Alternatives to filtering on lifecycle traceability links in CLM 6.0 configuration management enabled projects

Today I’d like to continue on the theme started in Finding suspect links and requirements to reconcile in Collaborative Lifecycle Management (CLM) 6.0 configuration management enabled projects by addressing another consideration from Enabling configuration management in CLM 6.0 applications.

Do you need to filter views based on lifecycle traceability links?

In CLM 6.0 for those projects with configuration management enabled, you can view artifacts with their lifecycle traceability links, but cannot filter by those relationships.  There are three key areas this impacts:

  • Limit by lifecycle status in DOORS Next Generation (DNG)
  • Traceability views for RQM test artifacts
  • Linking RTC plans to artifact collections

I’ll explore some alternative workarounds to these in this blog.

Limit by lifecycle status in DOORS Next Generation (DNG)

In CLM 5.x, views of requirements artifacts can be filtered by the status of lifecycle artifacts linked to them.  The same is true in CLM 6.0 but only for projects that don’t have configuration management enabled.  This limitation should be addressed in a future release by work item 97071.   Below is an example showing all feature requirements with failed test case runs.

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Similarly, the following shows all feature requirements whose linked development items have been resolved.

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In CLM 6.0, for configuration management enabled projects, the lifecycle status filter option doesn’t even appear.

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It is still possible to show a view of requirements with their lifecycle traceability links shown; it’s only the filtering that isn’t possible (at present).

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Here you could scroll through the Validated By column, for instance, and manually scan for test cases whose icon indicated a failure occurred.  This wouldn’t be viable for more than a short list of requirements.

What’s needed then is to display a view/query of the linked artifacts, filtered appropriately, and display, if possible, their linked requirements.

For example, show all failed test case runs in Rational Quality Manager (RQM) and their associated requirements.  When displaying all test cases, you can see visually by their associated icon, whether the test case has been run successfully or not.  This isn’t ideal given you aren’t able to filter by the test case status and must instead visually pick out the failed runs.  It does, however, show the linked requirement being validated.

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Alternatively, show a view of test case results and filter by their status.  Below is a list of test case results that are Failed or Blocked and their associated test case.

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Unfortunately, it doesn’t also show the related requirement.  Instead you would need to drill down into the test case from the failed run and see its linked requirements.

Use of the Jazz Reporting Service Report Builder may be an option in limited cases.  First, it’s use for configuration management aware reporting is Technology Preview in 6.0 and only really contains configuration data for RQM.  For DNG, only the default configuration data is included for configuration management enabled DNG projects.  If your requirements configuration management needs are basic, where a single configuration/stream is sufficient, this may be an option.

For example, the following report shows all requirements with failed/blocked test case runs.

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Now you’ll likely have multiple DNG projects.  DNG doesn’t publish project area data to the Lifecycle Query Engine (LQE) using Configurations data source so you can’t choose only those requirements artifacts from a given project, limit scope by that project nor set a condition to query by some DNG project area attribute.  You can, however, choose test artifacts for a given project area (and configuration) so if there’s a 1:1 relationship between DNG and RQM projects, you can produce a report that just shows the requirements from failed test case runs in the desired RQM project belonging to the desired global configuration (this is what is shown in the previous screenshot).

I tried looking at this from the opposite direction, that is, show all failed/blocked test case runs and their associated requirements.  You get the right list of failed runs, but it shows all their associated requirements, not all of which were tested and failed in that run.

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For the other example I gave earlier, show all requirements whose linked development items were resolved, you could go to Rational Team Concert (RTC) and run a lifecycle query such as Plan Items implementing Requirements, but you’d need to visually look for plan items whose status met your criteria as the query isn’t editable and thus you couldn’t add a filter.

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Traceability views for RQM test artifacts

In CLM 5.x, views of test artifacts can be filtered by the presence (or not) of a linked development item.

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The same is true in CLM 6.0 but only for projects that don’t have configuration management enabled.  RQM projects that have configuration management enabled, don’t include that filter option.  This limitation should be addressed in a future release by work item 134672.

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From this view, you would then need to visually scan the Test Development Item column for whichever condition you needed.

RTC has some lifecycle queries, such as Plan Items with no Test Case or Plan Items with failing Tests that could help.

