Do you want your engineering team to deliver bug-free code at high velocity? A fast and reliable CI/CD pipeline is crucial for doing that sustainably over time.
What is a CI/CD pipeline?
A CI/CD pipeline helps you automate steps in your software delivery process, such as initiating code builds, running automated tests, and deploying to a staging or production environment. Automated pipelines remove manual errors, provide standardized development feedback loops and enable fast product iterations.
What do CI and CD mean?
CI, short for Continuous Integration, is a software development practice in which all developers merge code changes in a central repository multiple times a day. CD stands for Continuous Delivery, which on top of Continuous Integration adds the practice of automating the entire software release process.
With CI, each change in code triggers an automated build-and-test sequence for the given project, providing feedback to the developer(s) who made the change. The entire CI feedback loop should run in less than 10 minutes.
Continuous Delivery includes infrastructure provisioning and deployment, which may be manual and consist of multiple stages. What’s important is that all these processes are fully automated, with each run fully logged and visible to the entire team.
Learn more here: CI/CD: Continuous Integration & Delivery Explained
Elements of a CI/CD pipeline
A CI/CD pipeline may sound like overhead but it really isn’t. It’s essentially a runnable specification of the steps that need to be performed in order to deliver a new version of a software product. In the absence of an automated pipeline, engineers would still need to perform these steps manually, and hence far less productively.
Most software releases go through a couple of typical stages:
Failure in each stage typically triggers a notification—via email, Slack, etc.—to let the responsible developers know about the cause. Otherwise notifications are usually configured to be sent to the whole team after each successful deploy to production.
In most cases a pipeline run is triggered by a source code repository. A change in code triggers a notification to the CI/CD tool, which runs the corresponding pipeline. Other common triggers include automatically scheduled or user-initiated workflows, as well as results of other pipelines.
Regardless of the language, cloud-native software is typically deployed with Docker, in which case this stage of the CI/CD pipeline builds the Docker containers.
Failure to pass the build stage is an indicator of a fundamental problem in the configuration of our project and it’s best to address it immediately.
In this phase we run automated tests to validate the correctness of our code and the behavior of our product. The test stage acts as a safety net that prevents easily reproducible bugs from reaching the end users.
The responsibility of writing tests falls on the developers, and is best done while we write new code in the process of test- or behavior-driven development.
Depending on the size and complexity of the project, this phase can last from seconds to hours. Many large-scale projects run tests in multiple stages, starting with smoke tests that perform quick sanity checks to end-to-end integration tests that test the entire system from the user’s point of view. A large test suite is typically parallelized to reduce run time.
Failure during the test stage exposes problems in code that developers didn’t foresee when writing the code. It’s essential for this stage to produce feedback to developers quickly, while the problem space is still fresh in their minds and they can maintain the state of flow.
Once we have a built a runnable instance of our code that has passed all predefined tests, we’re ready to deploy it. There are usually multiple deploy environments, for example a “beta” or “staging” environment which is used internally by the product team, and a “production” environment for end users.
Teams that have embraced the Agile model of development—which is guided by tests and real-time monitoring—usually deploy work-in-progress manually to a staging environment for additional manual testing and review, and automatically deploy approved changes from the master branch to production.
Examples of CI/CD pipelines
A pipeline can start very simple. Here’s an example of a pipeline for a Go project which compiles the code, checks code style and runs automated tests in two parallel jobs:
Here’s a more complex example of a pipeline that builds, tests and deploys a microservice to a Kubernetes cluster:
You can find more examples of CI/CD pipelines in Semaphore documentation.
Additional benefits of pipelines
Having a CI/CD pipeline has more positive effects than simply making what was previously done a little bit more efficient:
- Developers can stay focused on writing code and monitoring the behavior of the system in production.
- QA and product stakeholders have easy access to the latest, or any, version of the system.
- Product updates are not stressful.
- Logs of all code changes, test and deployments are available for inspection at any time.
- Rolling back to a previous version in the event of a problem is a routine push-button action.
- A fast feedback loop helps build an organizational culture of learning and responsibility.
What makes a good pipeline?
A good CI/CD pipeline is fast, reliable and accurate.
Speed manifests itself in a number of ways:
- How quickly do we get feedback on the correctness of our work? If it’s longer than the time it takes to get a cup of coffee, pushing code to CI is the equivalent of asking a developer to join a meeting in the middle of solving a problem. Developers will work less effectively due to inevitable context switching.
