We are standing up a CI pipeline using Jenkins and we are using SonarQube to run static analysis. We have set up quality gates and now we are failing builds, when the gates are not met. When we fail a build the code is still put into sonarQube. So if a developer tries to promote twice the second build will 'pass'.
Example:
Gate is no new critical issues.
The Developer checks in code with 1 new critical issue.
The build fails on static analysis (SonarQube has the rule flagged and a blocker).
The Developer checks in code again (no code changes).
the static analysis's passes because the critical issue is not 'new'.
Is there a way to revert back to the previous version on a failure, or better yet to run the analysis against the most current non-failing run?
Notes: Version - Sonarqube 5.1.2
You've asked how to keep committed code from being reflected in the SonarQube platform.
I don't recommend trying to suppress the analysis of committed code because then your quality measures don't reflect the state of your code base. Imagine that someone is making a decision about whether HEAD is releasable based on what they see in the SonarQube UI. If you're keeping "bad" code from showing up, then... what's the point of analyzing at all? Just use a photo editor to construct the "perfect" dashboard, and serve that gif whenever someone hits http://sonarqube.myco.com:9000.
Okay, that may be an extreme reaction, but you get my point. The point of SonarQube analysis is to show you what's right and wrong with your code. Having a commit show up in the SonarQube UI should not be an honor you "earn" by committing "worthy" code. It should be the baseline expectation. Like following the team's coding conventions and using an SCM.
But this rant doesn't address your problem, which is the fact that your current quality gate is based on last_analysis. On that time scale "new critical issues" is an ephemeral measure, and you're loosing the ability to detect new critical issues because they're "new" one minute and "old" the next. For that reason, I advise you to change your time scale. Instead of looking at "new" versus last analysis, compare to last version, last month (over 30 days), or last year (over 365 days). Then you'll always be able to tell what's "new" versus the accepted baseline.
Related
We are using Sonarqube 8.0 and TFS together with gated checkins. So when I check in a version of the code that makes the quality gate red, we break the build and the checkin gets rejected. But if I check in the exact same code again, sonarqube only analyses the new code and therefore the gate is green again, as there is no difference to the last analysis, which was red. So we where thinking to make the "New Code Period" the last green analysis, but this does not seem possible. I can only choose "Previous" "Periods of days" and "Specific". To me this does not make all too much sense, as I only want to see what is changing to my current checkin. Maybe we have to analyse the master branch and only set the analysis to check versus a specific version of the master branch, but that seems like a lot of work to always select a new version when we merge to master.
I know the analysis works better with pull requests to master from private projects, but we do not have git here, so this is no option right now.
Is there a good way to keep our dev branches clean with sonarqube? Right now it feels a little useless in combination with TFS and a single DEV branch…
We are using SonarQube to analyse the code that we checkin to TFS. Every time a developer performs a checkin, the new/changed code is being analysed. This mechanism did well for us, until last friday. All of a sudden SonarQube told as we had thousands of code smells/bugs/vulnerabilities in 1 of our 34 projects. Trying to understand where this came from, I saw a quirk in the SonarQube activities:
Performing an analysis, SonarQube says 'Quality Profile: Stop using '[x] way'' for 3 quality profiles
Performing the next analysis, SonarQube says 'Quality Profile: Use '[x] way''
This change in using profiles is also visible in the activity graph:
We made no changes to the quality profiles between these analysis. How SonarQube is being triggered is also not changed in this period. Also, no changes/updates are being made to any of the involving systems between these analysis.
Right now I'm completely in the dark about what have could caused the change in (not) using some quality profiles. My question therefore is:
Has anybody encountered this before or can anybody shine a light on where to look for where this came from?
The most aggressive build retention policy one can set for pull request builds is described in "Clean up pull request builds"
a policy that keeps a minimum of 0 builds
Still, it means that successful PR builds (with artifacts no one will ever need) will be deleted only after the next automatic retention cleanup - usually the next day, but in reality it results in nearly two days worth of no longer needed builds.
In our particular case it seems to be desirable to find a way to clean successful PR builds ASAP due to their frequency and artifact's sheer size that may periodically strain our not yet fully organized infrastructure dedicated to PR handling (it will be significantly improved, but not as soon as we'd like to, and those successful PR builds would still remain no less of a dead weight).
