Since the IMPACT conference, there has been quite a bit of buzz around the new features, capabilities, and enhancements coming in WebSphere CloudBurst 2.0. In addition to the updates for the appliance, there are some updates to the IBM Hypervisor Edition virtual images as well. In particular, there is one new offering that I want to make sure is getting more than a mere 15 minutes of fame.
What is this new offering that deserves some time in the spotlight? Well, it is the Intelligent Management Pack for the WebSphere Application Server Hypervisor Edition. Still not sure what this is? Simply put, it is an optional add-on to the WebSphere Application Server Hypervisor Edition that enables WebSphere Virtual Enterprise capabilities in the environments dispensed by WebSphere CloudBurst.
If you are not familiar with WebSphere Virtual Enterprise, this still may not mean much yet. Essentially, the use of the Intelligent Management Pack means you create environments that contain capabilities to dynamically manage your application runtime environment. This includes, but is not limited to, the following capabilities:
Dynamic clustering: Create WebSphere Application Server clusters whose membership changes autonomically in order to meet the needs of your applications. You create service level agreements to define the needs for your applications.
Application health monitoring: Monitor the health of your applications by assigning health policies. These policies designate the condition to monitor for (i.e. memory leaks), and they dictate what action to take in case the condition occurs (i.e. restart the server).
Application editioning: Manage multiple versions of your applications and roll out new versions of your applications without incurring downtime. This is essential if you consistently deliver updates to your applications deployed in production environments.
On-Demand routing: Build WebSphere CloudBurst patterns that include On-Demand Router parts. On-Demand Routers are a key component of WebSphere Virtual Enterprise environments and act as an enabler of some of the functionality discussed above.
If you are a user of WebSphere Virtual Enterprise, or otherwise knowledgeable with the product, the Intelligent Management Pack should be pretty familiar to you. When you deploy a pattern built from WebSphere Application Server Hypervisor Edition with the Intelligent Management Pack, you end up with a WebSphere Virtual Enterprise cell. When you log into the administration console, you will see the WebSphere Virtual Enterprise console. You can use any of the features in the normal WebSphere Virtual Enterprise product in the environment created by WebSphere CloudBurst.
Be on the lookout for more information concerning the Intelligent Management Pack. I know there is an article in the works, and we will also be working on some short demos for our YouTube channel. In the meantime, please reach out to me here or on Twitter (@damrhein) with any questions or comments.
Looking for a reminder of the difference a year can make? If so, just take a look at the last year or so for the WebSphere CloudBurst product. Since about this time last year, we have seen the release of versions 1.1, 1.1.1, 2.0, and 188.8.131.52, each one bringing their own set of major enhancements and features. Owing to this aggressive pace, it is sometimes easy to miss out on the latest capabilities of the product. For that reason, I wanted to give a brief rundown of some (definitely not all) of the major additions to WebSphere CloudBurst over the past year.
PowerVM and z/VM support: WebSphere CloudBurst 1.1 introduced support for PowerVM (based on Power5 and Power6 systems), and version 1.1.1 introduced support for z/VM. This means that a single WebSphere CloudBurst Appliance can provision to VMware, PowerVM, and z/VM virtualization platforms.
Power7 support: WebSphere CloudBurst 184.108.40.206 introduced support for Power7 systems, thus allowing users to take advantage of the significant enhancements provided by Power7 via WebSphere CloudBurst deployments.
Expansion of the IBM Hypervisor Edition portfolio: The portfolio of images that you can deploy using WebSphere CloudBurst now includes WebSphere Application Server, WebSphere Process Server, WebSphere Portal Server, WebSphere Business Monitor, WebSphere Message Broker, and DB2. In addition to adding new images, we also expanded the platform and operating system support for existing images. For example, you can take advantage of the Red Hat Enterprise Linux OS for WebSphere Application Server Hypervisor Edition, and you can deploy WebSphere Process Server Hypervisor Edition to z/VM infrastructure.
Addition of the Intelligent Management Pack: The Intelligent Management Pack is an optional feature of the WebSphere Application Server Hypervisor Edition that allows you to take advantage of autonomic, policy-driven runtime management capabilities in your deployed environments. This includes the ability to create proactive health policies for your environments, assign SLAs to your applications, manage the update of applications, and more.
License management capabilities: In WebSphere CloudBurst version 2.0 and later, you can make use of license monitoring and management functionality. This allows you to get both point-in-time and historical views of software PVU usage within your cloud, and it allows you to setup policies concerning the usage of PVUs for WebSphere CloudBurst deployments.
