Signed-off-by: Andrea Luzzardi <aluzzardi@gmail.com>
5.8 KiB
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Continuous Integration
Dagger is the perfect tool for CI workflows.
Benefits
- Develop and run your CI pipeline locally. No need to create a Pull Request to trigger CI, you can run the pipeline locally. Since dagger workflows are containerized, you can expect the same results no matter where the pipeline is executed.
- Write once, Run anywhere. The same pipeline 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 them across all your projects. Or with the world. Dagger ships with dozens of re-usable components
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.
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
// comifrom 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 thegolang
Docker image - lint task which executes
golangci-lint
inside the source artifact using thegolangci-lint
Docker image.
Before we can execute the configuration, we need to set up the Dagger workspace and environment.
# Initialize a dagger workspace 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):
$ 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 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.
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: "."
}
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
orgo
$ 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.