Fixing the Cost of Poor Quality Deployments

I had a hallway conversation with a colleague of mine the other day about what the benefits of  Continuous Deployments and how that could translate into discussion points with clients about the role DevOps can play with in an organization. During the course our conversation, I spun up a side thread and starting thinking about how one could approach the topic from where most businesses live and breathe—their bottom line. Approaching a potential client or even current client with a DevOps solution for their organization should really be around their cost savings. Time (speed to release) is also a factor, but I am going to approach this from the tack of cost.  Depending the customer or the client cost of deploying is more of a factor and speed. If you approach the cost factor first and tie that into the speed, then it is a double win situation.

Calculating the costs of deployments

Most organizations can claim that they have an automated deployment process, but it usually includes an individual either running script on the destination server, copying folders, files and even configurations to the destination.

How do you calculate those costs? Think of it as man-hours, each employee of a company has a cost associated with them. Each man-hour can now have a cost associated with it. So now we can create the formulae:

Cost per man-hour (CPMH) = (average hourly rate for 1 person)

Cost of Deployment (COD) = #of personnel *# of man-hours * combined CPMH for the # of personnel

For example:

We have 4 personnel who each have $100.00 hourly rate that is going to be $400 for 1 man-hour time for individuals.

Combined CPMH = $100.00*4

COD = 4 personnel * 4 man-hours each *(Combined CPMH)

So the simplistically any one deployment would a cost of 16*$400 or $6400.00. Those man-hours are never recoverable and the number personnel who could doing other things of more value are now burning monies to babysit a deployment.

Donovan Brown is quoted to have said “Never send a human to do a computer’s work”. He is absolutely right and here’s why. Humans by nature are fallible, there are going to be mistakes made even with rigid checklists and stringent policies. Repeatable processes that a human follows can and will be over looked. Overlooking steps or even typing a wrong character to can lead to errors in a deployment. So if you look at how employing a DevOps solution can benefit an organization you have to calculate your cost savings in the man-hours recovered with the use of automated tools to perform the repeatable basic function of performing a deployment.

Cost of Poor Quality Deployments (COPQ-D)

Above I spoke about the basic costs of performing a deployment, but how about the cost of poor quality deployments? Those are the types of deployments that fail and any number of developers and other personnel are immediately brought into a bridge call to either troubleshoot or to provide other types of support during the course of a failed deployment.

For example: we have a failed deployment  that takes 8 personnel a total of 6 hours to troubleshoot diagnose and determine a fix.

Person 1 = 100.00/hour; Person2 = $125.00/hour; Person3-8 = $75.00/hour; Combined CPMH = 100 + 125 + (75*6) or $675/hour

Personnel Cost (PC) = #personnel * the Combined CPMH

PC = 8*675 or $5400

In the end it cost the company to pay their employees $5400 because of a failed deployment, but coupled with this you have to also calculate lost business to an unavailable site. Another question that adds to the overall cost of a poor or bad deployment is the costs associated with performing a rollback of your application back to a known state.

These are just small examples, but I think that if you look back to some of your previously failed deployments where there were 10s of people on a call most of them idle while one or two individuals were performing screen shares with others fighting for verbal control of the situation.

Fixing it

The fix is really about being defensive in your ability to build, deploy, and test your compiled code before it even reaches your production environment. To perform this fix you need to be aware that your pipeline of code should be a single version that has progressed your lower test environments with increased testing at each stage.

Image result for ci/cd images

Next is building confidence in your build (branching and versioning). Ensuring that your branches are short lived and that your main branch is the single source of truth is critical to your team’s success. Consistent versioning is also important here, because in all cases for each build that is performed should have its own version even for very minor changes to your codebase.

Accurately describing your environments (Dev, Stage, Prod) and the server( s) that reside in each along with the roles that each server performs is another critical step for success. Knowing what each server does and carving up your packages to focus on that role is one more important thing in maintaining consistency and accuracy of your deployments.  Configuration values for each environment is key and should be kept out of your package codebase. Extracting those values to a central location based on machine role and environment adds to the consistency of your pipeline and allows for quick changes if the values change at any point for any reason.