Environment profiles: WebSphere CloudBurst provides quite a bit of out-of-the-box deployment automation in terms of selecting hypervisors, assigning IP addresses, and more. However, sometimes you need more control over exactly how this happens. WebSphere CloudBurst 220.127.116.11 introduced environment profiles that you can use to exercise more control over how deployment happens in WebSphere CloudBurst.
In my view, this is quite an impressive list of features delivered within a year's time. I should also reiterate that this is by no means a complete list, but just a selection of some of the major enhancements during this time. If you have any questions about the above additions, or if you have any questions on other features, please let me know.
We've begun to seed this location with all sorts of helpful information on IBM Workload Deployer. Check it out and you will find links to a "getting started" section, articles, demos, redbooks, whitepapers, pointers to various blogs where authors write about private clouds or IBM Workload Deployer (yep, this blog is included), links to product documentation and education assistant, upcoming events, and more included in the wiki. We're still populating this location with content and we're looking for input on how to improve things ... so please provide your feedback and check back often to see how it evolves.
The content provided in the community is open and visible to everyone immediately. However, there is even more value if you create an id (or use your existing developerWorks id) to become a member of the community. Members can participate in the many collaborative elements that the community provides. This includes the ability to open discussions and collaborate on the forum, post blog entries in the IBM Workload Deployer community blog, or even share content that you have created which may be of interest to others.
There is even a specific section in the community focused on the Plugin Developer's Kit that Dustin mentioned in the previous post on extensibility ( see IBM Workload Deployer PDK wiki page ).
So please visit this new IBM Workload Deployer community and send us your feedback so that we can improve and grow this into a valuable resource. Ultimately, we want this to be a place where we can help each other be successful using IBM Workload Deployer. We also want to learn valuable insights from your experiences with IBM Workload Deployer so that we can continue to make improvements and optimizations in the appliance with the goal of improving your private cloud experience, making your business more agile and efficient. As always, please send us your feedback.
I write a lot about WebSphere CloudBurst script packages. Typically, I write about what they are, how to create them, and even provide some samples from time to time. I find that most of the time I'm either writing or talking about script packages from the standpoint that they allow you to automate the delivery of customizations to environments you deploy with WebSphere CloudBurst. More specifically, I usually explain how you can include these script packages in your patterns to ensure that your custom scripts execute as part of every pattern deployment. The truth is, that is not the whole story. In fact, it's only 1/3 of the story.
In WebSphere CloudBurst, when you define a script package you also define its execution mode. The execution mode can be one of three values, and it indicates the invocation time for the script. The default value is at virtual system creation, and that tells WebSphere CloudBurst to automatically invoke the script as part of the deployment process. This seems to be the most commonly used execution mode, and in the original version of WebSphere CloudBurst it was the only available mode (which probably attributes to why I only usually tell 1/3 of the story here). As you may expect, there is a wide range of usage scenarios for this class of script packages including installing applications, activating monitoring agents, registering cells with an externally managed DNS server, and much more.
If you are like me (and many humans), you enjoy and actually expect symmetry. In that regard, it probably comes as no surprise that there is a script package execution mode called at virtual system deletion. As the name indicates, this class of script packages executes as an automatic part of the virtual system deletion process. When a user tells WebSphere CloudBurst to remove a virtual system, before it shuts down the machines in the system, it will run each script package marked to execute at virtual system deletion. Typical use cases for these scripts include removing information about the cell from externally managed DNS servers, freeing up connections with external systems, and other external 'clean up' activities.
So this leaves the final execution mode for script packages, the when I initiate it mode to be precise. This class of script packages executes when explicitly triggered by a user. In the virtual machine detail section for a deployed virtual system, you can see a list of user-initiated script packages for a given machine. There is a start button by each of the user-initiated script packages that allows you to invoke the script when, and as many times as you need to. While these script packages have many different use cases, the most common use case is to deploy application updates. Users build these application update scripts, attach them to a pattern, and invoke them whenever they want to deliver an updated application into their already deployed environment.
WebSphere CloudBurst script packages are one of the main vehicles for delivering your customizations to your cloud environments. The three execution modes mentioned above allow you to determine when the right time to deliver those customizations is.
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!
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!
