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dagger/docs/use-cases/1012-ci.md

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---
slug: /1012/ci
---
# Make your CI workflow portable
## Problems with existing CIs
- The CI code is sticky to the underlying CI infrastructure.
- It's hard to migrate the CI from a runner to another.
- The CI syntax is different with each CI runner.
- Most CI workflows are represented using YAML.
Implement the CI workflow using dagger solves all of those problems.
## Benefits of defining your CI workflow in Dagger
- **Your CI only runs dagger.** It moves all the CI logic from the non-portable
CI syntax, to a dagger plan, that runs the same way everywhere.
- **Develop and run your CI workflow locally.** No need to create a Pull Request
to trigger CI, you can run the workflow locally. Since dagger workflows
are containerized, you can expect the same results no matter where the workflow is executed.
- **Write once, Run anywhere.** The same workflow can run in any CI, goodbye
vendor lock in.
- **Blazing Fast**: Dagger will automatically build an optimized execution
graph, completing the job as fast as possible. Spend less time staring at CI to
complete and reduce costs.
- **Effortless Cache Optimizations**. Dagger will automatically
re-use cached execution results if no changes are detected. Made a change to the
frontend? The backend won't be built again.
- **Composable & Reusable**. Define re-usable steps and [share](../learn/1010-dev-cue-package.md) them across all
your projects. Or with the world. Dagger
ships with [dozens of re-usable components](../reference/README.md)
## Example
This example illustrates how to use Dagger to test and lint a Go project. The
use of Go is irrelevant and the example can be easily adapted to other languages.
From the project repository, create a file named `ci/main.cue` and add the
following configuration to it.
```cue title="ci/main.cue"
package main
import (
"alpha.dagger.io/dagger"
"alpha.dagger.io/os"
"alpha.dagger.io/docker"
)
// Source directory of the repository. We'll connect this from the CLI using `dagger input`
source: dagger.#Artifact
// Here we define a test phase.
// We're using `os.#Container`, a built-in package that will spawn a container
// We're also using `docker.#Pull` to execute the container from a Docker image
// coming from a registry.
test: os.#Container & {
image: docker.#Pull & {
from: "golang:1.16-alpine"
}
mount: "/app": from: source
command: "go test -v ./..."
dir: "/app"
}
// Likewise, here we define a lint phase.
lint: os.#Container & {
image: docker.#Pull & {
from: "golangci/golangci-lint:v1.39.0"
}
mount: "/app": from: source
command: "golangci-lint run -v"
dir: "/app"
}
```
The configuration above defines:
- **source** code of the project. More on this later.
- **test** _task_ which executes `go test` inside the source artifact
using the `golang` Docker image
- **lint** _task_ which executes `golangci-lint` inside the source artifact
using the `golangci-lint` Docker image.
Before we can execute the configuration, we need to set up the Dagger project and environment.
```shell
# Initialize a dagger project at the root of your project
dagger init
# Create a CI environment using the CUE files in the `./ci` directory
dagger new ci -p ./ci
# Link the `source` artifact defined in the configuration with the project
# source code.
dagger input dir source .
```
Next, bring up the CI environment (e.g. execute the CI configuration):
```shell
$ dagger up
# ...
7:15PM INF test | computing environment=ci
7:15PM INF lint | computing environment=ci
# ...
```
Since `test` and `lint` do not depend on each other, they are executed in
parallel.
Running `dagger up` a second time will return almost immediately: since no
changes were made to `source`, Dagger will re-use the cached results for both `test` nor `lint`.
## Integrating with CI
All it takes to execute a Dagger workflow in CI is to run `dagger up`.
We provide a [GitHub Actions](../learn/1009-github-actions.md) to make
integration with GitHub easier.
## Monorepos
Dagger workflows scale really well with CI complexity.
The following example illustrates how to test two different projects in the same
repository: a _Node_ frontend (located in _./frontend_) along with a _Go_ backend (located in _./backend_).
From the project repository, update the file named `ci/main.cue` with the
following configuration.
```cue title="ci/main.cue"
package main
import (
"alpha.dagger.io/dagger"
"alpha.dagger.io/os"
"alpha.dagger.io/docker"
)
// Source directory of the repository. We'll connect this from the CLI using `dagger input`
source: dagger.#Artifact
backend: {
// We use `os.#Dir` to grab a sub-directory of `source`
code: os.#Dir & {
from: source
path: "./backend"
}
test: os.#Container & {
image: docker.#Pull & {
from: "golang:1.16-alpine"
}
mount: "/app": from: code
command: "go test -v ./..."
dir: "/app"
}
}
frontend: {
// We use `os.#Dir` to grab a sub-directory of `source`
code: os.#Dir & {
from: source
path: "./frontend"
}
test: os.#Container & {
image: docker.#Pull & {
from: "node:16-alpine"
}
mount: "/app": from: code
command: """
# Install Dependencies
yarn
# Run the test script
yarn test
"""
dir: "/app"
}
}
```
:::tip
Larger configurations can be split into multiple files, for example `backend.cue` and `frontend.cue`
:::
The configuration above defines a _frontend_ and _backend_ structure, each
containing:
- A **code** directory, defined as a subdirectory of **source**
- A language specific **test** task using either `yarn` or `go`
```shell
$ dagger up
7:15PM INF frontend.test | computing environment=ci
7:15PM INF backend.test | computing environment=ci
7:15PM INF frontend.test | #8 0.370 yarn install v1.22.5 environment=ci
7:15PM INF frontend.test | #8 0.689 [1/4] Resolving packages... environment=ci
7:15PM INF frontend.test | #8 1.626 [2/4] Fetching packages... environment=ci
...
```
`frontend.test` and `backend.test` are running in parallel since there are no
dependencies between each other.
If you were to make changes to the _./frontend_ directory, only
`frontend.test` will be executed.