Finally, now that you have an accurate build from a single source of truth and you have your environments and roles established, comes down to creating a deployment process that can be use across all of your environments with no variation.  Here is where the cost savings come in.

  1. You have a consistent build and deployment process
  2. You have a consistent auditable trail from changeset/gitcommit to deployment of your code
  3. You have near immediate feedback from your team and are able to ensure faster delivery times for fixes or changes

If you have a full CI/CD pipeline for your codebase the cost savings of deployments now become trivial because are not involving humans and the cost of humans that invariably make mistakes.  If a normal deployment before the automation took 4 hours with 4 person at an average of $100/man-hour that would $1600 dollars for an ideal manual deployment. Now if a developer just changed some code and checked it in, the automation now takes place.  The developer is now free to work on other other items while the deployment occurs.

For the sake of argument if a normal pre-automated deployment took 16 man-hours and now we allow the servers to work in a consistent automated fashion that will only take 20 computer-minutes, the savings would be

16*60 = 960 man-minutes

960 man-minutes/20 compute-minutes * 100 = 4800% savings

Now with that type of speed up and reduction of cost you have the ability to add more features, kill more bugs, and generally put the latest information in front of your testers or consumers.

Managing DevOps as a Service (Part 1)

DevOps Challenges

One of the bigger challenges I see in the DevOps space is when you attempt initiate DevOps as a Service (DaaS).

My Definition: DevOps as a Service (DaaS)

  1. Performing actions to allow for teams 1+ to deploy codebase(s) to multiple environments (1+ servers) and maintain those servers within specifications.
  2. Maintaining multiple environments across globally distributed teams with a follow the sun approach
  3. Allowing for just pass through of code and deployment while maintaining infrastructure for enabling teams.

Typically what you see with small and medium sized teams is that one or two of the members of the development team are involved in the operations space as well. This works from the standpoint of smaller teams who have intimate knowledge of their environments, code base, and configurations. Yet, what if you had to control hundreds of teams? Different code bases? Different time zones? Different environments? Hundreds, if not, thousands of servers spanning on-premise, AWS, Azure? What you do and what can you do?

A friend of mine Damian Brady wrote about DevOps as a culture. Well truly it is a culture, you have to have ownership of the work that your are doing.  All too often, I see where teams develop and test locally and assume that their codebase is going to work in the various environment’s that they deploy to. A “throw it over the fence” style of development and deployment. This can be problematic when the assumption from the developers is that the operations team knows and understand the nuances of their codebase.

Categories of Development and Operations

Image result for devops images

Let’s define in simplistic terms both what I mean by categories of Development and Operations. Development is really the design and coding of an application or API to be consumed by internal or external parties. Operations is about the continuous maintenance of the application or API once the Development portion of the job is completed and the team that originally developed the code has rolled off on to other projects or clients. In nutshell, this “old school” approach has left many a maintainer performing Development work that really isn’t their forte. Developers are so focused on their timeline, their code that sometimes don’t understand or don’t want to understand the underlying infrastructure that serves up their application. This leads to the dreaded WOMM effect and its consequences.

My definition of WOMM is “Works on My Machine”. This the most basic build on the local machine that “just works”. F5 and it just works. It is also, from my point of view as a bacteria or viral disease that at some point most if not all development teams contract in their effort to quickly get code developed for consumption.

Many consulting teams in my experience fall into the Development Only category because of a few reasons:

  • Contract is Fixed Price or has limited scope
  • Operations, like Documentation, is the first to be cut from a contract to make the cost of work attractive
  • Business Developers sometimes fail to grasp long term affects of a short term project and too narrowly scope the deal in the hopes that contract once signed can lead to further work. Sometimes this bet pays off; but most others it does not.

