It is relatively common in human endeavor to attempt to figure out how much work will be involved in a project, and be wrong. The more complex the work being done and the organizational system doing it, the further off estimates can be. This was one of the drivers for both Agile and DevOps: to take smaller steps with less dependencies and complexity.
The complexity problem is true in the path to application release automation (ARA) as well. ARA merges continuous test/continuous delivery with deployment automation, but both of these toolsets are complex and continuing to evolve. When you think about it, it is somewhat amazing that ARA can handle the breadth of functionality it is covering, while both sides are shifting and growing as well as it does.

When you approach ARA, you should make certain you have a handle on the amount of work that it will take to get the system up and running. It’s not simple, even if you’re already using a full CI/CD environment. But it’s worth the work, so here are some of the things to watch out for.
Multiple Targets
First on the hit list is on the deployment side. One of the strengths of ARA is the ability to deploy to any environment. The ARA system has to know about each environment in enough detail to enable deployment on it. It must know how to deploy servers, where to get OS, what needs to be added on to the OS, and how to get the application onto these systems. Increasingly, programmable network elements and security configuration fall into this category also. While tools such as Chef and Terraform can help in this regard, if you’re not already using them, they’ll have to be configured if not already, and then linked into your ARA tool. Understanding the path from here to there is critical to early success with ARA.
Databases
This is one of the more vexing problems. While most ARA tools offer the ability to configure databases and database connections, your datasets generally don’t hop around so easily. So if you’re testing and deploying on separate networks, you’ll need to make sure that the relevant tables are on those networks. This struggle impacts moves to the cloud, changes from a fully test network to production or any other change that requires the database server be accessible when it hasn’t been in the past. The work to solve these problems is pretty wide. In some cases, such as purely internal or purely cloud, merely routing from the relevant app instances to the database server will do it; but, in the case of across-the-internet changes, it will take a lot more work. Make certain you understand what challenges you will face before moving.
Tooling Sets
Much of the external needs of an application are baked into the app build process through tools such as NPM or Git. But those tools don’t cover everything necessary for the entire app ecosystem. Agents, per-tool databases, small tools used occasionally—make certain you have a list of what makes the app work, and make certain they’re configured to be built in by the ARA tool. This sounds obvious, but watching a team learn by trying to deploy and fix broken parts only to do it again is not only painful, it also leaves a “Did we get everything?” impression. I saw one app break on deploy because the team didn’t include curl. Yes, curl in the deployment. Test had it in the environment, production did not.
Get an inventory of both application development dependencies (libraries, etc.) and deployment dependencies (databases, reporting tools, agents for monitoring, etc.), and save yourself some pain.
Decrease Your Work by Asking Questions
ARA gives you a repeatable build/deploy process that can be used to target the environments you need while reducing manual scripting and steps. But before you throw in, sit with your vendor’s tech people and ask them to walk you through stumbling points, they likely know far more gotchas than I do, because it’s their job, and unless you got the new guy for an SE, have probably seen more. And getting ARA up and fully functional quickly allows you to focus on other DevOps needs, such as improving automated testing.