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Here again, Report Builder could help as you could construct a report that shows test cases with or without associated work items.  For example, the report below shows test cases without any work item associated.

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Linking RTC plans to artifact collections

In CLM 5.x, it is possible to link an RTC plan to a DNG requirements collection and/or a RQM test plan.  Use of these grouped artifacts allows for shared scope and constraints across these lifecycle plans and are useful in auto filling gaps in plans or reconciling changes.

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In CLM 6.0, links to collections and test plans from an RTC plan only resolve to the default configuration in the project they reside in.  In other words, you cannot link an RTC plan to a versioned requirements collection or test plan.  This limitation should be addressed in a future release by work item 355613.  The primary limitation that translates to is you are unable to auto generate workitems for requirements in a collection when working with projects that have configuration management enabled.

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Missing that capability then the only work around is to manually create the workitems so that every requirement in the collection is linked to a corresponding work item.

A traceability plan view in RTC that includes a color filter will help identify those plan items without requirements links.

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Such a view will highlight cases where a work item may need to be removed as the scope has changed, e.g. the collection has had requirements removed.

In DNG, view the collection with the Implemented By column included and scan for requirements with no corresponding work item.

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If your requirements set is too large to view manually, export the collection view to a CSV file then open the exported file and filter or sort by the Implemented By column to more easily see those requirements without work items.

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Conclusion

Of the limitations discussed, I find the first one, inability to filter by lifecycle status, will be more problematic for customers though I’ve found it’s usage to be mixed.  I’m also not particularly enamored with the workarounds described because they too are limited and involve some manual steps.  I would be interested in hearing how significant these limitations are in your environment or if you have additional ideas on workarounds for them.

Finding suspect links and requirements to reconcile in CLM 6.0 configuration management enabled projects

The newly released CLM 6.0 has some great configuration management across the lifecycle capabilities.  As described in Enabling configuration management in CLM 6.0 applications there are some considerations to be made before enabling configuration management.  One of these is

Do you rely on suspect links for requirements in RM or for requirement reconciliation in QM?

The reason being is that in this release, automatic detection of suspect links (artifacts that need to be evaluated and possibly modified because a linked artifact has changed) is not working in configuration management enabled DOORS Next Generation (DNG) projects. Further, the requirements reconciliation process in Rational Quality Manager (RQM) to find any changed/deleted requirements impacting associated test cases is also not supported in configuration management enabled RQM projects.  Note that a new mechanism for determining link suspicion is intended for a future release, in the interim though, teams must use a workaround.  I’ll explore some of those in this blog.

Suspect Links Workaround

To determine what requirements have changed and which impacted test cases may need updating, we’ll need to look at a test coverage view of requirements filtered by a some modified date.  It’s likely that you’ll want to know which requirements have changed since the last release baseline.

Let’s assume we are working in the AMR Mobile US global configuration in DNG.  Open the Configuration Context Banner Button (CCBB) and navigate to the global configuration.

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Show the baselines for this global configuration.

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Observe the most recent baseline is AMR Mobile 3.0 US GA.  Drill down into it and see the baseline was created on May 27, 2015, 12:35:23 AM.

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Note at this time, baselines for the each of the contributors to the global configuration must be created first before the baseline for the global configuration can be committed/finalized.  This means there likely be some time disparity between the global configuration baseline and the baselines for contributing local configurations (they could be earlier or later than the global configuration creation date).  For this reason, it’d be more accurate to use the local configuration baseline creation time for the filtering.  While looking at the global configuration baseline, select the row with the desired local configuration and observe its creation time on the right.

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While viewing requirements of interest, likely on a per module by module basis, e.g. AMR System Requirements, open a Test Coverage view and add a Filter by Attribute for Modified on set to be after the baseline date.

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Here we see there have been four requirements altered, two which have no linked test case, but may need one if they are new, and two that have linked test cases, but may need to be updated.

Now you could look at each individual requirement one by one to understand if they are new or modified.  In this example, opening requirement 1830 shows it has been created since the baseline date.

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You could also add the Created On attribute to the view columns displayed.

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This requirement doesn’t have a related test case so now you would evaluate whether one should be created.

Looking at requirement 517, you observe that it was created before the baseline and modified since.  There is a related test case but you need to understand what the change was to better evaluate if it necessitates a change in the test case.

