Continuing my last post about using a service such as Twitter (or Yammer or equivalent) to create “pull” notifications that serve the individual, I’ve set up a Meister workflow to update the status of the Twitter handle @builds after a successful build.

I’ve set up a JBoss build in Meister involving a web service and consumer. This was originally developed in MyEclipse, but the Meister Eclipse plug-in allows the native Eclipse build to be externalized (a better approach than Maven). So, I am just dealing with that, which simulates a development continuous integration or QA build.

I have a workflow that has the two main Meister build tasks, “Generate Build Control File”, and “Build Targets”. The first gathers local and server metadata consolidating that into something like a makefile or Ant script depending on your perspective. The second is similar to running make or Ant.

This is a simple workflow to illustrate our messaging technique. Normally, we’d use an email notification task, but I’ve replaced that with an activity called “Tweet”. This calls a simple Perl script, called omtweet.pl that uses Net::Twitter. Here is why we use Perl a lot - the code is simple to update your Twitter status:

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use Net::Twitter;
 
my $twit = Net::Twitter->new(
  {username => "myuser", password => "mypass"; }); 
 
my $result = $twit->update(
  {status => "My current Status"});

I created a slightly more elaborate script that takes arguments and passes in a “Build Successful” message. If Java is your thing, look at Davanum Srinivas’ post and for .NET, there is Twitteroo.

Next, I run the build and we see the steps complete in real time on the workflow monitor.

The key is the last step, of course:

And, the proof is in the pudding:

I used the $(JOB_NUMBER) macro in Meister to get an incremental build number passed to omtweet.pl. Of course, following @builds and choosing device updates, I got a text message on my cell phone. I tried to get a picture of my cell phone with the message, but I haven’t worked out how to do that yet and it turned out terrible.

Well, this is a simple example, with a lot of possibilities. Meister wraps all build output in HTML and pushes to a web server. I’d like to include a shortened URL for that in the update. Currently we don’t have anything outside of a firewall, maybe I’ll try Yammer for that.

If you have any other suggestions, let me know. @seanblanton

There has been some talk around using physical, colored, lamps to notify build results (pragmatic automation, Carlos Sanchez, Richard Durnall, Alberto Savoia).

The idea comes from Lean Manufacturing principles developed by Toyota applied to software development. An “andon” paper lamp was a way to let other workers know there was a problem on the assembly line. The idea for builds is that while a build is running, an amber light flashes, letting other developers know not to run a build, a green light signifies the last build was completed successfully, and a red light means the build is broken and needs to be fixed.

While I’m sure it is an entertaining exercise to set this up, some simple software automation could achieve the same results, and it has obvious faults, like what if I am working from home?

Email is the de facto standard for build notification. There is a hardcoded mailing list somewhere and you get the email, even if you don’t want it, and you have to go and check your mail to receive it.

Twitter, on the other hand, puts the user in control of the notifications in true Web 2.0 fashion. Tweets are also ideal for receiving notifications via cell phone, where email is generally not. Consider the following cases:

• I can follow the build when I want, and unfollow when I want. No going to an admin to remove me from the list.
• I can turn on device updates so I get an SMS message about the result (maybe an important release is coming up), or I can turn off device updates, say, when I’m on vacation.
• I can retweet (forward) the build notification.
• You can put links in the message. Meister uploads all build logs in HTML format to a web server and we would include the link to that.

About a year ago, I used Meister with a post-build activity to Tweet the build result after a build. The activity was a simple Perl script using Net::Twitter. Let’s just say this experiment sort of fell on deaf ears.

Now I’m ready to roll with this again and you can follow my progress. I had created a Twitter account, @builds, for this purpose. In a day or two, you’ll see some tweets from that guy from one of my builds.

I’m interested in what other people have to say. Meister already uses Eclipse RCP as it’s front end, but most other build tools are still command-line and in the 1970’s. Let’s bring build management tools into the 21st century with Web 2.0 features.

In the Agile Scrum framework, a ScrumBut is a “reason why [you] can’t take full advantage of Scrum to solve the problems and realize the benefits.” Clearly, build problems are traditionally one of the biggest ScrumButs. Meister removes the scrum butt by taking variables out of the hands of operators managing the builds.