Operations teams on the other hand sometimes have unfounded aversions towards developers because of a few reasons of their own:

  • Developers inherently create bad code that breaks functioning applications and infrastructure – emphasis on the infrastructure. 
  • Developers don’t really understand infrastructure or how their codebase can work on one set of servers and yet not work at all in Production

Merging of Development and Operations

Now that we have the basics, we build up and look at the merging of developers and operations. In my experience I have seen a few larger organizations where there is a such a large divide between developers and operations that members of the operations team end up becoming the defacto hidden developer, bug fixer, tester for developer teams. I have in the past fallen into that category when I started branching out from development and into the operations space.

In my opinion it is very good for developers and operations teams to have a rudimentary understanding of each others space. Yes there are purists out there that would contend otherwise, but in order to be an effective team and have a strong application for consumption this is a critical piece within DevOps. Not only should the developer understand the infrastructure that they are going to host their application on, but they should be developing on it as well.  There are edge cases about this argument, but in general this is a good practice. Likewise it is good for the operations team to understand the developer space and be given a crash course when the code becomes un-configurable and broken.

DevOps is about continuous ownership from planning the application, to IDE development, to source control, to build, and finally to deployment. It ensures that the developers understand that to put their code into production is not the responsibility of a select few Wizards of Oz, but developer and the operations team go along the journey together to ensure a smooth and proper deployment.

Benefits of using Octopus Deploy Integration Tasks in vNext Builds

If you are like me and you use Octopus Deploy for deploying your projects; it can be a challenge to keep your OctoPack version updated. Restoring the OctoPack NuGet package each time you build with VSTS or TFS can be a challenge because if you perform a TFS XAML Build the build will fail because it cannot find the associated OctoPack targets and associated dlls. A workaround is to include the packages folder that contains the OctoPack targets file and associated dlls with your checked-in codebase, but that can be messy and lead to artifacts being left over in the case you wish to upgrade OctoPack to a newer version.

Another detractor to leveraging OctoPack in your solution sometime around version 3.4 a number of breaking change were introduced that caused nuget push issues. The teams that I work with on a daily basis are still on an older version of Octopus and when they installed the latest version of the Tentacle issues started to crop up along with failed builds and pushes to the internal NuGet repository.

So what are the benefits? According to the marketplace documentation, you can still use your OctoPack MSBuild arguments, but it doesn’t really apply to your older XAML builds.

Benefits of Octopus Deploy Integration

Some of the larger benefits when using the Octopus Deploy integration steps are:

  • You are always up-to-date
  • You have a clean project (no more packages to put with your codebase)
  • You have more Octopus Steps to play with (OctoPack can do them, but again it means more MSBuild parameters)
  • Troubleshooting is easier (Build shows all of the output in the console)

Benefits of vNext Builds with Octopus Deploy Integration

There are others who have blogged about the benefits of moving to the next version of Build. So I won’t go into the particulars. Suffice to say that replicating your XAML build in the new Build system is extremely beneficial and coupled with the Octopus Deploy Integration extension it can be even more powerful (

  • Control – You own it, you build it
  • TaskGroups (combined step tasks for Build templates)
  • Build Templates (cloneability, reusability)
  • Cleaner Visual Studio Solution
  • Centralized build/package/deploy processes
  • Decoupling of dependencies to installed packages

Even if you still want to use OctoPack, you can, you just have to take your old MSBuild arguments and paste them into the Visual Studio Build Step MSBuild Arguments parameter. Under the covers, it still does a lot of the same work, but the added benefit of with using the Octopus Deploy Package, Push steps allows for cleaner output logs during a build, package and push. One other benefit not mentioned previously is that with the new Build System you don’t have to check-in your packages folder that contains the OctoPack information (the NuGet Restore step takes care of that).


There probably some especially around references, but I can’t think of any that would hinder the overall usage.


