What Is CI/CD?
Continuous integration and continuous deployment (CI/CD) is a set of ideas,
processes, and capabilities that enables software changes to be delivered to users
in a timely, repeatable, and secure manner by introducing automation into
software development processes.
CI/CD Pipeline
From merging codes to testing builds, continuous integration (CI) validates all the
stages of the development process while optimizing the code release cycles through
automation capabilities. This, in turn, minimizes the probability of extended feature
development cycles and related issues like merge conflicts.
Continuous deployment (CD) focuses on setting up a bundled artifact into a
production environment in the fastest way possible. It automates the whole
distribution process, including deployment.
62% of the teams at an advanced stage of their DevOps evolution process adopted
CI/CD workflows in 2020. This number continues to rise due to the benefits and
scope offered by these processes. (StatistaOpens a new window , 2020)
Understanding the Process of CI/CD
Developers frequently commit codes to version control systems such as GitHub,
which start the CI process. The code quality can be determined by scanning or
analyzing it with static code analysis tools. The CI process creates the final build after
running automated tests, such as unit and integration tests.
Implementing CI is the first essential step for a developer to create high-quality code.
Several CI tools are available, including Harness CI, CircleCI, and Travis CI. Code
changes are deployed automatically into production in the final stage of the CI/CD
pipeline once the build has passed all tests.
The technical purpose of CI is to create a standardized and automated process for
developing, packaging, and testing programs. Most developer teams are inclined
toward code changes when the integration process achieves better cooperation and
software quality. On the other hand, the CD begins where CI ends to ensure that the
code changes are automatically pushed to the selected infrastructure environments.
CI/CD refers to a pipeline where you can submit new code on one end, let it get tested
through phases such as sourcing, building, staging, and production, and then finally
release it as a ready-for-production code.
In the CI/CD pipeline, each stage serves as a gate that verifies a specific feature of the
code. The premise is that, as the code travels through the pipeline, its quality will
improve since developers will check more aspects of it. Early-stage problems prevent
the code from advancing through the channel. Results of these tests are promptly
communicated. If the software fails a stage, all subsequent builds and releases are
halted.
These steps are only recommendations and can be changed based on the
organization’s requirements. You can also repeat the steps for testing, security,
performance, and other reasons. Also, one can make changes at different levels based
on a particular project.
See More: What Is DevOps? Definition, Goals, Methodology, and Best Practices
Top 8 Benefits of CI/CD
Companies attempt to deploy features as quickly as possible to stay competitive in the
market. A seamless CI/CD pipeline is the perfect platform for such short release
cycles. The pipeline comprises several DevOps automation tools and frameworks that
assist developers, testers, operations teams, and other project participants in delivering
software to end-users.
Benefits of CI/CD
This allows the teams to be more agile while also improving the overall efficiency of
the software delivery process. The groundwork for creating a pipeline might take a
long time and may need a high learning curve, but the advantages far outweigh the
time, expense, and effort required.
Let’s look at the top advantages of installing a CI/CD pipeline to understand why
many companies have switched.
1. Higher efficiency
Increased productivity is one of the leading advantages of a CI/CD pipeline. You
should automate your process if you have a review process that includes deploying
code to development, testing, and production environments and entering multiple
commands across several domains. This creates the need for a CI/CD framework.
2. Reduced risk of defects
Finding and resolving defects late in the development process is costly and time-
consuming. This is particularly true when problems arise with features already
released to production.
You can test and deploy code more frequently using a CI/CD pipeline, giving QA
engineers the power to identify and fix errors as soon as they occur. This way, you’re
effectively mitigating risks in real-time.
3. Faster product delivery
With a smooth CI/CD workflow, multiple daily releases can become a reality. Teams
can automatically build, test, and deliver features with minimal manual intervention.
Docker, Kubernetes, and Travis CI are some of the tools and frameworks that can be
used to accomplish this.
CD enables your team to provide customers with frequent and timely updates. When
CI/CD is used, the entire team’s efficiency increases, including the release of new feat
ures and fixes to problems. Businesses can address
market shifts, security challenges, consumer needs, and financial pressures faster.
If a new security feature is required, your team can
use CI/CD and automated testing to introduce the fix to production systems faster and
with higher assurance. What used to take weeks or months to finish
can now be completed in days or even hours.
4. Log generation
Observability is pivotal for DevOps. If something isn’t right, you need to figure out
why. You’ll need a way to track the system’s performance over time to determine
essential performance indicators. Observability is a technical tool that aids in this
endeavor.
Logging information plays a vital role in observability. Logs provide a large volume
of information to decipher what’s happening beneath the UI and study program
behavior. A CI/CD pipeline generates a lot of logging data at every level of
the software development process.
5. Quick rollback if required
One of the most exclusive benefits of a CI/CD pipeline is that it leads to the quick and
easy rollback of code changes if there are any issues in the production environment
after a release. If any new code change breaks a feature or general application, you
can revert to its previous stable version right away. You can deploy the most recent
successful build instantly to avoid production interruptions.