Ask for a build and get a build. Ask for continuous integration and test automation and coalescence and get it with Meister. Product owners should not be losing cycles to debugging builds, tweaking parameters to get different types of builds or in resolving confusion about what did or did not happen in a build or continuous integration workflow.

The client-server architecture and highly reusable build and workflow metadata extend the ScrumBut elimination to all developer machines and continuous integration build servers, creating a highly consistent build. Team members working on these different machines know exactly what to expect.

Since they know what to expect from the build, they can focus on resolving actual integration issues and testing rather than trying to make the build work in a consistent manner.

With our third nomination, we won the Jolt Award for product excellences in the change and configuration management category. You can view the announcement here.

While we have managed Jboss and WebSphere deployments using Meister and Mojo and we frequently manage resources for different target server environments through build, here is a company that focuses on both of those things.

I posted a comment about the reluctance of script writers to give up their scripting on their blog here.

It is just plain fun to run parallel workflows and builds and watch the activities and build steps light up the workflow monitor in real time like a Christmas tree. See this flash demo to see what I mean.

As customers go to machines with more and more cores, fewer machines are needed in the application lifecycle infrastructure, particularly for builds and code retrievals - the most resource intensive functions. This is helping to simplify the infrastructure, reduce maintenance and administration and drive down costs.

Several of our customers are running around 5000 builds and non-build workflows per month on two machines. The primary reason for two machines, in fact, is for disaster recovery, and the goal is to run both machines at less than half capacity so that in the event that one machine (or datacenter) fails, all the current capacity can be run as a contingency on the one machine that’s left.

Thread control is very simple with Meister and Mojo. Both use the omsubmit dependency manager program to handle this. Meister’s om program translates build events into workflow steps using omsubmit. The OMSUBMIT_MAX_USER_PROC value sets the maximum allowed number of threads.

You might think that if you are running dual, quad-core build machines that you should set the max threads at 8. However, Meister posts build operations to one thread and the associated logging operation to another. Compile operations notoriously use a lot of memory and CPU resources, but the logging operation posts to a server and waits for the operation to complete. There is really no disadvantage to setting the max threads higher than 16 in this case, so go ahead and do it.

As a non-build workflow example, I worked on JBoss deployments to 48 Linux machines. The workflow was parallelized into 48 activities each of which deployed to a single machine in parallel. The deployment activity was largely a remote execute operation that extracted archives on the remote machine. The extraction took about a second for a medium sized application. Again, this is a waiting situation where machine resources are essentially idle while the thread is in use, so use more threads. The machine was a dual, dual-core build machine and we set OMSUBMIT_MAX_USER_PROC to 50.

Watching the workflow monitor as the deployment ran, we could see roughly half of the machines light up (meaning actively running) at any one time and the entire deployment process synchronized all 48 machines in a little over two seconds.

So, don’t simply match your machine’s CPU threading capabilities - overclock! Aim high for max threads and try to determine where your performance is optimized. I’d love to provide you with some metrics as a function of thread count, but usually once something is working it’s on to the next project. I barely have enough time to blog!

It’s very common to have a code check-out step be part of an integration build. Far better it is to not check out code before a build. What? How is that possible?

Let me explain, Fred. The simple approach most of us take (and have to take when getting things started) has developers commit, commit, commit, and when it is time to deploy, check out the code, do a build, and then deploy the application. There is room here for both problems and optimizations. Doing a full check out of the code tree is more costly in terms of time than checking out only what has changed. Updating the code tree with a single commit is less costly than updating with a large number of commits.

You may be limited by the technology in-hand and how much you’ve invested in learning the technology and possibly customizing it. For example, if your file control tool can only do a full check out of a source tree, or that’s the only command you had time to implement in order to meet the deadline, or you don’t trust your tool to do incremental updates, then you are basically running the longest builds possible.

On the other hand, if you could update the code tree every time a developer does a commit with only the changed files, then you are ready to execute a build at any moment. This requires some deft manipulation of your file control tool, and that’s why you don’t see it more often.