The better approach of keeping a clean project/solution and letting TFS/VSTS do all of the work is just makes sense. Cluttering your project with excess complexity can make sustainable, reusable codebases hard to achieve. Coupled with that is the fact that over complicating your solution can also cause other developers within your team to have trouble trying to build the solution locally.

Starting From Scratch–Building Your Project Right Part 1


Let’s say for the sake of argument that you just uploaded your codebase into TFS2017/VSTS. What do you do? XAML builds are deprecated and the new Build system seems daunting. Again what do you do?  You can watch videos and read tons of different stackoverflow articles and blog posts on how to… yet there are still lingering questions on how to “just” start from scratch.

In my experience with teams from around the world before they used a version control system, would happily code on their local machine, perform a local build (where is just worked), and then using the power of Visual Studio would “Publish” their fixes directly to their remote environments. For one that is poor a ALM practice and two there is just no way to track any of the changes that were either breaking or fixing described typically with screenshots in an email thread. Overall it was the Dark Ages, a chaotic time where teams that were trying to be Agily/Scrummy/etc, yet really having no anchor or starting point to leap off from for how do perform a proper “single source of truth” build; let alone a deployment.

With “DevOps” and “Shift Left” being the buzz words of the day, it can be hard to get your team in the correct cultural mindset of ownership and control. In this article we will dig into the new MS Build system as if you were a newly minted Developer Lead with the appropriate Administrative Rights in your TFS/VSTS project.

Here is a basic scenario and then we will work through how you can build your project right with the new Build system in VSTS/TFS2017.


  • You are just now using source control
  • Your builds consisted of developers performing builds on their local machines
  • You may had a build server in the past, but you have either upgraded or the build templates that you previously used are incompatible
  • You have Post-Build scripting moves files around to make your codebase viable for a manual or even scripted deployment


This is barebones. Your particular scenario may not apply and I will discuss in the future how to do advanced builds and deployments.

Your codebase has been freshly checked into TFS/VSTS source control. If you chose Git or TFVC, it doesn’t matter the below techniques will apply for both version control types.  You need to perform a build that is simple and the output needs to packaged and ready to be consumed by either Release Management or Octopus Deploy. So where do we start?

How it’s done

Now for the pretty pictures.

First log into your TFS or VSTS site or account and click on the Build & Release tab. It should be blank if you are first starting out. The screenshot I am providing is from previous posts that build more and more advanced concepts.


You will see that there four items in the image called Mine, All Definitions, Queued, and XAML. You will not need the XAML tab; it has been deprecated and you can edit your old XAML builds nor are they compatible with the new Build system. So because of those points we will not be discussing that tab.

  • Mine – represents those build definitions that you the logged in user have created


  • All Definitions – represents all the build definitions that have been created for your solutions, branches, etc


  • Queued – represents all those builds that have been currently queued or running or completed


Now lets create a new build definition for our solution. In our case we are going to do something basic and build up from there.


then we get a popup that gives a number of options of generic templates to choose from. For now we will just choose the Visual Studio build. The reason behind this is that most developers are accustomed and acquainted with and it is in keeping with my idea of starting with the basics and building from there.


Click Next and you will see a another page where you choose your repository and other settings for your build.


The great thing about this page in the Build Definition Wizard is that you can make preliminary adjustments to your build before it is created. For instance you can choose the type (remote or local) of repository that you wish to point at, select the branch you wish to build from, and determine whether or not you wish to have Continuious Integration (build after every check in).  Subsequently you can choose the default agent for your build to be something different that has the capability you require to build your solution.


Make your selections and then click Create. Now you will have a “unsaved” generic build definition that you will need to continue editing. But first it will be wise to save you creation so that if you have to leave the page you don’t have to start all over again.



Now that we have saved the build definition, we can go into each of the build steps and one make adjustments and two add more build steps as necessary to perform our build.

On the left part of the page you should have noticed that there are six steps and descriptions for each. Lets talk about them a little in detail.

