I'm looking for a good way to manage deployment to a test environment of several branches of the same codebase.
My setup includes a Main branch and several Dev branches:
Main
Dev1 (feature set 1)
Dev2 (feature set 2)
etc...
These are all part of a continuous integration process where they get deployed daily for testing.
At the moment there is a "Testing" configuration, with corresponding Web.config transformation and publish profile, that control things like connection strings (Web.config) and location to deploy the application to (MSDeploy configuration in the publish profile).
It all worked fine until merging started happening. Once we start merging code, the different Web.config transformations and publish profiles inevitably get mixed up, and Visual Studio happily merges everything without finding conflicts, resulting in situations like the Main branch being deployed to the Dev1 location, or the Dev2 application getting configured with Main's connection string.
I can think of one solution, which is creating a solution configuration for each branch, and the corresponding Web.config transformations and publish profiles. This would definitely do the job of keeping everything separate and safe from merging problems, but it creates a whole lot of new configuration files all over the place. And on top of that it makes the task of creating or deleting a branch much more complicated.
Is there another way of doing it?
You should look at Release Management for Visual Studio 2013. You can configure a release pipeline with different variables at each environment that you are deploying to.
You would then only have two transformations. One, the default, for localhost development. And a second for use on the build server that contains the RM replaceable variables.
http://nakedalm.com/building-release-pipeline-release-management-visual-studio-2013/
Related
We are using Visual Studio Team Services.
We have a Prod-Branch which is builded by our Prod-Build-Definition and deployed by our Prod-Release-Definition to our Test / Integration and Production Environments.
With each Prod-Release deployed to the customer, we create a Prod-Rel-Version-x.x.x Branch from the Prod-Branch (in Case we need that for a Hotfix).
During the Sprint we are developping on a Dev-Branch which is builded by our Dev-Build-Definition and deployed by our Dev-Release-Definition to our DEV Environment for Developer Tests.
After the Sprint (or from time to time) the Dev-Branch is merged to the Main-Branch and then to the Prod-Branch. From there it is deployed to the different Stages for Testing by the customer.
When there is a Hotfix-Case, we fix the bug on the Prod-Rel-Version-x.x.x Branch and would like to reuse our existing Prod-Build-Definition to build this Hotfix-Version and deploy to the different stages by the existing Prod-Release-Definition for testing and going live with this version.
How can we reuse our Prod-Build-Definition with this different Branch (Prod-Rel-Version-x.x.x Branch instead of the Prod-Branch)?
When I look at the build definition, I think i would be possible, just be editing the Server Path (Repository > Mappings) from $/NameOfOurApp/Prod to $/NameOfOurApp/Prod-Rel-Version-x.x.x)...that should do the trick or not? But from what I read, it's not possible to use Build-Variables in Server Mappings, so I cannot change this variable for example in the Queue new Build Dialog...
What's the best way to accomplish my scenario?
The only way to do this is to create a single build definition which downloads all the branches. Then use variables in the tasks to select the version to build. This will become very messy (and slow) very fast.
Instead it's much easier to clone the build definition. Alternatively you can create a Build Definition Template from an existing build definition and use that to create a new Build Definition.
A much, much better solution however, is not to rely on so many branches.You only need the branch when you really need to make a hotfix, and you only need the stages branches when you have a lot of findings in higher stages. By improving teh way you work, you'll be able to get rid of the branches, simplifying the work for all.
Update
VSTS and TFS 2018 now support the use of variables in the workspace definition.
I have been researching and am trying to figure out the best branching and deployment strategy to accomplish the requirements below. Maybe I’m missing something but it is more complicated than it seems. Ideally, we’d just have one permanent branch, ‘master’, that could have specific commits tagged to mark releases to production.
Our current strategy is based on Git Flow and has permanent branches ‘master’ (only has releases to production) and ‘develop’. The primary thing that complicates using a multiple permanent-branches model is the concept of “promoting” the same build from the staging environment to production. Currently, this needs to be done in a separate source code branch (deployments to staging come from ‘develop’, deployments to prod come from ‘master’).
Tools: Git (VSTS), TeamCity, Octopus Deploy
Requirements (feature and hotfix lifecycles):
All code is reviewed via pull requests (enforced via branch policies)
All code gets deployed to a staging environment for testing
We can quickly go back to any snapshot of code that was deployed previously
If testing is successful, then the same build can be “promoted” from our staging environment to production (no need to build again)
Features accumulate over time before pushing out to production as a single release. Hotfixes have to be able to go through without getting caught up in the "all or nothing" next regular release.
I like the idea of having one permanent branch with tags (re: The master/develop split is redundant, http://endoflineblog.com/gitflow-considered-harmful), but having additional permanent branches may better facilitate deploying to different lifecycles/versions (feature and hotfix) to Octopus.
I have been wrestling with how best to pull this off and I may be over complicating things. Any feedback is appreciated.
It seems you have a number of questions and they are quite broad... I'll add some comments to each of your requirements as a conversation starter, but this whole thread might get blocked by moderators as it is definitely not the style of questions SO was made for.