Open the requirement history and get a sense of the changes.

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Should the changes be such that a reevaluation of the test case is warranted, follow the Validated By links to navigate to the test case(s) and check if they need updating.

To track the potential impact of those substantive requirement changes, you could tag the requirements and create a traceability view to look only at those.

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Alternatively, create a Tracked By link from the suspect requirement to a new RTC work item task that would be assigned to the test team to evaluate whether any linked test cases should be updated.

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Now rather than going through each requirement individually, an alternative is to make use of the Compare Configuration capability to compare the current local DNG configuration/stream to the DNG baseline included in the AMR Mobile 3.0 US GA baseline.

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The compare results will show additions, changes and deletions to project properties, folders and artifacts.  With this information, the analyst can make a reasonable determination of how substantive each change was.  Armed with this information, they would need to return to the Test Coverage view(s) and tag the appropriate requirements as suspect and/or create RTC work items to analyze the linked test cases.  Note that previously we were looking at requirements changes on a per module basis (if modules were being used) but the Compare Configuration will look at all changes to all artifacts across the stream, that is, consolidating all change and not giving a module perspective.

Now if you were paying attention to my scenario,  you’ll notice that the last screen shot above, showing the results of the compare, doesn’t line up with the Test Coverage view shown earlier as the system requirements that were shown to have changed since the baseline are not shown in the compare results.  No, this isn’t a bug in the software.  I was using a shared internal sandbox whose configuration was changed in between the time when I started writing this blog and the time I tried to capture the compare results.  Rather than trying recreate the scenario, I left things as they were as I think I still get the concept across (though the anal side of me really has a problem with it all not lining up!).

Requirements Reconciliation Workaround

Requirements reconciliation is a capability in RQM that looks at the requirements linked to a test case or the requirement collection linked to a test plan and determine if there are new, updated or deleted requirements that necessitate changes in the test case(s).  In CLM 6.0, requirements reconciliation is not supported in projects that have configuration management enabled.

While you can query for test cases changed since a certain baseline date, this doesn’t really help determine if there are test cases to be updated due to requirements changes.  It’s not possible from RQM to query on test cases and filter based on attributes of the linked requirements.

Thus, the reconciliation process would need to be driven by DNG such that the tester would need to use the same technique used by the analyst for the suspect links workaround.  That is, the tester would look at a test coverage view of requirements in DNG, filtered to show requirements updates since the baseline date and evaluate if a test case addition, deletion or update was warranted.  This process would be further helped if the analysts used tagging as previously described so that that tester wouldn’t need to sift through all the requirements to find only those with substantive changes.  Use of impact analysis tasks in RTC would as well.

Use of these test coverage views would only identify requirements added or changed since the baseline.  It would not list requirements removed.  So for a comprehensive view of requirements changes that need to be reconciled with test cases, RM stream needs to be compared against the baseline to see any requirements that have been deleted.

Conclusion

While it is unfortunate that this initial release of the global configuration management capability doesn’t include support for suspect links and requirements reconciliation, there are some manual workarounds available, while not ideal, can help mitigate the gap until such time such time a replacement is available.  For some customers, such a manual process may be untenable due to the volume of changes between baselines.  Rather than performing the analysis after the fact, perhaps being more proactive about flagging potential impacts from the beginning of and throughout the release is more appropriate.  As requirements get changed, assess then whether there are test case updates needed by tagging the requirement and/or creating an impact analysis task in RTC.  These can be reviewed/refined at different milestones throughout the release.  Again not ideal but does distribute the analysis burden.

Help! My RTC Database is getting big!

Many customers who have been using RTC for some time are seeing their database size grow, in some cases, to 100s of GBs if not TBs of data.  While growth is to be expected and is of no issue to modern DBMSes, proactive administrators want to understand the growth and how it can be mitigated especially in light of anticipated user growth in their environments.  Naturally, they come to us and ask what can be done.  While at this time we don’t have the solutions many customers are asking for (project copy, move, archive, delete, etc.), that isn’t to say we don’t have approaches that may be of value in some situations.

Working with our own self-hosted RTC environment as well as those of our enterprise customers, we generally find that the largest contributors to database size our build results, work item attachments and versioned content.  How would you know that?  Fortunately, we have a couple of out of the box reports you can run: Latest Repository Metrics and Latest Repository Metrics by Namespace.  Below are some samples showing a subset of the available namespaces and item types.

