Large Scale Continuous Integration

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Summary:

The main goal of software is to automate and simplify what would otherwise be accomplished using a manual process. This gives the users of the software leverage to do more with less. Instead of balancing our checkbook by hand, we can use Quicken to do it faster and more accurately. Instead of maintaining the records of millions of people's financial transactions with paper and pencil, banks use mainframes.

When you are creating new software, what do you think about? Don't you think about how it will scale to meet your customers' needs as they grow with high availability? Even if you don't achieve that on the first try, aren't you still thinking about it and striving to achieve it? You know that to do it, you will need to make the right technology and architectural choices. Over time, you may need to change some of those choices to keep pace with competitors. Even if your current needs are modest, software development architecture has evolved technologies and patterns to allow software to scale from a single user to hundreds or even thousands of users on multiple platforms at multiple locations with 99.999% uptime.

On the other hand, as an industry, we don't seem to be very good at scaling up the process of software development itself. Even when what needs to be built is primarily made up of well-understood tasks and requires very little discovery, it seems that when the size of the effort goes beyond 5-10 people, things start to break down pretty rapidly. Adding more people usually doesn't scale in the same way that adding more hardware does.

I think this stems from the belief that software automates a well-defined problem but that the process of software development is a creative endeavor and cannot benefit from the same kind of thinking that goes into designing software. However, after spending many years involved in thinking about how to improve the process of software development, experience has convinced me that a great deal of the process of developing software can be treated as infrastructure. This infrastructure supports the creative parts of the software development process, but can be clearly delineated from it.

By thinking about the infrastructure of your process in the same way as you would think about any manual process that requires automation, you can leverage your skills as a developer and apply them in a new way. The process of developing software is, in effect, an algorithm implemented with various technologies. You can think of your team, the technologies you use, and your development methodology as software.

What technologies are you using? What is the architecture of your organization? Will it scale from its current size to double its size? Will it scale seamlessly to include new teams in new locations? What will happen if you acquire a company?
When creating software, you want to design it so that it is flexible and adapts to new circumstances. The same should be true for your development organization. In this paper I will apply this way of thinking to the problem of scaling Continuous Integration to development efforts of more than 10 people.

Integration
How frequently have you merged your code with changes from the mainline, only to find that the result doesn't build, or it builds but it doesn't work? Monthly? Weekly? Daily? Hourly? Or worse, how often have you made changes that broke the build, requiring you to quickly correct the problem while getting flames from your team members?
If everybody in development is making changes against the mainline, introducing a bad change affects everybody until it is detected and corrected. Waiting for someone to fix a change that is impacting everybody is bad enough when the change was committed locally, but it becomes severe when the committer won't even be awake for another eight hours.

Big-Bang Integration
Integration is tough enough when you are just integrating your work with the work of other folks in your small team, or the whole effort is being done

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