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Copy file name to clipboardExpand all lines: CHANGELOG.md
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All notable changes to this project will be documented in this file. The format loosely follows [Keep a Changelog](https://keepachangelog.com/en/1.1.0/) and the repository uses [Semantic Versioning](https://semver.org/).
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## [1.1.1] - 2025-12-04
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### Added
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- Workflow now consumes GitHub repository variables `ENV_STAGE` / `ENV_PROD`, writes their full multi-line contents into `.env`, and feeds that file to the Adobe API Mesh CLI before create/update operations.
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- Documentation updates explaining the new `.env` injection path and the recommended GitHub variables for environment-specific configuration.
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## [1.1.0] - 2025-11-25
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### Added
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- New primary workflow `.github/workflows/deploy.yaml` that materializes branch-specific mesh secrets, computes CLI flags automatically, and waits for mesh provisioning with retry logic.
Copy file name to clipboardExpand all lines: README.md
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### Key Capabilities
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-**Dynamic `.env` injection** – GitHub repository variables (`ENV_STAGE`, `ENV_PROD`) can store full `.env` payloads, and the workflow materializes them into a runtime `.env` before invoking the API Mesh CLI.
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-**Secret materialization** – branch-specific secrets can include encrypted mesh credentials (`MESH_SECRETS_*`) that the workflow writes to `secrets.yaml` on the fly and passes through `--secrets` so sensitive resolvers stay out of Git history.
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-**Auto-flag builder** – the workflow inspects the repo for `.env` and `secrets.yaml` and automatically appends the correct `aio api-mesh:*` flags, helping you wire runtime configuration consistently.
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-**Provisioning watchdog** – mesh deployments poll `aio api-mesh:status` for up to 10 minutes with friendly logging, failing early if provisioning stalls or ends unexpectedly.
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Add any extra secrets referenced by your mesh (for custom resolvers, HTTP headers, etc.) and load them via environment variables or additional steps in the workflow.
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### Recommended GitHub Variables
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| Variable Name | When Used | Description |
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| --- | --- | --- |
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|`ENV_STAGE`| Pushes to `staging`| Full contents of the `.env` file you want the staging deployment to consume (multi-line values supported). |
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|`ENV_PROD`| Pushes to `production`| Production `.env` payload, typically mirroring secure resolver configuration for production meshes. |
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If these variables are present, the workflow writes them to `.env` before running `aio api-mesh:*`. If they are empty, the pipeline falls back to any `.env` file committed in the repository or skips the flag entirely.
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---
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## Quick Start
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2.**Add your mesh files**:
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- Place the primary mesh definition in `mesh.json`.
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- Commit any supporting schemas/resolvers alongside it.
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- (Optional) store non-secret runtime values in `.env` (e.g., `MESH_NAME=my-mesh`). The workflow passes `--env .env` to the CLI so those values are merged during create/update.
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- Provide runtime configuration via Git-tracked `.env` files **or** populate the `ENV_STAGE` / `ENV_PROD` GitHub variables with the exact `.env` content you want injected per environment.
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3.**Populate GitHub Secrets** with the values listed above.
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4.**Adopt the branch convention**:
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- Push or merge to `staging` for deploying to staging Adobe workspaces.
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