Strictly speaking, GDP is a derivative. It is based on poky and uses Yocto tools to “create” the Linux based platform, adding the different components developed by the GENIVI Alliance together with upstream software. For the defined purpose, the release centric model works fine, especially if you concentrate your effort is very specific areas of the software stack with a small number of dependencies on the other areas, and a limited number of contributions and environments where the system should work.
During this 2016, the GDP has grown significantly. We have more software, more contributors, more components and more target boards to take care of. Although the above model has not been not challenged yet, it was just a matter of time.
As I explained in two previous posts , the GDP is moving from a being a Demo to a Development Platform. Changing the mission means changing the goals and the target group, which implies the need to adjust the deliverable to meet the new expectations.
So, right after the 14th AMM, the Delivery Team decided to change the delivery model to better meet the new mission, providing developers the newest possible software with the an increasing quality threshold. At the same time, in order to increase the number of contributors, the GDP needs to provide a new solid platform every once in a while. That should be done trough a solid release.
What is a rolling delivery model?
Either for technical or business reasons, a year later it is time to upgrade. Our organization has to create a new Linux based system with newer upstream code and they have to integrate the patches from the previous release plus the updates and bug fixes developed for the coming release.
The delivery team now has to integrate 250 patches in the new base system, 150 of them coming from the previous release. One might think that the effort required to do this is 2.5 times the effort invested in the previous release. Maybe you think that the effort is not so high since some of the patches have been developed thinking about the new base system. There are many other considerations like this one that might affect the initial estimation. This example is obviously a simplification.
From the delivery perspective, the most popular way to tackle the problem though is reducing the release cycle, so the number of patches to forward-port in each release is smaller. The development time and the maintenance cycles are also smaller. The same applies to the complexity of the forward-porting activities. “Jumping” from one release to the next one is easier to do. Add automation of repetitive tasks to this recipe and you feel you have a win…. for some time.
The journey through the “road to hell” becomes more comfortable, but our organization is still getting burned, even in the case that our customers and ourselves can digest releasing frequently. We all know how expensive and stressful a release might become.
The most suitable option to achieve sustainability while scaling up the amount of software an organization can manage without releasing more often than your market can digest is to change your delivery model.
What is a rolling model?
So a rolling delivery model is a lot more than a continuous integration chain, although that is the key point.
Please have in mind that this is an oversimplification. This description doesn’t go into detail on other key aspects like maintenance cycles, how upstreamming affects the process, strategies towards updating the released products, etc.
A transformation process that takes an organization from a release centric model to a rolling one is about doing less and doing it faster, so less people can handle more software with less pain, allowing more people to concentrate in creating value, developing new and better software instead of just shipping it.
Back to GENIVI
The GDP will face a very interesting challenge since this model needs to be proven successful for a derivative. If we are able to move fast enough, it will come the time in which we will need to decide if GDP keeps being a derivative or it becomes upstream, that is, either GDP limits the delivery speed based on the Poky release cycle, or we work upstream with the Yocto project to increase our delivery speed.
If (almost) everything goes right, after adding a few needed services in GENIVI’s infrastructure and ensuring the updated software is in compliance with selected verification criteria, the same number of people will be able to manage and deliver more software. And once the new processes become more stable, automation will not just increase efficiency, it will boost the project by allowing GENIVI to achieve goals that only big organizations with large delivery teams can do. This is the kind of transformation that takes time to consolidate, but has a huge impact.
Based on my experience, I believe that if GENIVI is able to sustain this effort and keep a clear direction the next couple of years, the benefits of moving towards a rolling model will be noticeable even outside the industry.