Continuous Delivery: An Easy Must-Have for Agile Development


Everybody working in software development has heard about it when talking about software quality assurance: Terms that begin with “Continuous” and end with “Integration”, “Build”, “Testing”, “Delivery”, “Inspection”, just to name a few examples. The differences of these terms are sometimes hard to tell and the meanings vary, depending on who uses them. In this post, the easy implementation of Continuous Delivery is discussed.

For clarification, Continuous Delivery is defined as described by Humble and Farley in their book “Continuous Delivery”[1]. In this highly recommendable book, a variety of techniques (including all other terms mentioned in the previous paragraph) to continuously assure software quality are described.[1] Adapting these techniques does not require much effort nor experience and should be done in every software project. Especially in large-scale software projects, this technique helps to maintain high software quality.

Errors First Discovered by the Customer

In a software project with a lot of engineers working on the same code base, unexpected side effects of source code changes are very likely to result in erroneous software. If there are automated unit tests, most of these errors are detected automatically. However, unfortunately there are some unexpected run time side effects that only occur when the software is running on a particular operating system. In a normal development process, such errors are detected at the worst point possible: when the customer deploys or uses the software. This results in high expenses for fixing the issue urgently.

In order to prevent those kinds of errors, Continuous Delivery has developed. As Carl Caum from PuppetLabs describes it in a nutshell, Continuous Delivery does not mean that a software product is deployed continuously, but that it is proven to be ready for deployment at any time. [2] As described in [3], an article by Humble and Molesky, Continuous Delivery introduces automated deployment tests for achieving this goal of deployment-readiness at any time. [3] This post focuses on those deployment tests as it is the core of Continuous Delivery.

Implementing and Automating Continuous Delivery

To prove if software is working in production, it needs to be deployed on a test system. This section explains how to implement such automatic deployment tests.

Firstly, the introduction of a so-called DevOps culture is useful. This means a closer collaboration of between software developers and operation staff.[3] Each developer should understand the basic operation tasks and vice versa, in order to build up sophisticated deployments. Even though [3] describes this step as necessary, from my point of view such a culture can be advantageous for Continuous Delivery but is not mandatory for succeeding. It is not mandatory, because automated deployment tests can be developed without the help of operations, although it is certainly more difficult. More detailed information about DevOps can for example be found in the book “DevOps for Developers” by Michael Hüttermann [4].

Secondly, as explained in a blog post by Martin Fowler, [5], it is crucial to automate everything within the process of delivering software. [5] The following example shows a simplified ideal Continuous Delivery process:

  1. Developer John modifies product source code
  2. Test deployment is triggered automatically due to a change in the version control system
  3. Deployment is tested automatically, giving e-mail feedback to John that his source code breaks something in production
  4. John realizes he forgot to check in one file and fixes the error promptly
  5. Steps 2 and 3 repeat, this time John does not receive an email as the deployment tests do not find misbehaviour of the product.

For example, such a process can be automated completely easily with the software Jenkins[6] and its Deployment Pipeline Plugin. Detailed instructions for such a setup can be found in the blog post [7].

However, such a continuous process is not a replacement for other testing (Unit Testing etc.) but an addition to it. It is an additional layer of software quality assurance.

Steven Smith states in his blog post [8] that Continuous Delivery in an organisation requires radical organisational changes and is therefore difficult to introduce to a company. I disagree with that partly because it depends on the type of the specific company. If a company uses old fashioned waterfall-like development methods, Smith is right with that point. However, when concerning an agile developing software company, Continuous Delivery is nothing more than more automated testing. It does not require people changing their habits in this case, as the developers are used to Continuous Testing methods. The only additional work is to maintain deployment scripts and to write deployment specific tests.

Configuration Management Systems and Scripting

In order to perform deployment tests, scripts are needed for the automation. These scripts can be written in any scripting language, for example in Bash (shell-scripts). However, there are more sophisticated approaches using so-called Configuration Management Systems such as Puppet[9] or Chef[10]. According to Adam Jacob’s contribution to the book “Web Operations”, section “Infrastructure as Code”[11], the use of a Configuration Management System’s scripting language leads to the following advantages:

Firstly, such deployment scripts are declarative. That means that the programmer only describes what the system should look like after executing the script, without the need of describing how it should be done in detail. Secondly, the scripts are idempotent, so they only apply the modifications to the system that are necessary. Furthermore, executions of the same script on the same host always lead to the same state, regardless how often a script is executed. [11]

For these reasons, Configuration Management System’s scripting opportunities are superior to bash scripting. Furthermore, they provide a better readability, maintainability and a lower complexity of the scripts compared to similar Bash-scripts.


According to my software business experience, it is easy to implement Continuous Delivery step by step into an agile thinking company. The main things to focus on are the following: Firstly, such an implementation should be fully automated and integrated with the version control system. Secondly, a Configuration Management System is highly recommendable because of easier deployment scripting. Furthermore, such scripts provide better maintainability, which saves resources.

The goals achieved by the implementation of Continuous Delivery are twofold: Firstly, the release process is optimised, leading to the possibility to release almost automatically. Secondly, developers get immediate feedback when the source code does not work in a production-like environment.

In conclusion, Continuous Delivery thereby leads to crucially better software and can be introduced into an agile operating company without much effort.


[1] J. Humble and D. Farley, Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation, Pearson Education, 2010.
[2] C. Caum, “Continuous Delivery Vs. Continuous Deployment: What’s the Diff?,” 2013. [Online]. Available: [Accessed 2/2/2014].
[3] J. Humble and J. Molesky, “Why Enterprises Must Adopt Devops to Enable Continuous Delivery,” Cutter IT Journal, vol. 24, no. 8, p. 6, 2011.
[4] M. Hüttermann, DevOps for Developers, Apress, 2012.
[5] M. Fowler, “Continuous Delivery,” 2013. [Online]. Available: [Accessed 2/2/2014].
[6] “Jenkins CI,” 2014. [Online]. Available: [Accessed 2/2/2014].
[7] “Continuous Delivery Part 2: Implementing a Deployment Pipeline with Jenkins « Agitech Limited,” 2013. [Online]. Available: [Accessed 2/2/2014].
[8] S. Smith, “Always Agile · Build Continuous Delivery In,” 2013. [Online]. Available: [Accessed 3/2/2014].
[9] “What is Puppet? | Puppet Labs,” 2014. [Online]. Available: [Accessed 2/2/2014].
[10] “Chef,” 2014. [Online]. Available: [Accessed 2/2/2014].
[11] A. Jacob, “Infrastructure as Code,” in Web Operations: Keeping the Data On Time, O’Reilly Media, 2010.