The three failures of Continuous Delivery

Everyone seems to want to get on the Continuous Delivery train. Rightfully so, I think. For most, though, it’s not an easy ride. From my work with client and conversations with other coaches there’s a few common barriers to adoption.

In the end, the goal should be to be able to react faster to the market. And, to be honest, to finally be in actual control. But in business terms, it’s about cycle times. That’s what allows you to not just react quickly to market circumstances, but to actively probe markets and test product ideas.

So, as I mentioned, there’s a few common problems companies run into. First, just the basic technical steps to create a fully automated pipeline. Then, getting the tests sorted to a level that gives enough confidence to deploy to production whenever they’ve run. Only when those technical matters have been sorted do we get to the more interesting issues of allowing the business to make use of the possibilities offered by the newfound agility. Those have their own challenges.

Let’s have a look at the the ways these particular subject give teams trouble. In the hope that being forewarned some will be able to avoid them. I’ll go into more detail on how to avoid them in subsequent posts.

Get a pipeline

Now, if you’ve paid any attention to the literature, you know that at the core, CD is all about important things like process and a culture of quality. Which is all true, but that probably won’t help you very much. Most development organisations have spent years wrapping themselves in workarounds and buffers all painstakingly created to prevent detection of their real problems. So taking a relatively small, technical, step in setting up a delivery pipeline at least seems somewhat feasible and will by its nature start showing where some of the real problems lie.

A Delivery Pipeline

From what I’ve seen, just trying to set up that pipeline is trouble enough. That’s why I’ve put it as the first barrier to adoption of CD. It may seem easy, but there turn out to be many basic technical challenges. Most teams go through those same pains, and it’s not really surprising. There’s quite a bit of (often new) knowledge and skills involved. And teams usually have to deal with all kinds of legacy code and infrastructure, which doesn’t make it any easier.

Mostly, what companies find here is that they are missing is skills. And there are a lot of skills involved! A real DevOps approach should include operations knowledge in a team, but even then most of the skills needed to create a modern, fully automated infrastructure are something that takes most organisations a long time to develop.
It’s not that these things are beyond those teams, it’s just that they’ve not had to deal with them before. Sure, it is easy enough to package your application in a docker container and run it locally, but people are discovering it is quite a different thing to build it out further than that.


Testing is the achilles heel of many development teams. Most agile teams work hard to get and keep their code under test. Many fail. The advantage that Continuous Delivery has is that it sets explicit expectations on quality. There’s really no room to skimp on testing if every push you do should end up on production.
Like was the case for Continuous Integration, testing is what makes a Delivery Pipeline useful. It’s great if you have fully automated deployment, but if you have no way to determine if the code you’re building can be trusted, you’ll still not be in production any sooner.
There’s different ways teams fail with testing. Insufficient unit testing. Too limited protocol and service testing. A reliance on slow and brittle end-to-end testing. Skipping manual / exploratory testing, that may no longer be a gateway before going into production but is still very much necessary.


Organisations that manage to get past the first two hurdles have at their disposal a tool that can bring them unimagined business advantages. But even having come this far, existing silo’s, processes and political positioning prevent organisations from profiting from their newly found technical capabilities.

Symptoms of this can be found in the ignoring, or even complete lack, of market data in deciding on new products and functionality. In continuing a practice of long term planning, without built in checks to see if the intended goals are being achieved. In basing priorities on political influence instead of business goals. And even in a reluctance to release new features to users even once they’re available behind a feature toggle in production.

These issues can be the most difficult to address and need to be picked up at the highest management levels. They are attacked with changes in goal setting, reward systems, and organisational structure.

Interlocking pieces

As with any process, these different elements cannot exist for long without the others to support them. Testing withers if it cannot be run quickly and frequently enough. A delivery pipeline has little value if you have no way to know if you can trust the code that it’s building. And a highly evolved technical team that is not clearly and directly involved with business goals and customers will easily find more fulfilling work elsewhere.

That’s why my advice is to start in this order, picking up the next challenge as soon as there’s clear progress on the previous. You start building technical skills and then use that base as a flywheel to get a change in the rest of the company going.

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