You might think “continuous integration” will take care of this. Developer commits, update checked out, build is run. However, you may end up with a build, test execution and deployment that takes longer than the typical time between developer commits. You still have to do incremental updates and it only solves the problem in cases with very low developer activity.

I’d like to point out one tool that does an excellent job of post-commit code checkout, CA Software Change Manager for Distributed. CA SCM (for short) is the tool, formerly known as Harvest, from the company formerly known as Computer Associates. CA SCM is a highly scalable (1000’s of developers) file control tool with a great lifecycle process model. We at OpenMake Software still have our very first customer still using OpenMake/Meister with CA Harvest/SCM after 11 years. While we have a reseller arrangement with CA, our partnership with CA in services has extended to 14 years.

About 10 years ago, OpenMake Software developed an integration with the then, Platinum Technologies’ Harvest product, modeled after the now dead Computer Associates product, Endevor Workstation, that had an excellent post-action code tree update. (Endevor for z/OS, a.k.a CA SCM for Z/OS is still very popular and has a similar functionality called ‘output libraries’ - following all this?) Our integration had the horrific name, ‘Har-refresh’.

As product partners, we finally transitioned Har-refresh from an external add-on to CA who have turned it into a core functionality of the product, called Hrefresh (a better name.) Rather than simply a post-commit check out, HRefresh updates the code tree after any action that updates a dynamic code view. This includes, renames, deletions, commits and code promotions and demotions. We like this because CA SCM does all the work and we cherry-pick sets of up-to-date code trees to build up an application source code stack for a build. We align Meister dependency directories with HRefresh-managed file system directories for a tight SCM (software configuration management) build.

This mechanism distributes the resource load for checking out code to times when builds are not required. It’s true that often times people want to build as soon as their code is checked in (or promoted), but on average it is a very big net win reducing build times.

This is just an example of the type of sophistication that is out there to prevent pre-build code check outs and save time on your builds.

One of OpenMake Software’s product strategies is to keep things simple. Build management is one of the most complex operations in all of the IT world, and one of our key benefits is to simplify, organize and automate the build process for development, testing and production.

We’ve seen a trend among our customers to simplify their build management infrastructure by going to fewer build machines with more CPU cores. Builds in particular use relatively more CPU resources than other resources as code is interpreted and compiled in memory and then finally written to disk. By reducing the total number of machines, rack space, procurement, administration and other IT overhead costs are reduced at great cost savings per machine eliminated.

Recently, I was at one of the big chip makers where they used dual quad-core CPU Linux machines for their development and builds. They had two machines and were able to control access to allow separate areas for development, testing and release builds in keeping with best practices. Having all the horsepower of 8 CPU cores on a single machine kept them from needing more machines.

Another customer does 6000 builds per month with Meister on just two build machines.

IBM, when selling BuildForge, likes to talk about big build server farms, because their tool does remote execution on multiple machines, as does Meister. However, BuildForge does not do builds at all. It can remotely execute your existing build scripts, but there is little real value add to that. BuildForge is also famously expensive. What happens over the next few years to the high investment in multi-machine remote execution software as the number of machines declines, perhaps dramatically?

A similar argument can be for Electric Cloud’s Electric Accelerator product. It’s possible in some cases, for C/C++ builds to gain an edge by pushing a compile operation to another machine, and then bringing it back. You would only do this to gain access to additional CPU resources. In the past, you might have 8 build machines that Electric Accelerator would farm operations out to. Now, you can pull all those operations into a single machine and there is no need for that functionality. Also, you are stuck with converting your GNU makefiles into other GNU makefiles.

Meister is optimized for multi-core CPU build machines and offers multi-threaded capability to both build events and non-build workflow events. You know where your build is and there are fewer dependencies on network resources. Both BuildForge and Electric Accelerator add additional overhead to build administration to coordinate across multiple machines - a dying practice, that no organization wants to invest in. Meister is the best bet for a future with fewer build machines with more horsepower.

We’ve been testing Mojo and Meister 7.2.1 and getting ready for their release on December 15. This is a maintenance release with bug fixes from users who’ve started running builds and workflows with Meister 7.2 and using the free workflow automation of Mojo and putting those releases through their paces. It also contains a lot of UI and documentation improvements.