First you have the NuGet restore.

image What this little step does is go into your solution and check for the packages.config file and restore or install all of the packages each time you build. In this instance you can ensure that you have the everything restored from or other repo of your choice without having to check in your packages folder like you would have to do for your old XAML builds. With this step you can control a lot of what can happen with the installation or restoration of your packages.

Next is the Build Solution. This is a powerful step very similar to the older XAML Process. One item of note is that there are some overlapping of functionality that I have found for build steps, while it may not hinder a build, it just gives you further options for streamlining your process.


This will look a little familiar to those with a XAML build background, but this is a lot cleaner and can be adjusted to suit your needs. MSBuild arguments still work, but in some cases you don’t have add switches like “/m:1” when you can check the Advanced->Build in Parallel check box.

The Text Assemblies Step is standard with the Visual Studio Build Template. It will use Visual Studio Test to perform that function to ensure that you have testings completed and code coverage for the widgets you have on your Dashboard.

imageFrom a testing perspective this a powerful step that allows you to go into and perform advanced testing from the build without a lot of tools that you would assume that you need to perform the reporting, etc.

Also note that you see a image or this imagein each step it will show either a hover tip or open a new tab to more details about the step for your leverage or understand.

Next is the Publish Symbols path. It is a way for you to use your pdb and obj files to help debug your application on a different machine other than where your sources were built.


Next is the Copy Files to: step. This step is takes the output from your sources bin directory and copies those files or folders to your artifacts directory.  The artifacts directory is a cleaned directory that ensures that you have just the right objects in your artifacts folder that need to be either packaged or deployed at a later time. Again clicking on the image icon will provide options and parameters for you to use to make your build more coherent and robust.

So after the previous 5 steps, now what happens? Well the build agent then publish your outputs to a Drop folder. Typically this drop folder is within the $(Build.ArtifactStagingFolder). Where might that be? It is located under your build definition directory. Similar to this file path: “E:\TFSBuildAgent\vsts-agent-onprem\_work\5”. Inside of this folder are 4 folders that represent “a” artifacts, “b” build (output), “s” sources, TestResults (obvious).  Look at Resources->Variables for more information.


Once we have made our initial edits to your build definition, we can now Click Save and then queue a new Build.


and our build succeeded.


From our log output we can know that the artifacts are “published” and a little magic later we can compare and see that the artifacts are in the location where they are intended to be.


and finally…

Don’t be afraid of the build

As the heading suggests, when you are first starting out with using TFS/VSTS Build, don’t be afraid if your build fails or doesn’t perform the functions you are expecting immediately. I cannot stress this enough. I know that when I am testing builds that I spend a lot of time troubleshooting failed builds before I finally have a successful (green) build.

By working through your issues and using a methodical approach you can be successful. You shouldn’t feel pressured to get it right the first time. You don’t have to feel like you are going to get fired for having a broken build. Work through it, understand the build process, then communicate the understanding to your leadership.

If you are developing a Web Application or web api you may have to consult this how to. But if you are doing a single applicaton (exe, service, etc), then this approach can get you started in the right direction.


Here is another good resource about build settings and build tokens further details about the Visual Studio Build. Word of caution here is that if you are using TFSBuild.proj type of file, you will not be able to use Build because it contains tasks and targets that are supported only for XAML builds. this is for getting the different built-in and custom variables to work in your favor.

CI/CD with TFS/VSTS and Octopus Deploy

Building off my previous posts here and here about building multiple projects within a solution and troubleshooting packaging of your projects. We will now delve deeper into the Continuous Integration and Continuous Deployment pipeline that can ease the tensions of Deployment Aversion. Using two very powerful tools in your arsenal, you can streamline your deployment process and ensure that you are getting the biggest bang for your buck. Up until now we have identified our pipeline components and we have successfully, albeit manually, deployed our sample codebase to our destination servers. The question now is: can I streamline my pipeline using good ALM practices?


  1. You have your source code checked in
  2. Your build definition is in place
  3. You either have a partial Octopus Deploy project or similar

Setting up for success

Lets double check our Octopus Deploy Project. We will need to ensure that we have certain steps, configuration values, and settings.