And as far as I see the only way to do it would be to delete builds manually.
While it is not too difficult to implement, I'd still like to check whether there is a simpler standard way to delete successful PR builds automatically.
P.S.: There is one particularity in our heavily customized build process - we have multiple dependent artifacts. Like create A, use it to build B, create C to test B... So trying not to Publish artifacts on overall successful build with custom condition like it is suggested below is not exactly feasible.
Let's look at the problem from a different perspective: The problem isn't that builds are retained, the problem is that your PR builds are publishing artifacts.
You can make the Publish Artifacts steps conditional so that they don't run during PRs. Something like and(succeeded(), ne(variables['Build.Reason'], 'PullRequest')) will make the task only run if it's not a PR.
We just started using Visual Studio Release Management for one of our projects, and we're already having some problems with how we are doing things.
For now, we've created a single release stage, which is responsible for deploying our build artifacts to a dedicated virtual machine for testing. We intend to use this machine to run our integration tests later on.
Right now, we have a gated checkin build process: each checkin fires all the unit tests and we configured the release trigger to happen on this build also. At first, it seemed plausible that, after each checkin, the project was deployed and the integration tests were executed. We noticed that all released builds were polluting the console on Release Management, and that all builds were being marked as "Retain Indefinitely" and our drop folder location was growing fast (after seeing that, it makes sense that the tool automatically does this, since one could promote any build to another stage and the artifacts need to be persisted).
The question then is: what are we doing wrong? I've been thinking about this and it really does not make any sense to "release" every checkin. We should probably be starting this release process when a sprint ends, a point that can be considered a "release candidate".
If we do that though, how and when would we run our automated integration tests? I mean, a deployment process is required for running those in our case, and if we try to use other means to achieve that (like the LabTemplate build process) we will end up duplicating deployment code.
What is the best approach here?
It's tough to say without being inside your organization and looking at how you do things, but I'll take a stab.
First, I generally avoid gated checkin builds unless there's a frequent problem with broken builds. If broken builds aren't a pain point, don't use gated checkin. Why? Simple: If your build/test process takes 10 minutes to run, that's 10 minutes that I have to wait to know whether I can keep working, or if I'm going to get my changes kicked back out at me. It discourages small, frequent checkins and encourages giant, contextless checkins.
It's also 10 minutes that Developer B has to wait to grab Developer A's latest changes. If Developer B needs that checkin to keep working, that's wasted time. Trust your CI process to catch a broken build and your developers to take responsibility and fix them on the rare occasions when they occur.
It's more appropriate (depending on your branching strategy) to do a gated checkin against your trunk, and then CI builds against your dev/feature branches. Of course, that opens up the whole "how do I build once/deploy many when I have multiple branches?" can of worms. :)
If your integration tests are slow and require a deployment to succeed, they're probably not good candidates to run as part of CI. Have a CI/gated checkin build that just:
Builds
Runs fast unit tests
Runs high-priority, non-deployment-based integration tests
Then, have a second build (either scheduled, or rolling) that actually deploys and runs the whole test suite. You can schedule it according to your tastes -- I usually go with one at noon (or whatever passes for "lunch break" among the team), and one at midnight. That way you get a tested build from the morning's work, and one from the afternoon's work.
Using the Release Default Template, you can target your scheduled builds to just go as far as your "dev" (/test/integration/whatever you call it) stage. When you're ready to actually release a build, you can kick off a new release using that specific build that targets Production and let it go through all your stages normally.
Don't get tripped up on the 'Release' word. In MS Release Management (RM), creating a Release does not necessarily mean you will have this code delivered to your customers / not even that it has the quality to move out of dev. It only means you are putting a version of the code on your Release Path. This version/release can stop right in the first stage and that is ok.
Let's say you have a Release Path consisting of Dev, QA, Prod. In the course of a month, you may end up releasing 100 times in Dev, but only 5 times in QA and once in Prod.