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Looking at all the namespaces and item types begs the question…what do they all mean?  Yeah, they aren’t all obvious to me either.  Luckily, I have access  to the smart developers who wrote this stuff and can tell me.  If you find one you don’t know, send me a note/comment or post it on the jazz.net forums.  image

Once you find the larger contributors to size, the next questions asked are can they be deleted and who (that is, which project) is producing them.  In keeping with my team’s No Nonsense Tech Talk theme, I’ll be honest, there’s not much we can delete/archive and we certainly can’t do it at a project level, which would be of greater value, nor can we easily tell who produced it all.  It’s not all doom and gloom because there are some things we can do.

As mentioned earlier, we can delete build results, which often are a huge contributor to size growth.  We can delete work items, even attachments from work items.  Versioned content can be deleted, though you don’t usually want to do that, except for security reasons or to remove binaries versioned by mistake.  Then there are plans, streams, workspaces, etc, that can be deleted, but these don’t tend to take up much space.

So what happens when something is deleted? Well, in some cases, it’s not really removed from the database, only reference to it is removed or made less accessible.  For example, work item attachments don’t really go away when removed from a work item.  Try this.  Add an attachment to a work item then save the work item.  Hover over the attachment link and copy it.  Now remove the attachment from the work item then save the work item.  In the browser, paste the copied attachment URL and it will be found.  Similarly, if you delete a work item that has attachments, the attachment links still remain valid.  However, if you delete (not remove) a work item from the Eclipse client, the work item is actually deleted.

If you find that you’ve removed but not deleted an attachment, it is possible to go back and have it truly deleted.  To do so, using the Eclipse client, paste the URL to the attachment (which should be visible in a discussion comment from when it was first attached) somewhere into the work item (into a comment or the description), right click over that link and select “add to favorites”. Once it is in the favorites, you can drag it from Favorites and drop onto the Attachments section, which re-attaches it to the work item, at which point you can then delete it in the normal way.

Now some things like build results and versioned content once deleted can truly be deleted from the database.

At the repository level there are two key background tasks that are used to mark content as deletable then later deletes it.

  • an “Item Cleanup Task” background task at repository level marks newly orphaned content blobs as needing deletion (runs every 17 mins by default)
  • a “Deleted Items Scrub Task” background task at repository level deletes any content blobs that have been orphaned for more than ~2 hours (runs every 24 hours by default)

Once these both run, any content blobs that were deleted more than 2 hours ago should be fully deleted from the database.

However, DBMSes (particularly those in production) don’t generally release storage allocated for their tables immediately.  A compaction task usually needs to be run to reclaim the disk space.  The DBMS should have tools to indicate in advance how much space can be reclaimed by compaction.  Typical utilities to do this are shown below.  Details for using them should be left to a qualified DBA.

  • Oracle – ALTER TABLE … SHRINK SPACE
  • DB2 – REORG
  • SQL Server – SHRINKDATABASE

My teammate Takehiko Amano has done a very nice job of showing how deleting versioned content and later running DB2 commands reduces database size.  See his article Reducing the size of the Rational Team Concert repository database.

We find the build results often take up a good amount of the RTC database size.  These results often include all the log files from compilations, tests and other activities performed during the build.  Some times they will contain downloadable outputs, e.g. application archives and executables.  What happens is these results are often kept around and never deleted.  In some cases, especially for release milestones, they should be, but all those personal or interim continuous builds don’t need to be kept.  Build results can be deleted and will result in their database content being orphaned and subsequently deleted per the aforementioned process.  Rather than manually deleting results, consider setting up a pruning policy to automatically delete old results.  For those results you want to keep around and not be pruned, just mark them as not deletable.

In cases you know your build results are taking up a lot of space, the natural follow on question is which builds and who owns them.  Our development team recently had cause to address that question which resulted in a very useful script written by Nick Edgar, the RTC Build Component Lead.

Nick created a Groovy script that collects into a CSV file the pruning policy settings and footprint data for each build in all projects across a repository.