The reason I suggest the application proxy approach is twofold. First, it affords you the ability of having custom interactions with the REST API. For instance, you may insert logic into the server-side proxy code that returns only a subset of the JSON data contained in the response from the appliance. Alternatively, in an effort to reduce the chattiness on your client-side, you may join JSON data from multiple different REST requests to the appliance to fulfill a single client request. You may even decide to represent the data in an all together different format than JSON. All of these options and many more are available to you if you implement an application-based proxy to the REST API.
The second reason I suggest the application approach is that it is easier, and seemingly safer, to not deal with user passwords on the client-side. If you setup your application proxy, you can configure it to retrieve the appropriate password from a secure location (like an encoded file) based on information passed along in the request. This means the password information is only present in the request (in encoded form of course) from the application proxy to the WebSphere CloudBurst Appliance.
The good news about the application-based proxy approach is that it is simple to put in place. I composed one using the open source Apache Wink project. The Apache Wink project is an open source implementation of the JAX-RS specification (and then some), and it enables you to develop POJOs that are in turn exposed in a RESTful manner. In my case, I had a single resource POJO:
The Apache Wink runtime routes any HTTP GET request whose path is like /resources/* to the getResources method in the WCAResource class. This method passes along information taken from the query string (the host name of the target WebSphere CloudBurst Appliance and the requesting WebSphere CloudBurst username), as well as the HTTP path information and sends it on to the getResource method declared as follows:
The getResource method above uses the WebSphere CloudBurst host name and the request path to construct the URL for the corresponding WebSphere CloudBurst REST API call. Next, it constructs an Apache Wink Resource object and sends the REST request along to the WebSphere CloudBurst Appliance. How do we authenticate this request? We use the WebSphere CloudBurst username (sent as a query string parameter) to retrieve the appropriate encoded password information. Once we have that, we construct the necessary header for basic authorization over SSL.
The application-based proxy shown here is simply a pass-through. It does not manipulate the data returned from the WebSphere CloudBurst REST API, nor does it map a single client-side call to multiple REST requests. However, it would be simple enough to extend it to do any of those things. If you have any questions about the code here, please let me know. I'd be happy to share more of the code, or talk about how and where to extend it.
I was very encouraged by the consistently positive response we got at IMPACT for our WebSphere CloudBurst and Rational Automation Framework for WebSphere (RAFW) integration. I believe there were many reasons for this response: accelerated time to value, decreased investment needs for activities that are not core to your business, lowered barrier of entry for provisioning and configuring WebSphere cells, and much more. While those are certainly all very real and valuable benefits, I also believe that quite a bit of interest in this integrated solution comes from the fact that it is applicable to a number of needs common to you, our WebSphere users.
With that in mind, let's look at some (not all) of the scenarios where WebSphere CloudBurst and RAFW integration can help you:
Create WebSphere CloudBurst patterns that include configuration without scripting: Users love our WebSphere CloudBurst patterns. They really see the value in codifying both the topology and configuration of their application infrastructure. However, some users do not have existing WebSphere configuration scripts and do not have the time and/or resource to invest in creating these scripts. They are looking for a solution that provides not only the provisioning of WebSphere environments but also the configuration of said environments (configuration beyond what our IBM Hypervisor Edition images encapsulate, specifically application-oriented configuration). RAFW provides this capability in the form of 500+ out-of-the-box configuration actions for WebSphere environments. This includes actions to create JDBC resources, create JMS queues, deploy applications, configure application containers, and much, much more. You can create WebSphere CloudBurst patterns that contain a special script package, which points back to a RAFW project containing a set of configuration actions. During deployment, WebSphere CloudBurst will provision your WebSphere environment and then cause the invocation of the specified RAFW project, which in turn runs a set of configuration actions against the provisioned environment. This means you can set up full-blown, ready-to-go application environments with absolutely no user-supplied scripting. In fact, I took this approach to setup a J2EE performance benchmark application, DayTrader 2.0, running on WebSphere Application Server. Those of you familiar with the application know this is not a trivial environment to stand up. Yet, I did it without having to personally write a single line of configuration scripting, and it was all ready to go in around thirty minutes.
Creating WebSphere CloudBurst patterns from existing environments: This comes up all the time. I go through a standard introduction to WebSphere CloudBurst, users see the value, love the patterns-based approach, and immediately want to know how they get their existing environments into the form of a pattern. RAFW, along with the special WebSphere CloudBurst script package, can make this a straightforward and hardened process. You use a capability in RAFW to import the configuration of an existing cell, thereby creating a RAFW environment for that configuration. You then create a WebSphere CloudBurst pattern with a topology congruent to your existing environment, attach the special script package I mentioned earlier, and you are done with the import! When you deploy this pattern, you simply specify the RAFW environment that you created earlier (the one that holds the configuration data for your existing environment) and a RAFW project that will apply the configuration data in that RAFW environment to the WebSphere environment provisioned by WebSphere CloudBurst. The creation of the WebSphere environment, as well as its configuration, happens in a completely automated fashion.