All code is reviewed via pull requests (enforced via branch policies)
I haven't looked at VSTS for ages, but I'd expect they already support branch policies and pull-requests, so not sure if there's anything you need here other than configure settings in your repositories.
In case VSTS does not support that, you might consider moving to a tool that does e.g. BitBucket, GitHub, etc. Both of these have an on-premises version in case you can't (or don't want to) use the cloud hosted version.
All code gets deployed to a staging environment for testing
You achieve that with setting up lifecycles in Octopus Deploy, to make sure deployments/promotions follow the the sequence you want.
We can quickly go back to any snapshot of code that was deployed previously
You already have source control, so all you need now is traceability from the code that is deployed in an environment, to the deployment version in Octopus Deploy, the build job in TeamCity, the branch and exact commit in your source control.
There's a few things that you can do, to achieve that:
Define a versioning scheme that works for you. I like to use semantic versioning. "Major" and "Minor" versions are defined by the developers, and the "Patch" is the auto-incremented number from TeamCity (%build.number%). Every git push build the code and generates a unique build version (%major%.%minor%.%build.number%)
As part of the build steps in TeamCity, before you compile the code, make sure your source files are patched with the version number assigned by each build, the commit hash from your source control, and the branch name. e.g. if you are using .NET, make sure all the AssemblyInfo.cs files are updated with that version, so that the version is embedded in the binaries. This allows anyone to query the version looking at the properties of the binary files, and also allows you to display the app version on the app itself (e.g. status bar, footer, caption, about box, etc.)
Have TeamCity tag your source control with the version number of every build, so you can quickly see on your source control history. You probably only want to do that for the master branch, though which is what you care about.
Have Octopus tag your source control with the deployment version number and the environment name, so that you can quickly see (from your source control) what got deployed where.
Steps 1 and 2 are the most important ones, really. 3 and 4 are just nice-to-have. Most of the time you'll just open the app in the environment, check the commit hash in the "About", and do a git checkout to that commit hash...
If testing is successful, then the same build can be "promoted" from our staging environment to production (no need to build again)
Again, Octopus Deploy lifecycles, and make sure anything different in each environment is defined in the configuration file of the application, which is updated during the Octopus deployment, using environment-specific variables.
In terms of branch workflow, this last requirement makes it mandatory to merge changes into master (or whatever your "production" branch is) before the deployment lifecycle can begin.
We have our build and deployment scripts set up in TFS 2010.
But we are also evaluating indeo Build Master. Has any one used this before?
Also, in general, for a full .NET house does it makes senses to have another SCM management tool?
Here is the link for inedo
I found this while researching Inedo's BuildMaster as well. We're a .NET/TFS shop, and BuildMaster solves all sorts of different problems.
Here's a blog post I found that discusses the differences:
http://blog.inedo.com/2011/06/06/how-does-buildmaster-compare-to-team-foundation-server/
We're using the free version of BuildMaster and may upgrade to enterprise once we use it for other projects.
Buildmaster has a TFS plugin that helps grab builds from TFS Builds. We use Gated check-in to ensure the code builds and Buildmaster to package the build for 1 click to deploy through the environments. Buildmaster has a fix forward approach (as in, no roll backs), where you create many builds for a release and each propagates through each environment and when 1 or more exist in say QA and have not moved to Staging, they will both be moved to staging at the same time, but in order, thereby ensuring all artifacts move through every environment.
Prior to Buildmaster, we used an xml driven PowerShell script that worked well, but Buildmaster agents saved us from remote desktop script execution. Our Powershell script has 1 advantage that Buildmaster does not yet have. We used the xml configuration file to hold application configuration file information, including file names, relative paths and xpath settings to inject values, xml fragments and remove xml nodes from configuration files coming from source control. Buildmaster uses template configuration files stored in Buildmaster, with tag replacement for each environment. This results in high maintenance should anything change in a configuration file, such as additional environment non specific sections being added, which would require creating the template again.
Buildmaster does have a custom action that allow you to run executables, so theoretically, you can run your own commands to perform functionality that Buildmaster does not have built in, but this is not ideal.
In the spirit of keeping my SVN trunk clean and ready for deployment, I've been utilizing the following source control model. For the impatient, the basic concept is that you create development branches to do actual development, and leave the trunk clean and ready for deployment, at any time (no junk in the trunk).
In addition to this, I am configuring TeamCity for continuous integration. Within TeamCity, I'd like to ensure that all development branches, as well as the deployment-ready branch (the trunk, in my case) build correctly and pass all unit tests.
This might be a stupid question, but not being overly familiar with TeamCity, should I create a new TeamCity project for each branch? The deployment-ready branch, in particular, has a few additional rules than the development branch. For example, releases should be saved in versioned directories on the file system (e.g., C:\Projects\MyProject\1.0.187..., C:\Projects\MyProject\1.0.188...) to enable easy access to the binaries, at any point in time. On the other hands, saving versioned copies of the assemblies in the development branches is not necessary and would waste hard disk space.