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He further creates an interactive HTML report that parses the CSV file for display in a more visual form.  image

With this information you can find out which builds from which projects are taking up the most space and whether they have a pruning policy in place.  Armed with this information, an administrator could go to the appropriate release teams and take action.  Imagine running it weekly and posting to a dashboard or emailing it weekly to release teams.  The Groovy script to collect the data and index.html to render the report are attached to task work item 330478.

For gathering the CSV data you’ll need to 1) install Groovy, 2) install a build system toolkit that’s compatible (ideally at same version) as RTC server, 3) set environment variables (see top of Groovy script), and 4) run the script with: groovy -cp “$BUILD_TOOLKIT/*” <groovy file name> <any arguments needed by script>.

For the chart, just put the chart index.html file and CSV in the same directory and open the HTML file. Some browsers will require these to be served up by a web server to allow the HTML file to read the CSV file. For my testing, I used Python’s simple server support for this: python -m SimpleHTTPServer.

Given I am referencing code samples, I’ll keep our lawyers happy by stating that any code referenced is derived from examples on Jazz.net as well as the RTC SDK. The usage of such code is governed by this license. Please also remember, as stated in the disclaimer, that this code comes with the usual lack of promise or guarantee. Enjoy!

Being able to monitor the size and growth of your data, getting granular and actionable information about it and ultimately, being able to do something positive about that growth, is a key concern for IBM Rational and something we are exploring as part of our Platinum Initiative.  I welcome your input in this area.  Perhaps we can interact at IBM InterConnect 2015.

Tracking the status of your builds and getting their results

Our team was asked recently how we go about getting access to the CLM software downloads.  The primary answers were of course, the jazz.net product downloads while others use a ready made virtual or cloud image.  I tend to support customers who are at different version levels.  I also tend to want to run different versions of CLM natively.  Some times I get the download from jazz.net, which is really the official channel (not to mention IBM Passport Advantage site).  However, the typical download will involve use of IBM Installation Manager, which works great, but when you want to install multiple versions, you end up with multiple similarly named program groups.  I choose a method which allows me to install from a zip archive.

The point of this blog entry is not to advocate my method of getting the download.  In fact I wouldn’t recommend it for any production deployment.  What I want to do is use my method to illustrate some cool features of RTC that you can apply in your environment, not for getting our downloads but to allow others in your organization access to those you produce and to monitor progress along the way.

As I said, I like to use the zip archive installs.  This works for me since I don’t need an enterprise install and can typically get away with Derby and Tomcat.  The jazz.net downloads have zip installs for the RTC client, Jazz Build Engine and a combined JTS/CCM but not a full CLM install (JTS, CCM, RQM, RDNG).  If I want the zip install of CLM, I have to go elsewhere.

So let’s say I want the GA version of CLM 5.0 along with the RTC Eclipse client and Jazz Build Engine.  I will end up using combinations of the following capabilities:

  • Build Queue
  • Build Result
  • Track Build Item

Note once again, this scenario is for illustrative purposes only to highlight those capabilities and not promoting it as how you should go about getting your Jazz downloads.

Firstly, I know that the Jazz CLM development team has a Jazz build definition to produce one of its releases.  Using the Team Concert Web UI, I can browse the Jazz Collaborative ALM project area to see the list of build definitions for the project and in particular, the Jazz Collaborative ALM Development team area.

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I select the build definition for the build producing the bits for the release I am interested, in this case, calm.30-50(aka calm.jcb) for the version 5.0 release I want.

Note the list of most recent build results for the calm.30-50(aka calm.jcb) build.  See the Tags column.  RTC allows build results to be tagged.  The development team uses  tags for different purposes (e.g. passing a certain test stage) but one is to denote which build result is declared final for a particular milestone or release.  Here I can see that build result CALM-I20140509-1731 completed successfully, is green, is tagged 5.0-ga and thus produced the final bits for the 5.0 generally available (GA) release of CLM. 

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I select the result link to navigate to the CALM-I20140509-1731 build result.  Of interest to me here are the Downloads and External Links tabs. 

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The items on the Downloads tab represent artifacts produced by the build.  These can be published to the build result using the artifactLinkPublisher Ant task, available via the Jazz Build Toolkit.  In this scenario, links to the various platform CLM Installation Manager installers and full CLM zip archive install are published with the build result.  I want a 64-bit Linux install so I will select the Workbench-for-CLM-Linux64-Redhat_5.0.0.0-CALM-I20140509-1731.zip link.