Lets start out with cloning our already working deployment project.


Save our newly cloned project. We will get back this Octopus Project in a moment, but first we will need to do somethings with our TFS/VSTS build definition. In this example, we will expand upon our previous build definition and clone it. Why? Well first we know that it works and second it is easier to take away unneeded steps instead of trying to add and configure steps from memory. Cloning a Build Definition is very simple and straight forward. The below gif shows you how its done.


Since our build definition is only queued manually we will need to go and make some changes to the Triggers for the build to allow it to perform the CI for the beginning of our CI/CD pipeline. We will edit our newly cloned build definition and choose the Triggers tab and then select.  For now we will just check the Continuous Integration and leave the defaults.


Now each time there is a change to the codebase and change is checked in, this build definition will start and finish with our packages being pushed to Octopus Deploy. One of the many benefits here with the use of Triggers is that you can have multiple build definitions that can focus on specific branches and with CI/CD working in your favor your can get your code to testers or others for faster consumption and approval.


CI/CD Option 1

You are probably asking yourself why there is an Option 1 and 2. Well the fact of the matter is that with Octopus Deploy Extension you basically  perform can perform all of the steps of packaging, creating a new release, and finally queuing up a deploy.  Essentially, TFS/VSTS is now a one stop shop for building and orchestrating  your build and deployment pipeline.

How to perform Option 1

Going back to our CI/CD build definition we need to add a couple of more steps. Click add build step and select and add Create Octopus Release and Deploy Octopus Release.


Now we see that for our entire build definition we can build, test, package, publish, create and finally deploy a release. If you noticed that there was Promote Octopus Release, that task can be used in other build/deployment scenarios. For now, though, we are just going to use the create and deploy release.


Editing our create Octopus release step, we see a lot of options that we will need to fill out. We fill out the Octopus Deploy Server connection endpoint, we select the project name. For now we are going to use the Octopus defined version number, but later we can change this to be what ever SemVer compatible version number we want to display. Finally in the Deployment section we select our initial environment we would like to deploy to. After that because I like verbose logging for troubleshooting, select the Show Deployment Progress. This will ensure that we have a complete set of logs for our End-to-End test.


One thing to note here is that you add a lot of data for your release notes. This great for troubleshooting or even attempting to rollback to an earlier series of changesets.

We are going to kick off a manual build/release creation first, but to make sure that we are putting everything in the correct order.


and the end result without doing anything special with Octopus Deploy.


and now our Web application is still functioning.


Let’s go and make a change now in our source code, check it in and then see what happens.

Made some changes to our index page.


checked it in


Synced with the master (because this is a Git repo)


Build kicked off


Build finished and deployed


Now to validate against the working web application.

It worked. I made the change and the change was “automatically” reflected on the site. Now keep in mind this is simple way to perform this function. If you needed to perform a rolling deployment, or some other type, it would make sense t to adjust for Octopus Deploy process to accommodate those requirements.


CI/CD Option 2

Option 2 involves some manipulation of Octopus Deploy and not so much TFS/VSTS. If we leave what we were currently performing in TFS/VSTS from my previous post we will need to work and manipulate Octopus Deploy a little more.  So following the same example as above we will clone both the TFS/VSTS build and the Octopus Deploy project/build definitions, to ensure that we have a clean break from what worked  to what could work.

How to perform Option 2

There are a couple of items that we need to accomplish here. Because we have already cloned both the Basic Build definition and the Octopus Project, we will work with those cloned items in this mini exercise. For now we are not going to touch the clone of the build definition because it is generic and just performs the build and then packages and publishes the package( s ) to our Octopus Deploy internal NuGet repository.

First we will need to change how our Releases get created. After selecting your Process, find the Automatic Release Creation in the left hand side of the page. Select Project Triggers, this has moved from previous versions of Octopus Deploy and then select the create a release when a package is pushed.