6. Better planning
Organizational designs must be adaptable to changing economic conditions.
However, it’s difficult for development and testing teams to adapt to rapid changes in
dynamic business conditions. A CI/CD
pipeline enables organizations to accomplish this by ensuring that they have a well–
organized surplus of items and a continuous line of communication with clients.
7. Efficient testing & monitoring
Testing entails automating each test case and experimenting with the program. Any
cycle that needs to be repeated over time should be automated, and there are enough
innovations available to achieve this goal. Manual testing measures must be evaluated
for possible automation outcomes, and in the vast majority of circumstances, there
will be ways to automate the equivalent.
The code delivery cycle should create the possibility of running the test suite on each
product assembly built without client intervention, resulting in a defined goal of
providing quality delivery quickly.
Using continuous monitoring, Ops teams can oversee and ensure that the application
is running as expected and that the environment is stable. They must ensure that the
applications perform optimally.
This involves the deployment of software that can monitor application health and
issues. It may also be necessary for the Ops team to collaborate with the development
team to build self-observing or investigation gathering capabilities directly into the
applications. Developers have to consider checking the product from start to finish
continually.
8. Cost-effectiveness
The CI/CD pipeline takes a different approach to software delivery. It can be
compared to an assembling unit’s delivery pipeline. In any business situation, time
and assets are essential. Firms are expected to respond to client demands quickly and
effectively with such requirements.
With automated testing hooks at every stage, developers can fix issues early and avoid
critical issues in the production environment. With the implementation of a CI/CD
pipeline, code quality improves drastically, which, in turn, improves the overall ROI.
5. Measuring & Monitoring CI/CD Performance
Continuous improvement is one of the cornerstones of the DevOps philosophy.
It extends to every aspect of software development, from the product or service that you’re
building to your organization’s culture and processes.
Continuous improvement involves collecting and analyzing feedback on what you’ve built or
how you’re working in order to understand what is performing well and what could be improved.
Having applied those insights, you collect further feedback to see if the changes you made
moved the needle in the right direction, and then continue to adjust as needed.
A CI/CD pipeline plays a central role in enabling continuous improvement of your software. By
shortening the time from development to deployment, you can release changes to users more
frequently and so get feedback from use in production, which informs what you prioritize next.
Likewise, the rapid feedback provided from each stage of automated testing makes it easier to
address bugs and helps you to maintain the quality of your software.
But continuous improvement does not stop there. By applying the same techniques to the CI/CD
pipeline itself, you can refine the process of building, testing and releasing your software, which
amplifies the feedback loops you use to improve your product.
Understanding pipeline metrics
“You can’t manage what you don’t measure”, as the saying goes.
Metrics are an essential tool for improving system performance – they help to identify where you
can add value and offer a baseline against which to measure the impact of any improvements you
make.
Performance in CI/CD encompasses both speed and quality; there should not be a trade-off
between deploying changes fast and delivering a robust and reliable product – a high performing
CI/CD pipeline will allow you to deliver on both.
By measuring and monitoring the speed of activities, the quality of your software, and the extent
to which you’re using automation, you can identify areas for improvement and then confirm
whether the changes you’ve made have had a positive effect.
Top-level performance DevOps metrics
The following four metrics have been identified by DevOps Research and Assessment (DORA)
as high-level metrics that provide an accurate indication of how well an organization is
performing in the context of software development.
You can learn more about the research that informed these choices in the book Accelerate.
Lead time
Although lead time (also known as time to delivery or time to market) can be measured as the
time from when a feature is first raised until it is released to users, the time involved in ideation,
user research and prototyping tends to be highly variable.
For this reason, the approach taken by DORA is to measure the time from code being committed
to deployment, which allows you to focus just on the stages within the scope of your CI/CD
pipeline.
A long lead time means that you’re not getting code changes in front of users regularly and
therefore not benefitting from feedback to refine what you’re building. That can be due to several
factors.
A release pipeline that involves manual steps, such as large numbers of manual tests, risk
assessments or change review boards, can add days or weeks to the process, undermining the
advantages of frequent releases.
While investing in automated testing will address the former, the latter requires engagement with
stakeholders to understand how their needs can be met more efficiently. Alternatively, if the
automated steps are slow or unreliable, then build duration metrics can be used to identify the
stages taking the most time.
Deployment frequency
Deployment frequency records the number of times you use your CI/CD pipeline to deploy to
production. Deployment frequency was selected by DORA as a proxy for batch size, as a high
deployment frequency implies fewer changes per deployment.
Deploying a small number of changes frequently lowers the risk associated with releasing
(because there are fewer variables that can combine into unexpected results), and provides
feedback sooner.
A low deployment frequency can signify that the pipeline is not being fed with regular commits,
perhaps because tasks are not being broken down, or it can be the result of batching changes up
into larger releases.