Configure, capture, reuse: There are many situations that may require you to make manual changes to a WebSphere cell after it has been deployed. For example, during performance testing for your application, you might discover that you need to tweak the number of available threads in the web container. As another example, for the first setup of a given application environment, you may want to quickly deploy the cell using WebSphere CloudBurst and then manually install and configure your applications to make sure everything is just right. In either case, it is likely that you want to capture the updated configuration and make sure that any future deployments use those updates. Again, WebSphere CloudBurst and RAFW makes this simple. First, you build a pattern that encapsulates your WebSphere topology (the types and quantity of nodes you want) and attach the special script package mentioned above. For the first deployment, you simply specify the name of the new RAFW environment you want to create. Once the system is up, you log into the WebSphere administration console, make your necessary customizations, and then you use RAFW to import that updated configuration thus updating the initially created RAFW environment. For subsequent deployments, you simply deploy the same pattern, specifying the same RAFW environment as well as a RAFW project, which RAFW automatically created for you during the first deployment. This project applies the configuration (the one you manually established and imported into RAFW) to the WebSphere environment setup by WebSphere CloudBurst.
Configure WebSphere environments across virtual and physical settings: It seems that in many cases our users manage the same WebSphere environment across both virtual and physical settings. For example, they may provision the application environment using WebSphere CloudBurst for everything from development to pre-production, and then for production provision that same environment to a set of physical servers. At least, they try to provision the same environment. In reality, it is tough to reproduce the exact same configuration once you break from the WebSphere CloudBurst patterns-based approach. However, if you stored the configuration of your WebSphere cell as a RAFW environment, you could apply that configuration data to a WebSphere cell regardless of whether it existed in the physical or virtual world. Once you move to physical, you do lose out on the fast provisioning, WebSphere intelligence, cloud management capabilities, and automated integration with RAFW that you get when using WebSphere CloudBurst, but if it is in your process to move to physical hardware at some point, reusing the same RAFW environment certainly eases the migration task.
I hope this sheds some light on some of the common issues WebSphere CloudBurst and the Rational Automation Framework for WebSphere can combine to solve really well. This is by no means an exhaustive list, but really meant to point out the broad application of the solution. If you want to see how it works, check out this video.
Recently, IBM has made its presence in the cloud computing market known with a series of offerings and partnerships that position Big Blue nicely. There have been announcements of university partnerships, new cloud services and clients, and intent to deliver IBM software with Amazon Web Services. To further cloud computing and IBM’s offerings in cloud computing, teams of technical evangelists have been formed to spread the good news. I have joined one of these teams, and I’ll be here from time to time to talk about IBM’s work in the clouds.
Since we are just getting started, I figure it’s appropriate to touch on the definition and composition of cloud computing. I have read and heard hundreds of definitions for cloud computing, and they all make good points. Nearly every single definition describes a computing solution in which resources, both hardware and software, scale up and down to meet the needs of the cloud consumer. That consumer may be an end-user accessing applications that run in the cloud, or it may be the application running in the cloud that depends on the lower layer services of the cloud. Most of the existing definitions also imply some autonomic capability in which not only does the cloud scale up and down, but it does so without administrator intervention based on policies declared by the consumer. Personally, I like many of these aspects, so I have tried to combine the elements that I think are most important: Cloud computing provides computing resources in a scalable, autonomic, governable fashion. These resources may be software, application infrastructure, or physical infrastructure, and the overall solution enables IT to be delivered as a service.
Attempting to define the anatomy of cloud computing seems to elicit as many opinions as defining cloud computing. For me, the three-layer approach sums it up quite nicely. While it’s true that some cloud solutions span multiple layers, the Google App Engine comes to mind, it provides at least a reference point for the discussion of cloud products.
Application Services: This layer is comprised of what we have come to know as Software as a Service. This layer is very familiar to us (GMail, Facebook, MySpace, etc.), and it is equally familiar with enterprise consumers (WebSphere sMash on EC2, Salesforce, Sugar CRM, etc.).
Platform Services: The platform services layer is made up of different services that support applications. This may include middleware, connectivity, data, and messaging services. Offerings, such as WebSphere Application Server Virtual Images, SimpleDB on AWS, and Memcache from Google are all good examples of platform services.