Then we need to change the behavior of our Lifecycle (more information is here). The important fact here is that if we wish to stay away from modifying our build definition to automatically deploy we can do it within our Lifecycle. One key note here is that the default lifecycle allows for deployments to created environments. While this is not ideal, there is a way for us to create and manipulate a new Lifecycle to benefit our needs. For our cloned project we will need to “Choose a different lifecycle”.


Special note here is that the lifecycle once applied, will only be used by your deployment project going forward. Any previous releases that were created will use the previously assigned lifecycle. This can be confusing, but it makes sense because Octopus Deploy takes a snapshot of all of the variables and state of your project for each deployment.

Let’s go ahead and create a new lifecycle:

Click Library->Lifecycles-Add lifecycle


Then we need to give the new lifecycle a Name and add a Phase.  This is important because the phase helps us describe what we wish to do in each step of our deployment.


Adding a Phase means that you are going to be describing what happens to your deployment. After you click the Add Phase you will get this:


Give it a name and then click Add environment


Initially you will see and empty drop down box and a couple of radio buttons. Select your dev or other environment that you wish to deploy to first and then select Deploy automatically to this environment as soon as the release enters this phase. Then click Add.


Now it should look like this:


Click Save and we are almost there.

You can can multiple phases and multiple environments to each phase depending on your need. For this exercise, we are putting out the CI/CD basics that you can build upon for your future development and deployment efforts.

Now that I have created that lifecycle, I need to perform a couple more things to get everything wired up and in sync.

First, I need to go back to my project and change the lifecycle from Default to CI-CD Option2.


The next thing we have to do is change the Automatic Release Creation under the Project Triggers.  Warning here is that if you have an external NuGet or other repo that you are dealing with this option will most likely not work for you.  There may be an option 3 workaround, but I haven’t gotten to that state yet.

Click on Project Triggers and then


image check the “Create a release when a package is pushed to the built-in…” make sure you select the deployment step that contains your package, then click Save


Let’s test this out.


Our build was successful.


And it just works now.



From Option 1 it is clear that you can just use the Create Release step and not be dependent on both the Octopus Create Release and Octopus Create Deployment. Either option is viable and can be used interchangeably depending on your needs. You can have build definitions that work on specific branches of code for CI/CD and then use the promote package to your higher environments. The above technique while focused on a simple web application can be used for more complex deployment scenarios and applications.

Building Multiple Projects and Pushing to Octopus Deploy with Build vNext

In some cases there is need to have multiple projects within a solution that each require being packaged and then published or pushed to your repository of choice for deployment.  Typically from a Web Application perspective you could have Web Services, Web Api, and finally the Web Application itself.

What I am about to detail for you is performing these actions with success using TFS 2017 and Octopus Deploy.  These same actions can be applied to Visual Studio Team Services (VSTS). Be warned that this technique will not apply to older XAML build definitions.


We are going to assume that you have basic solution with .Net MVC Web Application, MVC WebApi, and Windows Services projects. You can more than this, but for the purposes of this demonstration this is what we have. Something like this:


And we have the solution checked into Source Control like this:image

You will also want to make sure that you have Octopus Deploy extension installed or applied to your account or TFS instance.

Where to Start

Well the most common thing here is that you will need to create is a basic Visual Studio vNext Build Definition. Log into your Project and Navigate to Build & Release and then click New in the right hand corner.


Now we are going to Scroll down and choose a Visual Studio build template. I won’t go into the details of all the different templates are, but for this exercise we will choose Visual Studio because it is a very quick way for you to get started.

image image

Now that we have our basic build definition in place it should look something like this.


Now save what we have so that we can start with the meat of this exercise. The next little preparation that you have to do make sure that you create a Service Endpoint for your Octopus Deploy input. I will be using Built-in Nuget Repository, but can also use and external NuGet repository of your choice. The fields that you will need to fill out are listed at points 3, 4, 5. You need to give the connection a meaningful name that you can remember. You must provide a url to the octopus instance that you intend to publish to and finally you will need to have an API key with the minimum permissions to publish to the Octopus internal NuGet Repository. Rule of thumb here is to create or have a Octopus Service Account that has the appropriate permissions.