Existing users of the 7.2 version of either Mojo or Meister will be able to upgrade via the update sites, http://www.openmakesoftware.com/mojo/update_site and http://www.openmakesoftware.com/meister/update_site, respectively.

Users interested in getting Mojo, the free workflow automation tool, and Meister, the industry leading build automation tool, can find download instructions on our website, http:///www.openmakesoftware.com.

We’ve heard from a number of companies that they are having problems with their WebSphere Eclipse headless builds and they are looking to us for a solution.

A headless build is an Eclipse function (and therefore an IBM WSAD/RAD IDE function) that allows you to execute Eclipse and some of it’s plug-ins at the command line. The GUI does not launch, but the main machinery does, and it makes use of the workspace metadata.

In theory this allows you to do the same build at the command line that was done in the GUI. It’s a nice theory that we subscribe to ourselves.

In practice, these companies do not feel they are successful for a number of reasons:

1. If it works it is slow. A slow build is almost as bad as a broken build.
2. Unexplained crashes in the middle of the build due to workspace corruption.
3. Crashes may leave the .lock file in the .metadata folder of the workspace. This prevents Eclipse from executing in the same location until it is cleaned up.
4. It’s a black-box build with a large number of operation swept

Meister takes a different approach and records the files and project types and then applies a traditional build with a mixture of Ant tasks and command line calls. This eliminates the need to even install RAD 7 on the build server, but you still need the runtime libraries.

I’ve worked with the IBM WebSphere EJBDeploy plug-ins and integrated Meister to actually call an Eclipse headless build via the WSAD/RAD ejbdeploy.bat file. As a rule, we always stick with the vendor-recommended approach, so we don’t have a choice. However, we don’t do the compiling and archive this way - just the EJBDeploy step.

By compiling and archiving the Java parts in a traditional way, we at least minimize the risk of a broken headless build and maximize the speed. And, yes the ejbdeploy step is usually the longest step in the build. The fact that IBM supplies the ejbdeploy.bat file at all, which mimics a command-line compiler, means we’re not the only ones taking this approach.

I’ll take that last one about ensuring a drive is mapped and make a Mojo activity template out of it so you only have to enter the drive letter and the share name. Here’s another one…

I have a workflow that can only run on a specific machine because it assumes certain software is installed (Git in this case). To fail a workflow that is not running on the correct machine, run this shell command at the beginning of the workflow:

if not “%COMPUTERNAME%”==”ASLAN” exit 1

I’ll make an activity template out of that one also, so then you only have to enter the computername. Note that this is case sensitive!

It’s true we can make one out of Perl that is platform independent.

In order to verify that a drive is mapped on Windows, and if not, map it, and then have the command complete with a successful return code, use this command:

dir O: > nul || net use O: \\computer\myshare

It should only return a fail code when it is unable to map a drive. I’m using this in one of my Mojo workflow activities…

How do you set up an automated build for EJB client JAR’s from the IBM Rational Software Delivery 7 development environment for WebSphere 6?

This question came up recently in my work for a major insurance company. When one extends the EJB client class, that is all a developer has to do as far as RAD 7 is concerned. When the developer deploys the JAR to the server, RAD 7 quietly generates stub source Java classes, compiles them and includes them in the JAR file.

An automated build in this context means that all the code the developer created in RAD 7 and checked into version control, is checked out of version control without RAD 7 and built exactly the way the developer intended. This is what OpenMake Meister is for.

One developer I was working with was concerned with how to generate those same source files in the automated build, which in his case was using OpenMake. He was familiar with how OpenMake uses the ejbdeploy command for building EAR’s with EJB server-side code and expected some equivalent for the EJB client.

Mercifully RAD 7 actually leaves the generated source files behind in the Eclipse project, in the standard source location. This means that we get the source code for free and there is really no need to regenerate it. All one has to do is check in the generated source to version control along with the developer coded source and build a normal JAR file in the automated build.

For the developer, this means:

1. Check in all the Java source code in the project. This is easy – better than picking and choosing which Java source to check in as the developer thought he had to do. This would be ultra-high risk for making a mistake and breaking the team’s automated build.
2. Assign the “Default Java JAR” configuration mapping for the EJB client project using the OpenMake Target Generator Eclipse plug-in.

