What problem does it solve? Manually creating and configuring Google Cloud data pipeline resources across dev, staging, and prod environments is error-prone and inconsistent. This Skill automates declarative resource provisioning through a single deployment.yaml file, ensuring environment-specific configurations stay synchronized and validated before deployment. ## Core Features & Use Cases - Declarative Resource Provisioning: Define BigQuery datasets/tables, Dataform repositories, Dataproc clusters, and BigQuery Data Transfer Service configs in one deployment.yaml file. - Multi-Environment Management: Map dev, staging, and prod environments to their own projects, regions, variables, and secrets with automatic parameter discovery via gcloud. - Secure Secrets Handling: References existing Secret Manager entries without ever reading or creating secret values, keeping sensitive data out of configuration files. - Use Case: A data engineer needs to set up a new BigQuery dataset with a DTS transfer config and a Dataform workflow for the staging environment. The Skill discovers the project ID and region, generates the deployment.yaml with proper labels and secret references, validates it, and deploys it with gcloud orchestration-pipelines. ## Quick Start Ask the agent to create a deployment.yaml that provisions a BigQuery dataset and a DTS transfer config for the dev environment, then validate and deploy it.
