Est Reading Time: 3 min
Jul 13, 2020
In February of 2005, Jenkins first made its debut and quickly became the de facto continuous integration (CI) platform for developers. Fast forward a few years and SaaS platforms such as TravisCI and CircleCI started offering products that significantly reduced the effort required to manage project configurations and brought easy scalability to growing teams. The mass majority of development teams today have some centralized continuous integration platform as the foundation for their continuous deployment pipeline.
As software teams have scaled and the tools we use to develop have increased, our build environments have grown in complexity. Much of this complexity is shielded wonderfully by the platforms we use. Still, it can be seen in increased run times, expanding queues, and ballooning costs for containers and execution cycles. These problems are exacerbated by the increasing number of devices that teams are building software for. Mobile devices, edge gateways, connected cars, gaming systems, and server applications, to name a few. Each environment requiring unique setups and configurations that shift month by month as new technologies are released to help developers be more efficient within their domain.
Centralized platforms and developer operation teams struggle to keep up with these changes. While the CI platforms add new features, it’s impossible to add everything immediately in a cost-effective way. This leaves operation teams stuck waiting on the platforms to adopt new technologies or forces them back to managing sprawling Jenkins infrastructure. They have no alternative validation methodology that provides the same level of confidence that each audit and test has been executed and passed before deploying the changes to production environments.
Developers already need to have local environments set up to test what they’re developing; there’s no need for a centralized system that duplicates this environment. Developers already have powerful enough machines to run their code on; there’s no need for a centralized platform to build and test code. With docker and other virtualization technology, local environments can already be made to mimic production environments, and operation teams should already be assisting team members with making their local environments as production-esque as possible.
So if we already all have production-like environments locally, why do we need the centralized CI environment to run tests? Especially when we’re already running inspections, tests, and other audits before pushing code into the pipeline. This wastes CPU cycles, wastes resources, wastes time, creates additional security threats, increases policy complexity, creates single points of failure, and wastes people’s energy. The problem is we don’t have a way to certify what actions have been taken by developers in their local environments.
Someone could run the unit test suite multiple times locally, and the CI environment will still run it. Another developer might run one set of tests that certifies those tests pass, but the CI environment will still rerun those tests when they are pushed. As a DevOps engineer, how do you know what has already been done, and what needs to be completed prior to deploying it to production? You can’t trust someone’s verbal commitment that they ran all the tests. You can’t stand over everyone’s shoulder and run the tests for them. This is why we’ve historically relied on a centralized platform for a record of trust that everything that needs to be run against the code, is run.
What if there was a way to log and certify what was executed locally on a developer’s machine for a given version of code? This is what our distributed DevOps platform, Nunicorn, does. We define a protocol that allows you to log each action that is taken against a given variant of code and then use this information to query what has already happened to it.
We generate auditable records of validation actions taken by developers in their local environment and allow DevOps engineers to define what needs to be executed before pushing code.
This distributed approach lets organizations incentivize developers to run more checks on their code locally and reduce strain on their centralized CI platforms by having a percentage of the costs for executing actions go to the developer. This, in turn, helps shift more responsibility left, which also helps to promote learning by the developers of what types of checks they should be running to produce the best code.
By taking this approach, developers can use the existing environments they use locally to validate their code. DevOps engineers can focus on improving efficiencies in team culture and adopting new technologies into local development environments. And team members receive incentives for adopting the new processes. By decentralizing where audits are executed, we’re able to reduce the load on CI pipelines, increase build throughput, reduce or remove single points of failure, and create an audit trail of everything that has happened to facilitate a feature. The audit log, in turn, enables more accurate measurement of the four key DevOps measurables:
If you’d like to join the alpha, contact us today and let us know what solutions make up your DevOps toolchain.
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