A lesson to learn from this is that not all technologies or technology variants will have an impact to the build process. The developer was considering an idealist approach to reproduce every minute step of RAD 7, but the best solution was something practical and simple. Build management is part art and part dirty science. Having a “generate” step for the EJB client Java classes in the automated build only introduces an additional point of possible failure, and we build-meisters know we don’t need any more of those!

With the Web 2.0 evolution, information flow between people has changed from a ‘push’ paradigm (I send you an email) to a pull paradigm (I follow you on Twitter). How could this possibly relate to code management such as branching, merging and history? Well, Git’s distributed repository model and how one obtains code updates from “friend” repositories is similar to Twitter and how you obtain status updates on the people you choose to follow. Instead of communicating micro-blog entries or status updates, Git is communicating source code branch updates.

Also like how Facebook or Twitter allows you to specify a person’s name in lieu of the communication protocol identifier (email address or web page), Git uses aliases for long repository locations so you have a more direct, natural language and human feel to what you are doing: “git fetch linus” will pull changes from Linus’ repository, which you have only had to define once.

Here is a scenario where Steve and I are working on a part of the Linux file system to provide information useful for build management and dependency tracking, which Meister and other tools can take advantage of. Steve started by cloning the master Linux repository and started working away making changes. Steve asked me to work on another part of this project, so I cloned his repository, allowing me to pick up all his changes. I am now automatically following (Git calls it remote-tracking) Steve’s “master” branch of his repository since I started my repository by cloning his. The “master” branch is a.k.a. the “trunk” code stream. I can pick up his updates periodically with:

$ git pull

Now, I may also want to get updates directly from the master Linux repository, but it has a complicated URL that I won’t remember and only want to look up once. So, as a one-time command I do:

$ git remote add linux-nfs git://linux-nfs.org/pub/nfs-2.6.git


Forever after:

$ git fetch linux-nfs
* refs/remotes/linux-nfs/master: storing branch ’master’ …
commit: bf81b46


The “fetch” command doesn’t put the master Linux changes directly into my workspace, but off to the side for me to examine first (very nice). If I want, I can accept the changes into my local work tree. To tell me which repositories I am following (which friends), I do:

$ git branch –r
linux-nfs/master
steve/master
origin/master


“origin/master” is my own trunk. I could also get the full repository information associated with the short names, but as long as it works, I don’t want to know what it is. For me, this type of friendly and fluid interaction with repositories is one of the major advantages over CVS and Subversion.

Here comes buildr: yet another Java build tool. Hopefully I, or one of my other cohorts will check this out in detail soon. But, with my experience working with all manner of build tools, with 100 companies and many more development teams, I can already make a few observations.

First of all, why another build tool for Java? I am occasionally told that Maven or Ant is a perfect tool, but clearly the people behind buildr don’t think so. The choice of JRuby as the vehicle for delivering this tool, I think is probably a good one. JRuby is a scripting language in the same vain as Perl, which is used by Meister.

Doing software builds is an ugly business involving lots of file and operating system interaction. This is not where Java shines, but scripting languages can. As long as operating systems are written in C and not Java, C-like tools will be better and faster at interacting with them. Plain Ruby itself is C-based, and JRuby no doubt inherits C-like operating traits. Calling out to a Java compiler from Perl or JRuby, though it has its own JVM, does not represent a significant overhead compared with the file system operations and the compilation/translation itself.

Both Maven and Ant are relatively difficult to extend compared most other build tools, and I’ll be buildr beats them here. If you have all the Maven plug-ins and Ant tasks you need, then good for you. If not, then you have to start developing in Java and it becomes too much of an investment to sink into a build system. It is much cheaper to extend in JRuby or Perl. My frequently cited example is the XMLBeans compile step in Meister, written in Perl, which is only 40 lines of real code. The Maven plug-in is 60 pages of Java code and no one can tell me really what it is doing (I asked on all the forums). Less code is usually more transparent, which is also good for build audits.