You should drive to get each check-in deployed and integration tested. If tests takes a long time, only do the minimal during (gated or not) check-in (for example, unit tests + deployment), and the rest in your second stage of Release Path (which should be automatically triggered after first stage completes). It does not matter if second stage takes a long time. As a dev, check-in, once build completes successfully (and first stage), expect the rest to go smoothly and continue on your next task. (Note that only result of the first stage impacts your TFS build).
Most of the time, deployment and rest will run fine and so there won't be any impact to dev. Every now and then, you will have a failure in first stage, now the dev will interrupt his new work and get a resolution asap.
As for the issue that every build is kept indefinitely, for the time being, that is a side effect of RM. Current customers need to do the clean up manually (or script it). In the coming releases, a new retention policy for releases/builds will be put in place to improve this. This has not been worked on yet, but the intention would be to, for example, instruct RM to keep all releases that went to Prod, keep only the last 5 that went to QA and keep only the last 2 that went to Dev.
This is not a simple question, so also the answer must be articulated.
First of all, you will never keep all of your builds; the older a build, the less interesting to anyone; a build that doesn't get deployed in production is overtaken by builds that reaches that stage.
A team must agree on the criteria that makes a build interesting to keep around and how long to keep it. Define a policy for builds shipped to production or customers: how long do you support them? Until the next release, until the following one, for five years? Potentially shippable builds, still not in your customers' hands, are superseded by newer, so you can use a numeric or a temporal criteria (TFS implements only the first, as the second is more error-prone). Often you have more than one shippable build, when you want a safety net option and being able select from a pool which deliver (the one with more manageable bugs).
The TFS "Retain Indefinitely" should be used when you cannot automate the previous criteria, so you switch to a manually implemented policy. Indefinitely is not forever, means for an unknown time interval.
Although this question specifically involves Gradle and Bamboo, it really is a question about any build system (Ant/Maven/Gradle/etc.) and any CI tool (Bamboo/Jenkins/Hudson/etc.).
I was always under the impression that the purpose of a CI build is to:
Check out code from VCS
Run a buildscript (Gradle, etc.)
Deploy a binary (WAR, etc.) to an environment
Hence, all the guts and heavy-lifting (running automated tests, code analysis, test coverage, compiling, Javadocs, packaging, etc.) was all to be done from inside the buildscript.
But Bamboo seems to allow you to break this heavy-lifting out of the buildscript and into Bamboo itself. In Bamboo, you can add build stages and decompose the stages into tasks. Each task is something just as atomic/fundamental as an Ant task.
So it got me thinking: how much should one empower the CI tool? What typical buildscript functionality should be transferred over to Bambooo/CI? For instance, should I be compiling from a Gradle task, or from a Bamboo task? Same goes for all tasks/stages.
For some reason, I view this as the same problem as to whether or not to use stored procedures or put the data processing all at the application layer. What are the pros/cons of each approach?
TL;DR at the bottom
My experience is with Jenkins, so examples will relate to that.
One thing with any build system (be it CI server or a buildscript), is that it should be stable, simple and self-contained so that an untrained receptionist (with printed instructions and proper credentials) could do it.
Ease of use and re-use
Based on the above, one would think that a buildscript wins. Not always. As with the receptionist example, it's about easy of use and easy of reproducibility.
If a buildscript has interdependent build targets that only work in correct order, dependence on pre-supplied property files that have to be adjusted for the correct branch ahead of build, reliance on environment variables that no-one remembers who created in the first place, and a supply of SCM revision numbers that have to be obtained by looking at the log of the commits for the last month... This is in no way better than a Jenkins job that can be triggered with a single button.
Likewise, a Jenkins workflow could be reliant on multiple dependant jobs, each being manually pre-configured before the build, and need artifacts uploaded from one place to another... which no receptionist will do.
So, at this point, a self-contained good buildscript that only requires ant build command to do everything from beginning to end, is just as good as a Jenkins job that only required build now... button to be pressed.
Self-contained
It is easy to think that since Jenkins will (at some point) end up calling at least a portion of a buildscript (say ant compile), that Jenkins is "compartmentalizing" the buildscript into multiple steps, thus breaking away from being self-contained.
