running in the virtual machines.
After choosing the pool of hypervisors that are capable of hosting the virtual machines in your deployment from a compute resource perspective, the appliance then considers high availability. To better understand this particular placement stage, let's consider an example. Consider you are deploying a pattern based on WebSphere Application Server Hypervisor Edition and it contains two custom node parts. It is conceivable, and in fact likely, that these two custom node parts will host members of the same cluster, and thus the two nodes will support the same applications. As such, IBM Workload Deployer will attempt to place the two custom nodes on different physical machines in order to prevent a single point of failure. Of course, this depends on having two hypervisors with enough resource (CPU, memory, storage) to host the virtual machines, but the appliance makes that decision in the first placement stage.
After considering compute resource and high availability, IBM Workload Deployer moves to the last stage of placement: license optimization. In this stage, the placement subsystem attempts to place the virtual machines on hypervisors in a way that minimizes the licensing cost to you. The appliance can do this because it is aware of IBM virtualization licensing rules and takes those into account during this stage (if you aren't familiar with virtualization licensing rules and you are curious, ask you're sales representative to explain some time). During this stage, it will not violate any resource overcommit directives or rules in place, nor will it compromise system availability, but it will seek to minimize costs within these parameters.
At this point, I should make something clear that may already have occurred to you. You can override most of these placement rules by creating a cloud group containing only one hypervisor. In this case, IBM Workload Deployer will put all virtual machines on the single hypervisor until it runs out of compute resource (memory is likely to be the constraining factor). I would not suggest that you do this unless you have a good reason or you are in a simple pilot phase, but I do like to point out the art of the possible!
While not incredibly deep from a technical perspective, I do hope that this provided a few helpful details on what goes on during the placement stages of deployment. If you have any questions, do let me know.
Jason McGee will be leading the second GWC Lab Chat this week on Wednesday, 4/20. The very timely topic is related to recent announcements from IBM regarding the IBM Workload Deployer (see previous posts). Entitled "Application-Centric Cloud Computing" the discussion will focus on the concept of deploying and managing your application workloads in a shared, self-managed environment rather than manually creating and managing the application middleware topologies. It places the focus on the application rather than the infrastructure. This concept promises to deliver greater simplicity, elasticity, and
density among other things. It can position your business to react more
quickly and efficiently to the increasing demands of your customers and
free you from the managing all of the details.
Many of you may have already heard Jason speak last week at IMPACT 2011 in the cloud mini main tent or perhaps at any number of other sessions that Jason was involved in. Jason is the key architect behind IBM's WebSphere cloud activities. Obviously, Jason understands the cloud space very well and has a clear view of the evolution into Application-Centric Cloud Computing. This GWC Lab Chat will provide the opportunity to get your questions answered and share your perspective on this technology.
Jason will provide a brief introduction to the concepts and ideas and then lead an open discussion. Put it on your calendar and plan to attend - and please plan to bring your questions and comments to help foster a rich discussion. We want to hear from you.
If you haven't registered yet it is not too late - learn more and register here. It is easy to register and there is no cost. This is a very timely event and a great way to dig a little more deeply into concepts you first heard at IMPACT or perhaps hear them for the first time. Don't miss it!