I am a little disappointed to see them try to placate the Maven and Ant users by promising it is a drop-in replacement for Maven and they have all the Ant tasks covered. Both tools have their drawbacks and I don’t want to see another tool with the same deficiencies. They should have the cajones (or coñejos) to apply all their resources to what they think is a better tool (with its own unique benefits and deficiencies). I imagine offering Ant task equivalents is pretty easy because of the ease of coding in JRuby compared with Java.

They also don’t mention who is supposed to use the tool. Is it for individuals, small development teams, the enterprise? Maven falls short because it is only appropriate for development teams and not for stable, controlled, enterprise builds. Ant is not even tool, but a means to create some tools for small teams. I don’t think Meister will fear buildr either.

Well, since buildr is only in incubation status with Apache, I’m not sure how much time I’ll be able to spend on it, but I am curious and I’ll let you know if I find out more.

First, let me say how nice it is to have the Mojo workflow engine that allows us to manage the compliance checks, deploy to multiple machines in parallel and validate deployment. This makes our lives a lot easier and provides clear benefits for deployment via the parallelization, dependency management, scalability, logging and reporting. Underneath the covers, and for those of you who don’t have the luxury to use this almost-free product, there are some important low-level tools that are critical to the development, testing and operation of the Mojo JBoss deployment system on Linux.

With the most important listed first, they are:

1. JBoss support
2. The Perl executable (5.6-5.10) and base language
3. Perl’s Test::Simple or Test::More modules
4. Perl’s Test::Harness module
5. The JBoss twiddle.sh script or command equivalent
6. Perl’s XML::Twig
7. Perl’s Archive::Zip
8. vi
9. ssh
10. xterm

JBoss support wins hands down due to the number of bugs and critically important undocumented features. On a scale of 1 to 10 where 10 is the best documentation, I give JBoss about a 3 or 4. Googling doesn’t even help that much for deployment issues.

You may be surprised at the prominence of Perl, but if you think about what you are really doing and what the best tool for the job is, it makes sense. You are really moving an archive (a ZIP format file), copying XML files, creating directories, changing permissions, extracting the archive to the file system perhaps. Where did I mention Java? Nowhere. The twiddle.sh command comes in handy if you get the secret commands from JBoss support that tell you if the application you deployed has actually started correctly. Notice that this is a shell script suggesting we’re not the first to use non-Java tools to manage deployment.

Particularly on the testing side, I can’t think of a viable alternative to Perl testing. We need to test that we created this directory, changed that permission, updated that file timestamp, etc. We have about 300 test cases encoded in Perl that are run with every change to the deployment system. It takes about 20 seconds to write and run a simple test case in Perl.

Lessons? Use JBoss support early and often and use Perl.

When you work with a locking-type version control tool like CA Harvest, your Meister build project will appear in your Eclipse workspace as read-only when you check out an existing workspace. I’ve been using Eclipse for WebSphere development (WebSphere Studio Application Developer) and for JBoss via MyEclipse IDE. If you want to regenerate your Java targets, you first have to check out the Meister build project so that the files are writable.

Since this can lock the targets exclusively and prevent others from updating the target, you may not want to check out the build project, but you may still want to develop freely and update your local targets for Meister to build it. For this situation I recommend creating a separate build project that you may never check in to version control. It will be writable and it allows you great freedom for a maximally agile development environment. The ‘official’ build project may reference all the built archives in the workspace, but having your own local build project can allow you to focus for a unit build. For example, my workspace may contain an EAR project, a WAR project and one or more JAR projects. If I am principally working only on one of the JAR projects, my local build project can reference only that one JAR project.

When it’s time to release your JAR code updates to the system build and test environments, synchronize your workspace and check out the VC build project. Generate your targets, do a local system build and then check everything in. Your team system build will work fine!

I wanted to share a specific benefit I enjoyed while using Meister for Java development. As part of my role to help develop an automated JBoss build and deploy system, I ended up taking on a developer role for a web services security project for both JBoss and WebSphere. While the project involved about 1000 lines of Perl, it also got me writing simple web services and consumers for JBoss and WebSphere and building them using Meister and its Eclipse plug-in.

