This skill ships inside the Astronomer Data Engineering plugin — install the plugin and you also get hooks.
WHEN YOUR AGENT SHOULD USE IT
USE FOR
- Build and pack the Go program with the SDK's own packing tool, since a plain build is ignored.
- Compile for the worker's operating system and chip so it does not fail with a format error.
- Bake the packed program into a Docker image or a Kubernetes deployment.
- Deploy the same program on Astronomer's Astro platform through its project folder and .env file.
- Pin the SDK to a release, or try an unreleased fix from a specific commit.
Documents
This is the playbook your agent receives when the skill activates — you don't need to read it to use the skill, but it's here to audit before installing.
Deploying Go SDK Bundles
A Go SDK deployment has one artifact: a bundle, a single self-contained native executable that also carries its embedded source and a manifest (the AFBNDL01 format, "the executable is the bundle"). You build and pack it with go, place it where Airflow's ExecutableCoordinator scans, and the Python task runner forks it once per task instance. This skill is platform-neutral: it shows the build, the coordinator wiring, then how to get the bundle onto a worker.
Experimental. The Go SDK is under active development and not production-ready. Everything resolves against the single module
github.com/apache/airflow/go-sdk(Go 1.24+).
Order of operations: write the tasks (authoring-go-sdk-tasks) -> build and pack the bundle (this skill) -> place it under
executables_rootand configure the coordinator -> deploy the matching Python stub DAG.
Build and pack the bundle
The coordinator only recognizes a packed bundle: it scans for the AFBNDL01 trailer and silently skips any file that lacks it, so a plain go build binary is not deployable on its own. Use the packer, shipped as a Go 1.24 tool directive in go.mod (no global install, version pinned per project):
go tool airflow-go-pack ./example/bundle # build + pack in one step
go tool airflow-go-pack --goos linux --goarch amd64 ./example/bundle -- -trimpath # cross-compile; flags after -- pass to `go build`
go tool airflow-go-pack --executable ./bin/sample-dag-bundle --source main.go --airflow-metadata <airflow-metadata.yaml> # pack an existing binary
go tool airflow-go-pack inspect ./bin/sample-dag-bundle # inspect a packed bundleThe packer builds the binary, execs it with --airflow-metadata to capture the manifest from RegisterDags, then appends source + manifest + a 64-byte trailer. The result is one runnable file.
- Build for the worker's OS/arch. The bundle is a native executable and is not portable; cross-compile with
--goos/--goarch. A mismatched binary fails on the worker withexec format error. - Re-pack after any change to the binary. Re-stripping, re-signing, or swapping in a debug build invalidates the trailer's
binary_sha256, and the bundle is then rejected.
Wire up the coordinator
Python's ExecutableCoordinator scans executables_root, matches the incoming dag_id against each bundle's embedded manifest, verifies its integrity hash, then forks the bundle. No Go process runs on the host.
-
Place the packed executable under a scanned directory:
cp ./bundle /opt/airflow/executable-bundles/ # identified by the AFBNDL01 trailer, not by filename -
Register
ExecutableCoordinatorand route the queue to it (see configuring-airflow-language-sdks):[sdk] coordinators = {"go": {"classpath": "airflow.sdk.coordinators.executable.ExecutableCoordinator", "kwargs": {"executables_root": ["/opt/airflow/executable-bundles"]}}} queue_to_coordinator = {"golang": "go"} -
Deploy the matching Python stub DAG; its
queue=must equal thequeue_to_coordinatorkey (golanghere), and itsdag_id/task_ids must match what the bundle registered.
Deployment paths
The SDK runs on any Airflow with the Task SDK; Astronomer tooling is not required.
Docker / Kubernetes
Cross-compile the bundle for the image's platform and bake it in. No Go runtime or worker process is needed in the image; the Python task runner forks the bundle.
FROM apache/airflow:3.3.0 # the language SDKs target Airflow 3.3+
COPY ./executable-bundles/ /opt/airflow/executable-bundles/
# set AIRFLOW__SDK__COORDINATORS and AIRFLOW__SDK__QUEUE_TO_COORDINATOR as env varsOn the Helm chart, bake the bundle into a custom image as above or mount it via a shared volume, and set the [sdk] config through environment variables on the worker/scheduler. See deploying-airflow for the broader Docker Compose and Helm workflow.
The
apache/airflow:3.3.0tag above is illustrative: the language SDKs need Airflow 3.3 or newer. Pin whatever current 3.x you actually run rather than copying this tag from memory; read the base image's current tags or docs.
Astro (one option, not required)
- Build/pack the bundle, then stage it in the project:
mkdir -p include/executable-bundles && cp ../go-bundle/<packed-bundle> include/executable-bundles/. - In the project
Dockerfile, copy the bundle to the coordinator's directory:COPY include/executable-bundles/ /opt/airflow/executable-bundles/. - Put the coordinator config in the project
.env(loaded automatically): theAIRFLOW__SDK__*JSON values (see configuring-airflow-language-sdks). astro dev start(orastro dev restartafter changes); deploy withastro deploy.
Don't pin Astro Runtime / Airflow versions from memory; read the generated
Dockerfileor current docs. While the Go SDK is in preview, a beta/dev image may be required.
Versioning and preview installs
go-sdk/ is a single Go module, so its release tag takes the monorepo subdir form, go-sdk/vX.Y.Z (do not create per-cmd tags). Your bundle module depends on github.com/apache/airflow/go-sdk; pinning that version also pins airflow-go-pack, which is a package in the same module referenced through the tool directive. Pin against the release tag:
go get github.com/apache/airflow/go-sdk@v1.0.0To build against an unreleased commit or branch (for example, to try a fix ahead of the next tag), depend on it directly and Go fabricates a pseudo-version:
go get github.com/apache/airflow/go-sdk@<commit-or-branch>Deploy checklist
- Bundle built and packed (
go tool airflow-go-pack); registereddag_id/task_idmatch the Python stubs. - Built for the worker's OS/arch (e.g.
--goos linux --goarch amd64). - Packed AFBNDL01 bundle placed under a directory in
executables_root. ExecutableCoordinator+queue_to_coordinatorconfigured (configuring-airflow-language-sdks).- Python stub DAG deployed, its
queue=routed to the Go coordinator. - Re-packed after any rebuild/strip/sign (preserves
binary_sha256).
Related Skills
- authoring-go-sdk-tasks: Write the Go task code and the matching Python stubs.
- configuring-airflow-language-sdks: Register
ExecutableCoordinatorand route the queue. - deploying-airflow: General Airflow deployment (Astro, Docker Compose, Kubernetes).
- setting-up-astro-project: Initialize and configure an Astro project.
Installation
npx skills add astronomer/agents --skill "deploying-go-sdk-bundles" --full-depthRun this in your project — your agent picks the skill up automatically.
BEFORE IT WILL WORK
2 FOR YOU- 01
Run Airflow 3.3 or newer
- 02
Have Go 1.24 or newer to build the program
License
Licensed under Apache-2.0— you can use, modify, and redistribute it under that license's terms.
View the full license file on GitHub →