However, instead you should zoom out by one level, and treat the whole Jenkins job configuration as a single XML file (which, by the way, can be stored and versioned through an SCM just like the buildscript)
So, at this point, it doesn't matter if the whole build logic is inside a single buildfile, or a single XML job configuration file. Both can be self-contained when done right.
The devil you know
In majority of cases, it comes down to what you know.
Some people find it easier to use Jenkins UI to visually arrange their build workflow, reporting, emailing, and archiving (and for anything that doesn't fit as wanted, find a plugin). For them, figuring out a build script language is more time consuming then simply trying it in UI.
Others prefer to know exactly what every single line of their build script does, and don't like giving control to some piece of foreign code obfuscated by UI.
Both points have merits from all sides Quality-Time-Budget triangle
The presentation
So far, things have been more or less balanced. However:
My Jenkins will email a detailed HTML report with a link to a job page and send it straight up to the (non tech-savvy) CEO. He can look at the list of latest builds, along with SCM changes for each build, linking him to JIRA issues fixed for each build (all hyperlinks to relevant places). He can select the build with the set of changes that he wants, and click "install iOS package" right off his iPad that he just used to view all this information. Meanwhile I can go to the same job page, and review the build logs and artifacts of each log, check the build time trends and compare the parameters that were used between the failing and succeeding jobs (and I didn't have to write any echos to display that, it's just all there, cause Jenkins does that for you)
With a buildscript, even if you piped the output to a file, would you send that to your (non tech-savvy) CEO? Unlikely. But wait, you know this devil very well. A few quick changes and hacks, couple Red Bulls... and months of thankless work (mostly after-hours) later... you've created a buildscript that will create and start a webserver, prepare HTML reports, collect statistics and history, email all the relevant people, and publish everything on a webpage, just like Jenkins did. (Ohh, if people could only see all the magic you did escaping and sanitizing all that HTML content in a buildscript). But wait... this only works for a single project.
So, a full case of Red Bulls later, you've managed to make it general enough to build any project, and you've created...
Another Jenkins/Bamboo/CI-server
Congratulations. Come up with a name, market it, and make some cash of it, cause this ultimate buildscript just became another CI solution a la Jenkins.
TL;DR:
Provided the CI-server can be configured simply and intuitively so that a receptionist could run the build, and provided the configuration can be self-contained (through whatever storage method the CI-server uses) and versioned in SCM, it all comes down to the Quality-Time-Budget triangle.
If you have little time and budget to learn the CI server, you can still greatly increase the quality (at least of the presentation) by embracing the CI-server's way of organizing stuff.
If you have unlimited time and budget, by all means, make your own Jenkins with the buildscript.
But considering the "unlimited" part is rather unrealistic, I would embrace the CI-server as much as possible. Yes, it's a change. However a little time invested in learning the CI-server and how it compartmentalizes or breaks into tasks the different parts of the build flow, this time spent can go a long way to increasing the quality.
Likewise, if you have no time and/or budget, figuring out the quirks of all the plugins/tasks/etc and how it all comes together will only bring your overall quality down, or even drag the time/budget down with it. In such cases, use the CI-server for bare minimum needed to trigger your existing buildscripts. However, in some cases, the "bare minimum" is no better than not using the CI-server in the first place. And when you are at this place... ask yourself:
Why do you want a CI-server in the first place?
Personally (and with today's tools), I'd take a pragmatic approach. I'd do as much as feasible on the build side (clearly better from an automation perspective), and the rest (e.g. distribution of work across machines) on the CI server. Anything that a developer might want to do on his own machine should definitely be automated on the build level. As to the concrete steps you gave, I'd generally check out code from the CI server, and deploy binaries from the build. I'd try to make every CI job look the same, invoking the build tool in the same way (e.g. gradlew ciBuild).
In Bamboo, you can add build stages and decompose the stages into tasks. Each task is something just as atomic/fundamental as an Ant task.
To some extent, this overlap in functionality is natural, as neither build tool nor CI server can assume existence of the other, and both want to provide as complete a solution as possible.
For some reason, I view this as the same problem as to whether or not to use stored procedures or put the data processing all at the application layer.
It's not an unfair comparison, and hence opinions will be as diverse, contextual, and nuanced.
Disclaimer: I'm a Gradle(ware) developer.