- How long does it take us to build, test and deploy a simple code commit? For example, a total time of one hour for CI and deployment means that the entire engineering team has a hard limit of up to seven deploys for the whole day. This causes developers to opt for less frequent and more risky deployments, instead of the rapid change that businesses today need.
- Do our CI/CD pipelines scale to meet development demands in real time? Traditionally CI/CD pipelines have limited capacity, meaning that only a certain number of pipelines can run at a given time. As as a result, resources sit idle most of the time, while at busy periods of the day developers wait in a queue for CI/CD to become available. One of the biggest changes in the recently released Semaphore 2.0 is auto-scaling and a pay-as-you-go pricing model, a “serverless” operating principle which supports developer productivity.
- How quickly can we set up a new pipeline? Difficulty with scaling CI/CD infrastructure or reusing existing configuration creates friction, which stifles development. Today’s cloud infrastructure is best utilized by writing software as a composition of microservices, which calls for frequent initiation of new CI/CD pipelines. This is solved by having a CI/CD tool that is programmable and fits in the existing development workflows, and storing all CI/CD configuration as code that can be reviewed, versioned and restored.
More info here: Why cloud-native success depends on high velocity CI/CD.
A reliable pipeline always produces the same output for a given input, and with no oscillations in runtime. Intermittent failures cause intense frustration among developers.
Operating and scaling CI/CD infrastructure that provides on-demand, clean, identical and isolated resources for a growing team is a complex job. What seems to work well for one project or a few developers usually breaks down when the team and the number of projects grow, or the technology stack changes. When we hear from new users, unreliable CI/CD is one of top reasons why they move to Semaphore, often from a self-hosted solution.
Any degree of automation is a positive change. However, the job is not fully complete until the CI/CD pipeline accurately runs and visualizes the entire software delivery process. This requires the use of a CI/CD tool that can model both simple and if needed, complex workflows, so that manual error in repetitive tasks is all but impossible.
For example, it’s not uncommon to have the CI phase fully automated, but to leave out deployment as a manual operation to be performed by often a single person on the team. If a CI/CD tool can model the deployment workflow needed, for example with use of secrets and multi-stage promotions, this bottleneck can be removed.
Good things to do
When the master is broken, drop what you’re doing and fix it. Maintain a “no broken windows” policy on the pipeline.
Run fast and fundamental tests first. If you have a large test suite, it’s common practice to parallelize it to reduce the amount of time it takes to run it. However, it doesn’t make sense to run all the time-consuming UI tests if some essential unit or code quality tests have failed. Instead, it’s best to set up a pipeline with multiple stages in which fast and fundamental tests—such as security scanning and unit tests—run first, and only once they pass does the pipeline move on to integration or API tests, and finally UI tests.
Always use exactly the same environment. A CI/CD pipeline can’t be reliable if a pipeline run modifies the environment in which the next pipeline will run. It’s best that each workflow run starts from exactly the same, clean and isolated environment.
Build in quality checking. For example, there are open source tools that provide static code analysis for every major programming language, covering everything from code style to security scanning. Run these tools within your CI/CD pipeline and free up brainpower for creative problem-solving.
Include pull requests. There’s no reason why a CI/CD pipeline should be limited to one or a few branches. By running the standard set of tests against every branch and corresponding pull request, contributors can identify issues before engaging in peer review, or worse, before the point of integration with the master branch. The outcome of this practice is that merging any pull request becomes a non-event.
Peer-review each pull request. No CI/CD pipeline can fully replace the need to review new code. There may be times when the change is indeed so trivial that peer review is a waste of time; however, it’s best to set the norm that every pull request needs another pair of eyes, and make exceptions only when it makes sense, rather than vice versa. Peer code review is a key element in building a strong, egoless engineering culture of collaborative problem solving.
Ready to implement a CI/CD pipeline?
Semaphore is the fastest cloud-based CI/CD service that natively supports Docker and major programming languages, with autoscaling and a pay-as-you-go pricing model. Creating a new pipeline involves just a few simple steps:
- Create a free Semaphore account.
- Select a Git repository that you have access to.
- Commit and push an example pipeline.
- Take the guided tour and learn from many tutorials and example projects in Semaphore documentation.
You can also watch one of the Semaphore Uncut videos which demonstrate the use of Semaphore hands-on.