Add KMS encryption to YAML pipeline

[tarun-google]

https://pantheon.corp.google.com/dataflow/jobs/us-central1/2025-12-04_11_26_10-10794556338436195746;bottomTab=WORKER_LOGS;graphView=0;logsSeverity=INFO;step=?pageState=(%22dfTime%22:(%22s%22:%222025-12-04T19:26:10.498Z%22,%22e%22:%222025-12-04T19:32:14.697Z%22))&project=apache-beam-testing

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[gemini-code-assist]

Summary of Changes

Hello @tarun-google, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a critical security enhancement to Beam YAML pipelines by integrating Google Cloud Key Management Service (KMS). It provides a robust mechanism for encrypting sensitive configuration parameters, such as database credentials, directly within YAML definitions. These encrypted values are then automatically decrypted at runtime using a specified KMS key, ensuring that confidential information is never exposed in plaintext throughout the pipeline's lifecycle. This significantly elevates the security and compliance of data processing workflows defined using Beam YAML.

Highlights

• KMS Integration for YAML Pipelines: Introduced a new kms.py module and integrated Google Cloud Key Management Service (KMS) to allow decryption of sensitive configuration values directly within Beam YAML pipelines.
• YAML Schema and Preprocessing Updates: The pipeline.schema.yaml now supports an encryption block within transform definitions, specifying a KMS key and fields to be decrypted. A new preprocess_encryption function in yaml_transform.py handles the automatic decryption of these fields at runtime.
• Enhanced Security for Sensitive Data: This feature enables users to store sensitive information, such as database credentials, in an encrypted format within their YAML files, significantly improving the security posture by preventing plaintext exposure.
• New Example and Dependencies: A new example YAML pipeline (write_to_jdbc.yaml) demonstrates the usage of KMS encryption for database credentials. The google-cloud-kms library has been added as a dependency for GCP-related functionalities.
• Comprehensive Unit Tests: Dedicated unit tests have been added for the KMS decryption logic and the YAML preprocessing of encrypted fields, ensuring robustness and correctness of the new functionality.

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