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Once downloaded, I can expand the archive, navigate to the server folder and start the Jazz Team Server and go through the setup and import the appropriate licenses.

This only gets me the CLM installation.  I also want to get the corresponding RTC Eclipse Client and Jazz Build Engine.  Since this is a GA release, I can get these from the typical jazz.net downloads page, but to further my illustration, I will use the External Links tab.

On this tab, I see the list of contributing builds from other projects.  I am interested in the contributing build from the Team Concert project area, that is, RTC – rtc.jcb RTC-I20140509-1417.  Note these links can be produced using the linkPublisher Ant task.

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Navigating to the result of the contributing RTC build, I see the build is tagged for 5.0 and has it’s own Downloads and External Links tabs. 

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For my purposes, I am interested only in the Downloads tab so I can find the download link for the zip install version of the Build System Toolkit and Eclipse Client.

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Once downloaded, I can expand and run. 

One last feature, which is very useful if I am trying to get access to the milestone or release bits early or just to be aware of how we are progressing at declaring its final build, is the Track Build Item work item type. 

The development team uses these work items to collaborate across the teams and disciplines on the builds being produced, their contributors, schedule, test status, blockers found and finally, which will be designated as final/green for the milestone/release.  For example, the Track Build Item 324131 was used to track the CLM 5.0.1 RC1 milestone release. 

The description section tells me a lot of useful information about the release and its primary build and contributors. 

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Looking through the discussion comments, I see a great deal of collaboration leading to green declaration of the final build.

A build is ready for test:

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A problem occurred with the build

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A build may be ready to be declared final but the team needs to coordinate on some approvals.

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The team is declaring the latest build as green and ready to move on to the next release.

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With all this useful information available, should I want to stay current on the release and pick and choose which builds to get early access to, I would subscribe to the work item and monitor the comments.

In conclusion then, by browsing the build queues to find a build result that has been tagged then using the result’s Downloads and External Links, coupled with the Track Build Item work item, development teams have a powerful way to monitor and collaborate on builds throughout the release cycle and obtain their results.

Automating changes to a build workspace configuration

Here’s the scenario.  A build engineer gets a request to establish a build workspace and corresponding build workspace.  He creates the build workspace, gets the desired components added to it, sets the flow targets then changes ownership of the workspace to the build user’s functional ID.  After that, he creates the build definition and associates it with the newly created workspace.  All is good and developers can begin to use the new build definition.  After a time, a request comes in to change the configuration of the build workspace, specifically the components to use.  Since the build workspace is owned by the build user, any changes to it must be made by that user.  Many organizations eschew the use of functional IDs or at least minimize who knows their credentials and are concerned about extra maintenance brought on by password expiration rules.  What to do?

This specific scenario came up recently with a customer of mine.  In particular, their build workspaces have three flow targets.  The current/default is the stream with the application source and it is scoped to include a subset of the components in the stream.  The other two streams are build script and configuration related.  At times, the release team needs to change the components included in the scope of the application source stream.  They do so currently by logging in as the build user, something they detest doing.

What they much prefer is support for team ownership of repository workspaces but that isn’t currently possible (though requested via 271760).  We instead proposed a solution that put the workspace configuration change in the build script which is already performed as the build user and owner of the workspace.

As of 4.0.1, the SCM CLI includes the capability to add/change workspace flow targets.  It was later refactored in 4.0.6 to the current verb-oriented form.

${scmExe} –non-interactive set flowtarget -r ${repositoryAddress} -u ${userId} -P ${password} ${team.scm.workspaceUUID} ${targetStreamUUID} –flow-components ${componentsToLoad}

Where:

  • scmExe – path to scm CLI executable
  • repositoryAddress – URL of CCM server
  • userId – build user ID
  • password – password of build user
  • team.scm.workspaceUUID – build repository workspace UUID
  • targetStreamUUID – stream flow target to set component scope
  • componentsToLoad – space delimited list of components

Unfortunately the SCM CLI does not understand the password file format used by the Ant tasks. You either need to give it as plain text using –P shown above or login outside the build system with the option to remain logged in (on each build machine).

