FAQ
General
What is the Dagger Platform?
We're building the devops operating system, an integrated platform to orchestrate the delivery of applications to the cloud from start to finish. The Dagger Platform includes the Dagger Engine, Dagger Cloud, and the Dagger SDKs. Soon we will deliver the capability to publish and leverage prebuilt modules to further accelerate the adoption of Dagger across an organization’s pipelines.
How do I install Dagger?
Refer to the documentation for information on how to install the Dagger CLI.
How do I update Dagger?
To install a Dagger CLI that matches your OS & architecture, run the following:
curl -fsSL https://dl.dagger.io/dagger/install.sh | BIN_DIR=$HOME/.local/bin sh
This installs dagger
in $HOME/.local/bin
:
Homebrew users can alternatively use the following commands:
brew update
brew upgrade dagger
What compatibility is there between the Dagger Engine, Dagger SDKs and Dagger CLI versions?
- The Dagger CLI is released in tandem with the Dagger Engine and thus shares a version number with it.
- Dagger SDKs automatically provision a Dagger Engine at a compatible version.
Each release notes the compatible Dagger Engine version in its release notes. If running from the CLI, or providing a CLI for the SDK to use via the _EXPERIMENTAL_DAGGER_CLI_BIN
variable, check the release notes of the SDK, which indicate the required CLI and Engine versions.
The image below shows an example of the compatibility information available in the release notes:
How do I uninstall Dagger?
Follow these steps:
-
To uninstall a Dagger SDK, follow the same procedure that you would follow to uninstall any other SDK package in your chosen development environment.
-
Remove the Dagger CLI using the following command:
sudo rm /usr/local/bin/dagger
Homebrew users can alternatively use the following command:
brew uninstall dagger
-
Remove the Dagger container using the following commands:
docker rm --force --volumes "$(docker ps --quiet --filter='name=^dagger-engine-')"
-
Remove the
dagger
sub-directory of your local cache and configuration directories ($XDG_CACHE_HOME
and$XDG_CONFIG_HOME
on Linux or the equivalent for other platforms):- macOS
- Linux
rm -rf ~/Library/Caches/dagger
rm -rf ~/Library/Application\ Support/daggerrm -rf ~/.cache/dagger
rm -rf ~/.config/daggernoteThe paths listed above are defaults and may require adjustment for your specific environment. The third-party packages Dagger uses to determine these paths are listed below:
- Go (SDK and CLI): https://github.com/adrg/xdg
- Node.js: https://github.com/sindresorhus/env-paths
- Python: https://github.com/platformdirs/platformdirs
Does Dagger send telemetry?
By default, the Dagger CLI sends anonymized telemetry to dagger.io. This allows us to improve Dagger by understanding how it is used. Telemetry is optional and can be disabled at any time. If you are willing and able to leave telemetry enabled: thank you! This will help us better understand how Dagger is used, and will allow us to improve your experience.
What telemetry does Dagger send?
The following information is included in telemetry:
- Dagger version
- Platform information
- Command run
- Anonymous device ID
We use telemetry for aggregate analysis, and do not tie telemetry events to a specific identity. Our telemetry implementation is open-source and can be reviewed in our GitHub repository.
Can Dagger telemetry be disabled?
Dagger implements the Console Do Not Track (DNT) standard. As a result, you can disable the telemetry by setting the environment variable DO_NOT_TRACK=1
before running the Dagger CLI.
What are Dagger's caching features?
Dagger is able to cache:
- Operations, such as copying files or directories to a container, running tests, compiling code, etc.
- Volumes, such as data caches or package manager caches
Operations are automatically cached every time a Dagger pipeline runs. Cache volumes must be explicitly defined and used in your Dagger pipeline code.
Can I run the Dagger Engine as a "rootless" container?
No. "Rootless mode" means running the Dagger Engine as a container without the --privileged
flag. In this case, the container would not run as the "root" user of the system. Currently, the Dagger Engine cannot be run as a rootless container; network and filesystem constraints related to rootless usage would significantly limit its capabilities and performance. This also means that Dagger is not compatible with platforms which do not support privileged containers, such as AWS Fargate and GKE Autopilot. Read more about these constraints.
Can I configure the Dagger Engine?