Believe it or not, I am still using WebSphere Studio Application Developer 5.1. While my specific tale involves that IDE, it is equally applicable to MyEclipse and Rational Application Developer set of Eclipse IDE’s. In my environment, CA Harvest is the version control/SCM tool and Meister is the build tool. After code is checked in from my desktop using the CA Harvest eclipse plug-in, the code is replicated out to a Linux server, where Meister performs the official system build that is sanctioned for deployment to the application server. There is also a Meister Eclipse plug-in that scans the WSAD workspace for build targets and dependencies. Meister stores this information in one XML file per build target and those files are also checked in to CA Harvest right along side the source code.

Working intensely within the WSAD Eclipse environment as the project manager cracked the whip, I worked with a consumer application and updated it according to the changes in the service WSDL and service endpoint URL’s. One thing I learned is that if one of the parameters for the consumer is tweaked, don’t bother tweaking the XML or generated code, just regenerate the whole client. WSAD will even check out the files before if they need to be. So everything looked good on my desktop with the service and consumer deployed to two separate WebSphere servers on ports 9080 and 9081. Now to get it into the enterprise ‘dev’ environment…

Using the ‘Generate Target Definitions’ feature of the Meister plug-in I updated the Meister build target XML definition files and checked in all my code. I then promoted the code in CA Harvest which automatically kicked off a ‘dev’ build in the Linux environment. I got an error back from Meister saying ‘jdmpview.jar’ doesn’t exist.

Since I knew my consumer app and its elementary nature, I knew that jdmpview.jar wasn’t one of my JAR’s and it must be one of WebSphere’s. Given that 200 other Java apps use the same build environment with the same standards, I probably didn’t use some new feature of WebSphere that no one else is using. Therefore, it must a problem on my local desktop with the version of JVM I was using.

Sure enough, the consumer app was using the base_v51 WebSphere runtime instead of the ee_v51. (I did inherit the initial version of the app from someone else!) And, oddly enough, there is an extra JAR in the base that is missing in the more fully featured Enterprise Edition. Meister correctly forced the runtime environment to be EE for the Linux build, overriding the developer selection. I switched the runtime in the Java build path properties, regenerated the Meister target definitions, checked them in and promoted them to a successful ‘dev’ build. Regenerating the target definitions had the effective of switching out the list of JAR files in the library path from the base_v51 set to the ee_v51 set. The whole thing including one bad and one good build took about 4 minutes.

The great benefit for me was the balance between developer and SCM functions. We could have applied more controls at the desktop level, but from my perspective, I prefer an Agile environment with more freedom even if it means occasionally hanging myself with my own rope. In this scenario I let the tools dot the I’s and cross the T’s and it took no more time than say, waiting for Outlook over VPN.

In developing Java applications for multiple server environments (e.g. dev, test and prod) there is a common pain-point of having to manage deployment descriptor or configuration files specific to each server. For example, you may have an XML log4j configuration file with some parameters different for different server environments. You may want to turn on debug messaging for the development server, but turn it off for production. At the same time, the Java source code will (eventually) be the same in production as it was in development. A similar situation applies for .NET application development.

Like many build management tasks, managing these environment-specific files is generally left to either manual or some type of scripting. This is really something that needs to have a high level of automation applied. Particularly in larger environments, much like scripted build management solutions, existing tactics fall short. This situation is in a far worse state than even the compile part of build management. It is not enough to simply have a script that can spit out some files. One of the biggest problems is information management and the fact that parameter values in the configuration files may be determined by different teams! How do a production engineering team and an application developer both feed inputs into the same XML file?

I’ve worked on this problem for several years and with a number of companies. The critical functionality can be broken down into two different items – information management and a processing engine. In an effort come up with something better, I’ve done a review of what’s out there and here is what I came up with:

