Continuous delivery is the next phase to guarantee automating of all the necessary pre-deployment steps. We don’t ever want the lower lead time to result in increased re-work time do we? Instead, let’s aim for a smooth path where each integration complies with release criteria to update the new code on a live application or website.
Need For Speed
¨I want this code in live production faster to get my UX numbers soaring.¨
Don’t keep this phrase in your musty drawer of unmet goals. Continuous integration, delivery and deployment could be the differentiators that’ll make you ace the summit on that low to high web performer hike.
A software delivery lifecycle can take anything from weeks to months. Today’s top performers automate the build and deployment, environment provisioning and testing processes to open up the possibility of focusing on better products which yield higher returns.
The first component is Continuous Integration (CI). When developers merge their code to mainstream branch or working code base as often as possible you’ve got CI.
It’s basically triggering a build whenever a change gets committed to the source code. In other words, the developer fetches the code from the source code repository, compiles it and runs automated tests to create a build. This gives you full visibility of the project code and forges the way for earliest possible error detection.
The prime factor here is risk reduction. Risk is majorly reduced when creating a build after running automated test for every commit. With each integration, bugs and errors are easy to find and easy to fix–making the build every more simplified.
Let’s break down how drastically lowering your lead time will simplify life and enable you to cash in on the goods.
Work in small batches and get feedback sooner from users before spending long amounts of time and resources on each integration. Agile web development is also a good way to see profits sooner as the delivery lifecycle is based on a product in live production. This can be even be integrated into A/B testing to help you decide upon final implementation (more on that later).
The hypothesis-driven approach to product development reduces possible costs of building out whole features without knowing for sure what is preferred by the user.
Therefore, you see which features bring you ROI and measure the differences in performance for each. You can also lower the fixed costs that a release process involves by having a build/ test and deploy pipeline that relies on automation, thus bringing down costs associated with delivering incremental changes to software in the traditional release process.
So continuous delivery is hot. But to go the whole hog and stand out in this business you need to bump that up a notch toward continuous deployment. Say unit test, platform test, and staging integrations are all automated, meaning that you have effectively achieved continuous delivery but deploying to production is still a manual, painful, time consuming procedure. Well, what we’re going to look at next is when automation takes over this step too.
Deployments should be low-risk and performable on demand. The new functionalities do need to be tested and controlled though. A continuous delivery pipeline will apply patterns like blue-green deployments that significantly reduce any possibility of relative downtime.
Safety and QA are two of the staples that continuous deployment instrumentation looks after. An infrastructure that lets you back out new feature when a certain defect has been overlooked by the automated process is required to guarantee successful continuous deployment.
So to ensure that live users on an application have new code running for them error free, we need instrumentation to foresee that the automated integrations do not churn out a poor result. Such an external instrument should immediately interrupt the process and roll back any updates–meanwhile notifying the developer(s).
Fast regression detection made possible by automated tools can save individual web professionals or entire teams heaps of time allowing them to focus on usability and coding additional new features.
Simply cranking up the frequency of deployments to the max should by no means be considered a foolproof way to ensure quality. You have to ascertain you’re working with the right target and avoid common mistakes in agile practices
Here’s an enjoyable graphic representation of agile practices which is about as easy to navigate as the Tokyo subway map:
Simplify your life and improve your dev wellness
Continuous delivery and deployment improves the overall process by allowing teams or individuals to better understand which resources are going into the right features and which aren’t. The continuous approach is improving UX on a global scale, reducing levels of peer frustration and improving overall zen dev–yes, it’s a thing. Ommmm.
What is the most important sweet spot shared by all of us? Happy users. By automating software delivery cycles to allow developers to focus on building great products we are entering a new era of application and website development.
From Puppets 2016 State of DevOps report :
- High-performing IT organizations deploy 200 times more frequently than low performers, with 2,555 times faster lead times.
- They have 24 times faster recovery times and three times lower change failure rates.
- High-performing IT teams spend 50 percent less time remediating security issues.
- And they spend 22 percent less time on unplanned work and rework.
- Employees in high-performing teams were 2.2 times more likely to recommend their organization as a great place to work.
- Taking a lean approach to product development (for example, splitting work into small batches and implementing customer feedback) predicts higher IT performance and less deployment pain.
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