Within TeamCity, I'd prefer to see only a single project for each software project. In other words, if my company is working on X number of development projects, I'd prefer to see that project listed only once, not X * 2 (assuming each project has only two branches).
You only need to create a single project, but you will need multiple build configurations - 1 for each branch. As far as I know, you can't customize the artifact folder name on disk (it's an auto-increment number), however you can download all artifacts as a zip file in TeamCity 4.5 from the UI. There is also a scheduler included with TeamCity that lets you cleanup artifacts so they don't consume too much disk space.
TeamCity 2018.1.5
TeamCity doesn't support multi branches for SVN as for GIT - so I solved such problem with Configuration parameter - where I set active branch from which I need to build and after can easily switch to another branch by running a custom build or change that configuration parameter.
After need just configures triggers to start building from a specific branch:
So on project side you can see different branches
And easily switch between branches by running Custom Build and change branch there:
Describe the process you use to develop web applications at a not-so-high level, focusing on VC, bug tracking, QA, unit testing, deployment and anything else similar (minus the planning/client communication side of things).
I'm new in this area, so my rough example (read: haven't used this process) is no doubt abit off, so to speak - point out it's flaws so I can learn.
Eg.
Create project repository on local SVN server.
Create batch/shell scripts for DNS mappings.
Check out project, begin work on local working copy.
Develop features as branches.
Track bugs with Mantis (link commits to bugs through it's SVN integration (no idea if that exists)).
Document as you go.
Do QA on branch.
Merge to trunk when stable.
Unit Testing?
Commit to repository when feature is implemented and stable.
Copy releases to tags in repository. Eg. /project/tags/rel-123/
Use Phing to upload to staging server. (Could someone please clarify exactly what a staging server is used for beyond 'testing'?)
Use Phing to prep live site for update, set up DB/deploy, etc.
Create/checkout HEAD version ("main branch")
Develop code and sync with the main branch -at least- daily
After development is done, write and run unit tests
Go through code review and submit code/changes to the main branch
Let continuous builder run all unit tests and system/integration tests on main branch
When ready, cherry pick revisions and integrate them to the QA branch
Run system and integration tests, fix reported bugs, or rollback as necessary; this repeats steps 4-7
After QA signoff, integrate QA change to release branch
Run unit tests, system/integration tests on release branch
Deploy to production and run sanity tests.
A staging server is a copy of your production environment that is as up-to-date as possible. On my current project, we're able to keep each release independent from each other, so our "staging server" is our production server, just accessed from a different url.
Notes and discreprencies:
All of the steps have some variation depending on the size of your project. The larger your project, the better the benefit from cherry picking and environment separation. In smaller projects, these can just be time sinks and are often ignored or bypassed.
To clarify, there is a Development stack, QA stack, and Staging stack. Depending on your project size, QA might be staging, Production might be staging, or some combination thereof. The separation of the Dev and QA stacks is the most important one.
In the steps above, I'm assuming both code and relevant data is versioned or tracked. Having a release and build process that takes control data into account makes a release very, very easy.
In a small-medium sized project, there may or may not be a release branch; it depends on the frequency of code change. Also, depending on the frequency of code change and size of your project, you may integrate the full QA branch to the Release branch, or cherry pick specific revisions to integrate to the release branch.
FWIW, I've found "migration scripts" to be of little value. They're always a one-off script with little reuse and make rollbacks a pain in the ass. Its much easier, I would argue better, to have the application backwards-compatible. After a few releases (when a rollback is a laughable), data cleanup should be done, if necessary.
Very roughly:
Create repository in SVN
Checking local working copy to developer environment
Update/commit changes frequently
Deploy to stage from SVN trunk using custom deploy script
QA tests on stage, reports bugs in Mantis
Developers fix bugs, mark as resolved
Re-deploy to stage
QA tests bugs, closes if fixed
QA is finished, do regression testing
Deploy to production using custom deploy script
Do a little dance
We also create branches for future versions or features. These eventually get merged into the trunk.
We keep our db structures synchronized with a custom db comparison tool that is executed during the deploys.
Old post, but interesting question !
At my company now :
Create a new Github repo
Configure Jenkins
Clone locally
Start a branch
Develop and add tests (server, client and e2e)
Commit for every step, and fetch + rebase to keep the branch in sync
When ready, push the branch to the server : a pre-commit check lint and tests and block if not ok
Create a pull request for the branch
Here, jenkins automatically runs tests on the branch and flag it as "green" or "broken tests" directly in the pull request
Have at last 2 colleagues review the pull request and fix their findings (back to step 5)
When everything green and 2 colleagues have agreed, the last one merges the pull request
Delete the branch on server
When ready, push a new version
Latest version get immediately deployed on a testing platform
QA validate the corrections and features introduced (back to 5 if problem)
(TODO) deploy to a pre-prod with identical parameters than the production
Deploy to production
Go apologize to users for the bugs introduced ;) and report them in the issue manager
get feature requests and report them in the issue manager
restart cycle at step 2