A simple way to get the UUID of a workspace or stream is to open it up in the Eclipse editor and select Copy URL workspace editor menu in the view header or browse to it in the Web UI to get the URL.  The end portion of the URL is the UUID.  For example, the UUID for the repository workspace URL shown below is _GVqXYLRpEeOdavKqgVc36Q

https://clm.jkebanking.net:9443/ccm/resource/itemOid/com.ibm.team.scm.Workspace/_GVqXYLRpEeOdavKqgVc36Q

For components with spaces in their name, care must be taken to offset them by appropriate quotes.  For my tests, single quotes worked on Linux and double on Windows.

The command will set the scope of the specified flow target (e.g. application development stream) for the specified workspace (e.g. build workspace) to include only those components in the specified list.  The current configuration of the component(s) in the target stream is used.

Note if multiple flow targets exist for the workspace and a component listed is included in multiple flow targets, then scoped flows need to be used to avoid conflicts.  See How should my source code be loaded from Jazz SCM?

Let’s take a look at an example.  Below, the build.brm.continuous repository workspace, owned by the build user, has six components and three flow targets in its configuration. Banking Logic, Database, Java UI and Prerequisites are from the BRM StreamBuild comes from Build Scripts and Build Config comes from the stream of the same name.

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The BRM Stream is scoped to only include only a subset of the components.

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Assume that we wanted to add the Database component to the scope.  Using SCM CLI command similar to that shown in the screenshot below, the scope can be changed to add it in.

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This results in the flow target scope being changed.

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Now to add this to the build script so it can be automated.  Observe in the editor screenshot below that the command has been added to an exec statement in an Ant build script.  image

The targetStreamUUID and componentsToLoad values need to be passed to the build script.  Add these as properties of the build definitions.  For example:

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When the build is requested, the componentsToLoad value can be changed.  In our original example, the Database component can be added in by editing the componentsToLoad build property at the time of the build request.

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Should you be concerned that adding the ‘set flowtarget’ command to the build script will add unnecessary overhead, albeit very minimal, to every build execution even when component list isn’t changed, you can create a build script and definition that only performs the ‘set flowtarget’ command and run it when needed.

The example shown was for changing the flow target component scope.  The technique used can be applied for other build workspace manipulations needed and supported by the SCM CLI.

Thanks to Nick Edgar, RTC Build component lead, for making me aware of the ‘set flowtarget’ command and suggesting its application to the problem described.

Do I need that other Jazz server?

I have been working with a team trying to determine if they need a second Change and Configuration Management (CCM) server to support their Rational Team Concert (RTC) deployment.  The performance of the existing CCM isn’t bad.  While the CPU utilization is low, the memory consumption is peaking a little high so some monitoring would be helpful to understand the usage patterns more.

The main motivation for considering a second CCM server is the expected growth to occur this year.  They know their current average and peak license usage, current count of licensed/registered users and how many new registered users they expect to add.  They also know the recommended range of users for a CCM based on IBM’s testing and analysis as shown in CLM Sizing Strategy.

The slight disconnect is that the user ranges we recommend are based on concurrent users not how many registered users there are or how many on average have a license in use (checked out).  Unfortunately, as yet, we don’t have a good way to measure the actual number of concurrent users.

So what do we do?  I see two ways to make this estimate.

First, the CLM Sizing Strategy states:

The number of concurrent users can often be estimated from the number of registered users. In an organization located on one continent or spanning just a few time zones, the number of concurrent users can be estimated to be between 20% and 25% of the total number of registered users. In an organization which spans the globe where registered users work in many different time zones, the number of concurrent users can be estimated to be between 10% and 15% of the total number of registered users.

What you can then do is take a percentage of the current plus expected registered users, e.g. 20-25% above when spanning few time zones, and compare that to the RTC ranges based on workload.  That will help you determine if another CCM (or more) is needed.  The percentage you apply may be different based on your experience.  In fact, in my customer case, a large number of users were registered and licensed in anticipation of them being migrated to RTC.  Applying that percentage today would give them a higher number of estimated concurrent users than was being experienced.

