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CI/CD is a set of practices for integrating code changes often, checking each change automatically, and keeping software ready to release. Continuous integration (CI) means developers merge small changes into a shared code line and receive fast build and test feedback. Continuous delivery keeps software in a state where it can be released on demand. Continuous deployment goes one step further and automatically releases qualifying changes to production. The practices shorten feedback loops and can make releases safer and more repeatable, but only when testing, security checks and production monitoring are sound.
The abbreviation “CD” is used for both continuous delivery and continuous deployment, so this article spells out the full term whenever the difference matters.
Three practices with three different promises
CI/CD is usually taught as one idea, but it contains three separate practices. Each one answers a different question: how often code is integrated, whether software can be released at any time, and whether every qualifying change actually goes live.
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Continuous integration
In continuous integration, developers regularly merge their work into the main code line, ideally in small increments. Each merge triggers an automated build and a set of quick checks, so a regression is found while the change is still small and easy to trace. DORA, the DevOps Research and Assessment program, describes rapid feedback as the core of CI and calls it a key component of continuous delivery. See DORA, “Capabilities: Continuous integration”.
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Continuous delivery
Continuous delivery means the software stays deployable throughout its lifecycle, so the team can release it whenever it chooses. DORA defines the practice this way:
“Continuous delivery is the ability to release changes of all kinds on demand quickly, safely, and sustainably.”
— DORA, “Capabilities: Continuous delivery”
The key point is that release is a decision, not an automatic event. A team practising continuous delivery may still require a human approval, a change window or a business sign-off before a change reaches customers.
Continuous deployment
Continuous deployment means every change that passes automated validation is deployed to production as soon as possible, without a manual release step. DORA notes that this approach is not suitable or necessary for every kind of software, and that it is not a prerequisite for continuous delivery. It is a separate choice, not a more advanced version of the same thing.
Continuous delivery and continuous deployment at a glance
DORA states that the two terms are commonly conflated but are separate practices. The table below sets out the practical differences.
| Question | Continuous delivery | Continuous deployment |
|---|---|---|
| What reaches production? | Changes the team chooses to release | Every qualifying change that passes automated validation |
| What triggers the production release? | A deliberate decision, on demand | The pipeline itself |
| Is a human release step required? | Can be, depending on team or policy | No, by definition of the practice |
| Is it suitable for all software? | Applies across many kinds of software, including infrastructure, databases, firmware, mobile apps and regulated contexts, with controls | Not suitable or necessary for every kind of software |
| Must the other practice be in place first? | Not required to adopt continuous deployment | Not a prerequisite for continuous delivery |
What happens in a CI/CD pipeline
A pipeline is a sequence of automated checks and release steps. The exact stages depend on the product, the risk and the organisation, but a typical flow looks like this:
- A developer commits a small change or opens a pull request.
- Automation builds the software and runs fast checks such as linting, unit tests and security checks. GitHub describes continuous integration in this way, with workflows that run automatically in the repository. See GitHub Docs, “Continuous integration”.
- Changes that pass move on to broader integration, acceptance or environment checks. These stages are specific to each team.
- In a continuous delivery setup, a release-ready change waits until someone decides to deploy it. In a continuous deployment setup, qualifying changes are released to production automatically.
- The team observes production behaviour and uses incidents and customer feedback to improve both the system and the pipeline.
A pipeline does not mean every test runs on every commit. Test depth and release controls are choices shaped by risk. A green build shows that the checks that ran passed; it does not prove the software is correct.
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Why teams adopt CI/CD
Smaller changes are easier to fix
DORA says continuous integration creates rapid feedback loops and encourages small batches, with the aim of reducing the cost and pain of integrating changes. GitHub makes a similar point: frequent updates help teams find errors earlier and reduce the amount of code a developer has to debug.
Release capability can reduce risk
DORA describes continuous delivery as a way to reduce software risk. Its research reports that the capability is associated with better delivery performance and availability, and with improvements in quality, less deployment pain and lower burnout. These are associations observed across teams, not guarantees that a specific team will see the same results.
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Automated checks support safer change
CI/CD is not simply a faster way to push code. Automated testing, security checks and observability are what make frequent change manageable. DORA stresses that these technical practices matter most in regulated and safety-critical domains.
Where CI/CD applies
CI/CD is often associated with web services, but DORA states that continuous delivery applies to infrastructure, databases, firmware, mobile apps and regulated contexts. In those settings the controls, approvals and evidence requirements remain important, and they shape how the pipeline is designed. Continuous deployment is the option most likely to be unsuitable where a release needs formal sign-off or cannot be reversed easily.
How to measure whether it is working
GitLab’s documentation describes four DORA metrics. Two measure delivery speed and two measure stability and recovery. Read them together, and in the context of the team’s workflow.
| Metric | What it measures | Type |
|---|---|---|
| Deployment frequency | How often successful deployments reach production | Speed |
| Lead time for changes | How long changes take to reach production | Speed |
| Change failure rate | How often deployments cause production failures | Stability |
| Time to restore service | How quickly service is recovered after a failure | Recovery |
Source: GitLab Docs, “DevOps Research and Assessment (DORA) metrics”.
A rise in deployment frequency alone does not show that a team is delivering more value. If frequency climbs while change failure rate and recovery time worsen, the pipeline is moving changes faster without making them safer. The official DORA and platform documentation define these measures but do not provide a universal target, so compare your own numbers over time rather than against an external benchmark.
Quick Recap
Common misreadings
- “CD means every change goes straight to production.” That is continuous deployment. Continuous delivery only requires that software be ready to release.
- “A passing build proves the software works.” A build and its checks show only what was tested.
- “Adopting a tool adopts the practice.” GitHub Actions and GitLab CI/CD automate checks and can report outcomes, but useful tests, clear ownership and operational feedback still have to be built by the team.
- “Faster releases are always better.” Speed is only meaningful alongside stability and recovery measures.
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