• Ant ‘filter‘ task: As with many Ant tasks, this works great if you are an individual with a few items that need updating. It is a nightmare if you are working in a multi-team enterprise with multiple server environments. The main problem is that you have to constantly take working copies of XML files and insert a token for Ant to later re-replace. This leads to a management nightmare to synchronize parameterized copies of XML files with their working copies from the desktop environment. The advantage is that it works for any file type so you can use it for properties files as well as XML files.
• OOPS Consultancy Ant ‘xmltask‘: This is a good engine for specifying and performing changes to the XML and has a full feature set. In fact, we use this in some of the Meister build services. The problem is that it is only for Ant and therefore you have all the reuse, standardization and hard coding issues. Xmltask can provide part of the solution we are looking for, but we still have an information management problem to deal with.
• Maven: Maven has what is essentially the Ant filter task. The specifications are abstracted in the pom files, which is better than Ant, but it encourages templating of configuration files leading to all the problems associated with that (synchronizing templates with working files, testing templates, etc.)
• XML:DB XUpdate: This is a working draft of a specification to encode XML update instructions into an XML document. There is a Java implementation of XUpdate listed on the site called ‘Lexus’, but I couldn’t find anything on it. Since the build management task requires us to generate XML files, I’m not keen on generating XML files using xupdate tags that will allow me to generate other XML files.
• Perl XML::Twig: This has worked wonderfully for me on a back-end web services security effort and I could not be more happy with such a precise, elegant and brief XML library, which includes XPath. This is not a solution for Java or .NET developers, but it could serve as an engine to mimic xmltask or implement the XUpdate specification.
• Excel. Yes, I’ve seen Excel used effectively as the information management front-end to updating the XML. It is a convenient format to share among teams, it is centralized source of information, it can be checked into version control and it can be saved as an XML file itself for processing by another engine. In a large environment, you may have 5 or more server environments, lots of different components to configure, so you could have literally hundreds of parameters to manage. Excel gives you a nicely transparent way to view those values.

I’ve worked out a good system putting Meister build management metadata under version control. Why put it under version control when you can do a backup, you may ask? Well, there are times when you may want to develop a reusable workflow or update a Java build method script and test in an isolated test environment. For this you would use a separate test instance of the Meister server. Putting at least some of these files under control will help ensure that you move the known version of your tested server metadata file into your production environment.

There are a few other challenges to be aware of. You may want projects and dependency directories to be able to be created an edited in production while you simultaneously modify a workflow, for example. You don’t want to overwrite a dependency directory definition in production with an older one you are migrating from the test environment.

I’ve got a few other challenges as I’m using CA Harvest for version control and its excellent control over changes extends version locking to the file system by removing write access to files that are not locked by someone for change. Meister requires that most metadata files be writable, so if you check in files to CA Harvest directly, you will leave Meister metadata files read-only and that will cause problems.

So, here are a few tips from my now slick Meister metadata version control system:

• Use the …/meister/kbserver/tomcat/webapps/openmake.ear/openmake.war/ directory as the root of the file tree under version control. Don’t version anything outside of that tree, but do version everything under it for a simple boundary to your project.
• Before checking in/committing changes, copy files from the Meister runtime directory to an alternate workspace or temporary directory tree. Check in/commit from there, not the Meister runtime directory. This ensures that you don’t write into the runtime environment, possibly corrupting something.
• Before taking updates from version control, check them out to an alternate workspace, reference directory or other temporary directory. This is again to avoid corrupting the runtime environment. For CA Harvest, you can use the automated reference directories to copy from. Be careful not to preserve the read-only attribute when you copy from there. I used File::Copy::Recursive and its option not to preserve permissions for a simple, streamlined copy.
• Manage the check in’s and deploys (copy’s) according to the major subdivisions of the Meister metadata. My check in and deploy commands work by taking a directory relative to the openmake.war/ directory as an argument.
• Use the awesome Perl SCM project by yours truly to reduce your coding by 90% if you are using CA Harvest. CA Harvest also requires a number of other steps, such as creating a change package, locking files you plan to change to the package before checking them in, and breaking up the locking and check in commands into manageable chunks. The Perl SCM project helps with all that.
• If you can manage your changes incrementally, all the better. OpenMake Software’s HarRefresh and CA Harvest’s HRefresh manage reference directories with incremental changes. This gives you a workspace or reference directory with only the changes relative to a baseline, not the full baseline. This means if you changed only one workflow, then it is easy to copy just the one changed file to the production environment, instead of the whole baseline with only one changed file. You will have a very simple and transparent production change procedure with this – very nice.