Yes. By replacing the /etc/dagger/engine.toml
file with your custom configuration, you can configure the Dagger Engine with CA certs, registry mirrors or additional privileges. However, note that this is a temporary solution and may change in future. Read more about Dagger Engine configuration.
Can I use Dagger Engine to build Windows Containers?
Unfortunately, not right now. Dagger runs on top of BuildKit and support for Windows Containers is still experimental in BuildKit. In addition, Dagger has a lot of custom code written on top of BuildKit such as networking, init systems, and Linux namespace entries, that do not have exact parallels on Windows.
I am stuck. How can I get help?
Join us on Discord, and ask your question in our help forum. Our team will be happy to help you there!
Dagger Cloud
What is Dagger Cloud?
Dagger Cloud complements the Dagger Engine with a production-grade control plane. Features of Dagger Cloud include pipeline visualization, operational insights, and distributed caching.
Is Dagger Cloud a hosting service for Dagger Engines?
No, Dagger Cloud is a "bring your own compute" service. The Dagger Engine can run on a wide variety of machines, including most development and CI platforms. If the Dagger Engine can run on it, then Dagger Cloud supports it.
Which CI providers does Dagger Cloud work with?
Because the Dagger Engine can integrate seamlessly with practically any CI, there is no limit to the type and number of CI providers that Dagger Cloud can work with to provide Dagger pipeline visualization, operational insights, and distributed caching. Users report successfully leveraging Dagger with: GitLab, CircleCI, GitHub Actions, Jenkins,Tekton and many more.
What is pipeline visualization?
Dagger Cloud provides a web interface to visualize each step of your pipeline, drill down to detailed logs, understand how long operations took to run, and whether operations were cached.
What operational insights does Dagger Cloud provide?
Dagger Cloud collects telemetry from all your organization’s Dagger Engines, whether they run in development or CI, and presents it all to you in one place. This gives you a unique view on all pipelines, both pre-push and post-push.
What is distributed caching?
One of Dagger’s superpowers is that it caches everything. On a single machine (like a laptop or long-running server), caching "just works", because the same Dagger Engine writing to the cache is also reading from it. But in a multi-machine configuration (like an elastic CI cluster), things get more complicated because all machines are continuously producing and consuming large amounts of cache data. How do we get the right cache data to the right machine at the right time, without wasting compute, networking, or storage resources? This is a complex problem which requires a distributed caching service, to orchestrate the movement of data between all machines in the cluster, and a centralized storage service. Because Dagger Cloud receives telemetry from all Dagger Engines, it can model the state of the cluster and make optimal caching decisions. The more telemetry data it receives, the smarter it becomes.
Does distributed caching support ephemeral CI runners?
Yes. Ephemeral runners, by definition, lack caching; the runner’s local storage is purged when the runner is spun down. However, when your CI is connected to Dagger Cloud, these ephemeral runners gain all the benefits of a persistent shared cache.
Does Dagger Cloud store my cache data?
Yes. For distributed caching to work, it requires two components: a centralized storage service and an orchestrator. Dagger Cloud provides both, in one integrated package.
Where does Dagger Cloud store my cache data?
Dagger Cloud features a global data storage service spanning 26 regions across 3 cloud providers: AWS, Google Cloud Platform, and Cloudflare R2. The region closest to your compute is automatically selected.
Does Dagger Cloud support “bring your own storage” for distributed caching?
The ability to "bring your own storage" is coming soon. Please reach out to us if this capability is needed for your organization.
Dagger SDKs
What language SDKs are available for Dagger?
We currently offer a Go SDK, a TypeScript SDK and a Python SDK.
How do I log in to a container registry using a Dagger SDK?
There are two options available:
- Use the
Container.withRegistryAuth()
GraphQL API method. A native equivalent of this method is available in each Dagger SDK. - Dagger SDKs can use your existing Docker credentials without requiring separate authentication. Simply execute
docker login
against your container registry on the host where your Dagger pipelines are running.
Dagger API
What API query language does Dagger use?
Dagger uses GraphQL as its low-level language-agnostic API query language.
Do I need to know GraphQL to use Dagger?
No. You only need to know one of Dagger's supported SDKs languages to use Dagger. The translation to underlying GraphQL API calls is handled internally by the Dagger SDK of your choice.
There's no SDK for <language> yet. Can I still use Dagger?
Yes. It's possible to use the Dagger GraphQL API from any language that supports GraphQL or from the Dagger CLI.