Another method would be to look at the average/peak number of licenses in use for RTC vs those that are licensed.  From this ratio, assuming linear growth, you can project how many licenses would be in use in the future.  Again, you would then compare that to the recommended ranges.  This method should be a little more accurate than the anecdotal, gut feel percentage of registered users in the first method.  We at least know that the number of concurrent users isn’t any more than the number of licenses in use.  Based on what you know of the users  to be added, linear growth may not be quite right and you may need to adjust the projection (e.g. the users being added are expected to be heavier users of RTC).

This latter method is what we used.  It seemed more accurate plus, as mentioned, the number of licensed users included many who weren’t onboarded yet.

Now the CLM Sizing Strategy is based on the workloads we generated on a given set of hardware.  Your workload and hardware may be such that you can handle more users (or maybe less).  I’ve had customers report that they were able to support more users than our recommended ranges.

This then shows that all the numbers and percentages need to be balanced against real experience with the environment, not only the license usage data but other things like CPU utilization, JVM size, database size, etc.  Monitor your current environment and perform trend analysis to assess if the server is nearing capacity.  Look at Monitoring: Where to Start? and Monitoring and Troubleshooting Guide for IBM Rational Collaborative Lifecycle Management (CLM).

Note that using the built in Jazz server license usage reports or the Rational License Key Server Administration and Reporting Tool, one can get an idea of license usage trends. For example, the reporting tool will show license usage by product. The recent release now includes support for authorized licenses.  Support for showing reports by role is being considered for a future release.

peakReport.jpg

As mentioned in the beginning, in this customer’s case, they weren’t experiencing any performance issues with the server.  Their CPU utilization looked fine.  There were memory usage peaks hitting 80% – 90% of the total heap so I suggested monitoring this and increase the heap as needed.

In the end, though the straight numbers and percentages suggested additional servers would be needed, this customer didn’t have good monitoring data, wasn’t experiencing performance issues and seemed to have capacity to support more users.  My recommendation was to hold off on a topology decision, put some monitoring in place, adjust the server configuration as needed/able (memory, JVM, CPU (number, speed)), assess performance/capacity of server vs expected users yet to add, if capacity/performance can’t be adjusted by manipulating the server configuration and it looks like the growth will be more than the server can handle, then add the additional CCM.

We didn’t want to take the addition of the second CCM lightly because doing so would incur another set of issues, that being the behavioral differences between a single CCM environment and a multiple CCM environment that I’ve blogged about previously and documented on the deployment wiki.  See Planning for Multiple Jazz Application Server Instances.

When assessing whether a multiple CCM topology was needed, one consideration we made was whether to mitigate some of the primary behavioral differences of concern to the customer by making one CCM be the hub for all work items and planning and the other CCMs for source control and build only.  There are tradeoffs for sure but that’s another blog discussion for another time.

Considerations when deploying multiple instances of a Jazz application

As you have seen from previous posts I’ve made on the impact of deploying multiple QM or CCM applications in your CLM environment, which were then turned into an Innovate 2014 presentation, I’ve been very interested in getting the word out on the subject.  We tend to focus on getting a good infrastructure in place, as we should, but we don’t always factor in what might be different in the usage of the Jazz applications when we have multiples of them.  I’ve been on a crusade of sorts to gather what is known in this area, consulting other SMEs like my colleague (and co-author/presenter) Ralph Schoon, architects in Rational development for the different Jazz applications and several customers.

My goal is that there would be no surprises when multiple instances of an application exist and that the behavior differences are factored in up front during usage model design.  Where differences exist and where appropriate, I’m pursuing product changes to remove them.

Following a good discussion during our session at Innovate, incorporating feedback received, Ralph and I have converted our presentation to a page on the Jazz.net deployment wiki (see Planning for multiple Jazz application server instances).  Have a look and if you have any feedback, post a comment here or better yet, post it on the wiki (see How can customers make comments on the wiki pages?).

I did a simple straw poll at Innovate to get a sense of the ranges for the number of instances of a particular Jazz application in different customer environments.  Of the 30-40 attendees, most only had one JTS but there were 3-5 that had 2-3 JTS. Several had 3-5 CCMs. Only one had multiple QMs (3). None were planning multiple RMs yet.  I’d be very interested in getting other samplings.  If you have multiple instances of any one of the Jazz applications (registered to the same JTS) or multiple JTS instances, I’d like to hear how many and understand a little more about the environment.  You can post a reply to this blog or contact me directly (tfeeney@us.ibm.com).