When changes need to be batched up for business reasons (for example, due to user
expectations), measuring the frequency of deployments to staging sites instead will allow you to
monitor batch size and assess whether you’re reaping the benefits of working in small
increments.
Change failure rate
Change failure rate refers to the proportion of changes deployed to production, which result in a
failure, such as an outage or bug that requires either a rollback or hotfix. The advantage of this
metric is that it puts failed deployments in the context of the volume of changes made.
A low change failure rate should give you confidence in your pipeline; it indicates that the earlier
stages of the pipeline are doing their job and catching most defects before your code is deployed
to production.
Mean time to recovery
Mean time to recovery or resolution (MTTR) measures the time it takes to address a production
failure. MTTR recognizes that, in a complex system with many variables, some failures in
production are inevitable. Rather than aiming for perfection (and therefore slowing down
releases and forfeiting the benefits of frequent releases), it’s more important to respond to issues
quickly.
Keeping your MTTR low requires both proactive monitoring of your system in production to
alert you to problems as they emerge, and the ability to either roll back changes or deploy a fix
rapidly via the pipeline.
A related metric, mean time to detection (MTTD), measures the time between a change being
deployed and your monitoring system detecting an issue introduced by that change. By
comparing MTTD and build duration, you can determine if either area would benefit from some
investment to reduce your MTTR.
CI & Operational metrics
In addition to these high-level measures, there is a range of operational metrics that you can use
to better understand how your pipeline is performing and identify areas where you might be able
to improve your process.
Code coverage
In a CI/CD pipeline, automated tests should provide the majority of your test coverage, freeing
up your QA engineers to focus on exploratory testing and defining new test cases. The first layer
of automated tests performed should be unit tests, as there are the quickest to run and provide the
most immediate feedback.
Code coverage is a metric provided by most CI servers that calculates the proportion of your
code covered by unit tests. It’s worth monitoring this metric to ensure that you’re maintaining
adequate test coverage as you write more code. If your code coverage is trending downwards
over time, it’s time to invest some effort in this first line of feedback.
Build duration
Build duration or build time measures the time taken to complete the various stages of the
automated pipeline. Looking at the time spent at each stage of the process is useful for spotting
pain points or bottlenecks that might be slowing down the overall time it takes to get feedback
from tests or deploy to live.
Test pass rate
Test pass rate is the percentage of test cases that passed successfully for a given build. As long as
you have a reasonable level of automated tests, it provides a good indication of each build’s
quality. You can use this metric to understand how often code changes are resulting in failed
tests.
While catching failures with automated tests is preferable to relying on manual tests or
discovering issues in production, if a particular set of automated tests are regularly failing, it
might be worth looking at the root cause of those failures.
Time to fix tests
Time to fix tests is the time between a build reporting a failed test and the same test passing on a
subsequent build. This metric gives you an indication of how quickly you’re able to respond to
issues identified in the pipeline.
A low resolution time shows you’re using your pipeline to best effect; by dealing with issues as
soon as they are found, you can work more efficiently (as the changes are still fresh in your
mind), and you avoid building more functionality on top of unstable code.
Failed deployments
Failed deployments that result in unintended downtime, require the deployment to be rolled back
or require a fix to be released urgently. The count of failed deployments is used to calculate the
change failure rate (discussed above).
Monitoring the proportion of failures out of the total number of deployments helps measure your
performance against SLAs.
However, bear in mind that a target of zero (or very few) failed deployments is not necessarily
realistic, and can instead encourage teams to prioritize certainty. Doing so results in longer lead
times and larger deployments as changes are batched together, which actually increases the
likelihood of failures in production (as there are more variables) and makes them harder to fix (as
there are more changes to wade through).
Defect count
Unlike failures, a defect count refers to the number of open tickets in your backlog classified as
bugs. It can be further broken down by issues found in testing or staging and issues found in
production.
Like code coverage, monitoring the number of defects is useful for alerting you to a general
upward trend, which can indicate that bugs are getting out of hand. Keep in mind, however, that
making this metric a target can lead to your team focusing more on classifying tickets than on
fixing them.
Deployment size
As a corollary to deployment frequency (see above), deployment size – as measured by the
number of story points included in a build or release – can be used to monitor batch size within a
particular team.
Keeping deployments small shows that your team is committing regularly, with all the benefits
that entails. However, as story estimates are not comparable across development teams, this
metric should not be used to measure overall deployment size.
Conclusion
Monitoring these metrics allows you to better understand how well your CI/CD pipeline
performs and whether you are on an upward or downward trend.
You can use metrics to identify areas of your process that would merit further attention. Once
you’ve made a change, it’s good practice to keep monitoring the relevant metrics to verify
whether they had the intended effect.
However, while metrics can provide useful indicators of performance, it’s important to read the
numbers in context and to consider which behaviors might be incentivized by focusing on a
particular metric. Bear in mind that the goal is not the numbers themselves, but keeping your
pipeline fast and reliable so that you can keep delivering value to users.