Infrastructure Services: Infrastructure services provide physical resources as needed. These include hardware, networking, storage, and more. IBM’s Blue Cloud, Amazon’s EC2, and Google App Engine are examples of infrastructure service providers.
Looking at all three layers, it’s plain to see that starting with application services, each layer builds on the other. However, that does not mean that each layer cannot be used independently of the other. In fact, companies often construct on-ramp paths to cloud computing that start with services in only one of the layers (i.e. virtualization of hardware).
So, there's my shot at defining cloud computing! To be sure, my view of the cloud has evolved over time. The more opinions and thoughts I read, the more I challenge my own view. For that reason, I’d like to hear what you think. What is the definition and anatomy of your cloud?
Lately, I have run into multiple situations where an IBM Workload Deployer user has been trying to decide exactly how they want to create their customized images for the cloud. Essentially, they have been trying to decide whether to use the native extend and capture capabilities of IBM Workload Deployer, or to pursue the use of the Image Construction and Composition Tool (also included with the appliance). The conversations have been interesting and challenging, but more importantly, they have been a reminder that constructing enterprise-ready environments for the cloud does not happen by magic. It takes thought, deliberate planning, sustainable design, and the tools to carry everything out.
The tools part we have covered. I have every confidence, bolstered by user experience after user experience, that IBM Workload Deployer and associated tools (like the Image Construction and Composition Tool) equip you to build highly customized, cloud-based application environments. In this post, I want to focus in on the thought process that goes into how you decide to build your customized environment. Specifically, I would like to talk about important points to consider as you try to understand whether to use the native extend and capture capabilities of IBM Workload Deployer or the Image Construction and Composition Tool.
To be clear from the outset, I am not trying to provide a decision flowchart in this post. For all intents and purposes, that would be next to impossible. Instead, I want to pose to you some important questions that you should ask of yourself, along with the reasons why I believe those queries to be important. Keeping in mind that this is not an all-inclusive list, here it goes:
Question: Are the customizations that you want to make congruent with an IBM-supplied image?
Reason: One of the first decisions you should make is whether or not you can start with an IBM-supplied image as the base for your customization. You need to know what middleware elements (type and version) make up your environment and what operating system should host that environment (version and distribution). You can match that information against the list of content that IBM supplies. If there is a match, you should start by looking at extend and capture to customize that image to meet your needs. If there is no direct match, you may be looking at the Image Construction and Composition Tool.
Question: Does your custom content supplement middleware content supplied in an IBM image?
Reason: If you simply need to add additional components that supplement software already in an IBM image, I believe it is best to first examine the use of extend and capture. Whether these components are IBM software or not is irrelevant as the extend and capture functionality does not care.
Question: How configurable do you want to make the custom content in your image?
Reason: If you are adding content into the image, you need to think about just how configurable you need it to be. When you use extend and capture, you add the content to an existing image in a manner that pretty well ends up being opaque to IBM Workload Deployer. To configure that content, you need to have script packages and make sure they are part of every pattern you create based on the image. Alternatively, if you use the Image Construction and Composition Tool, you can embed configuration behavior in the image's activation engine, and you can expose deploy-time parameters without needing to include script packages in every single pattern. As an example, if you need to add a monitoring agent into your environment, you would likely do this via extend and capture and end up with a pretty simple script package to configure that agent during deployment. If however, you need to create an image with a custom database, you would likely favor the Image Construction and Composition Tool as you could embed common deploy-time configuration parameters directly in the image. For a database, there are likely to be many more deploy-time configuration parameters that you want to expose as compared to a more simple monitoring agent.
Question: Is your main focus on making operating system changes?
Reason:If your primary focus is on making operating system changes AND the answer to the first question is that your target content aligns well with IBM-supplied images, then extend and capture is where you want to start. Of course, you need to make sure that you can make all necessary changes to the OS with extend and capture, but I will say that this capability is not very restrictive at all.
Admittedly, this is a short list, but I believe it is a good starting point for how you decide upon one approach versus the other. Also, I would be remiss not to point out that these tools are absolutely not mutually exclusive. Many users I work with use a combination of the two approaches. In fact, there are some use cases that call for both tools. Start by creating a completely custom image in the Image Construction and Composition Tool, and then subject that image to the extend and capture process in IBM Workload Deployer to customize it for a particular purpose, team, project, etc. I hope you find this helpful, and I welcome your feedback or thoughts!