How its done

We now have the basics set up. So lets get into the requirements for getting multiple projects to be compiled, packaged, and pushed to Octopus Deploy. Previously you would have to have a lot of pre-work done to your actual project/solution, e.g., adding OctoPack, creating a nuspec file, etc. With the new build system and its extensibility, it makes your projects/solutions much cleaner and much simpler to use especially if you add more projects to your solution that require packaging and publishing later on.

Edit your saved build definition and select Build Solution step. We need to make an adjustment here to ensure that

  1. We get a separate folder for each project
  2. We ensure our Output Directory for the solution is pointing to our ArtifactsStagingDirectory

Like so.


What this will do will ensure that the build output from the step will go to the build artifacts directory on your build agent, similar to this:image

The “a” in this case means Artifact.

We will not worry about the Test Assemblies step right now and we can also leave the Publish Symbols and Copy Files Step and the Publish Artifact alone for now. The point of this post is to get your projects built, packaged, and published for deployment. Next what we need to do is add another few build steps to our Build definition.

Click on Add Build Step


And then we are going to Add the Octopus Package Application step, one for each of our projects that we wish to publish. Then we are going to add the Octopus Push Package(s) to Octopus step to finish up our Build.


Now for each of the projects you will need to edit the Package Id, Version, but more importantly you need to know what and where your source and destination path is going to be. If you don’t these two items correct, your build will fail.


We do know that our output is going to the artifacts directory and we know that each project is going to have its directory. But a critical component here is what the Octopus Step is going to do. It is important to note that we want, must, need to do is

  • Keep your package small
  • Take only the most relevant codebase

I have seen so many teams in the past and currently take everything from their source tree and package it into a 100MB+ file and attempt to push it to Octopus Deploy then deploy all of source tree to production. It is really hard to contemplate the security risks of putting your entire codebase for someone to steal and compromise.

For web applications and web api projects there is typically a _PublishedWebsites folder, this folder contains a reduced build output with only the most relevant dlls, config files, and other content for your web application or web api to run. Everything else is irrelevant and if you choose the folder at the higher level you will essentially get two copies of the same code base in your package. Citing the two points above, keep the package small and only package the most relevant code! This doesn’t mean only the files that have changed! This means your most minimal amount required run your application.

Now that we have edited the Package steps, we can move on the other important final element to this post, which is the Push Packages to Octopus.

Select the Push Packages step and you will notice that you need to edit the Octopus Deploy Server (this is the Service Endpoint that created earlier) and the most important item is the the location of the packages.  Earlier in this post I told you that you didn’t really need to worry about the Publish Artifact step. The drop directory is where we are going to put our package after the build and packaging steps and that same directory is going be where we find those packages and publish them to our Octopus Deploy NuGet feed.


Now we are done! Save all the work that we have done and then queue a build. Don’t get frustrated if you your build doesn’t register success. Take a look at the logs for each build you attempt and step through to ensure that your folder paths are correct. Ensure that the API Key has correct permissions to publish to the Octopus NuGet Repository.

If you do have a successful build it tell you that it performed the compilation, packaging and publishing of the packages. Similar to this.




Checking each step to ensure that the logs are telling me what is happening.




and finally verified it has been pushed to our Octopus Deploy instance.


Next Steps

Now that I showed you how get your build to package and publish to Octopus. You may wonder what about CI/CD? or what can I do now?

To answer the second question, you can actually go ahead and make this a task group and save it for other teams to utilize in the future. You can also use this technique for other project types as well. Once you understand how you can create a package with the Octopus Deploy Extension, you can change the build definition to a CI/Timed Build and get those packages published for the next phase.

To answer the first question: That is for another post.