redisSessionManager#6078
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Thanks for your pull request! It looks like this may be your first contribution to a Google open source project. Before we can look at your pull request, you'll need to sign a Contributor License Agreement (CLA). View this failed invocation of the CLA check for more information. For the most up to date status, view the checks section at the bottom of the pull request. |
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Hi @kartikPothapragada , Thank you for your contribution! We appreciate you taking the time to submit this pull request. Closing this PR here as it belongs to adk-python-community repo. |
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Problem:
The existing session management relied on in-memory storage, which limited scalability and persistence. Sessions would be lost on application restarts, and horizontal scaling across multiple instances was not supported.
Solution:
Implemented a Redis-backed session service that provides:
Persistent session storage across application restarts.
Support for distributed deployments by centralizing session state in Redis.
Configurable TTL (time-to-live) for session expiration.
Improved performance through Redis’ optimized key-value operations.
This approach was chosen because Redis is widely adopted, lightweight, and well-suited for fast session lookups and distributed environments.
Testing Plan
Unit Tests:
Added unit tests for RedisSessionManager covering session creation, retrieval, update, and deletion.
Verified TTL expiration logic.
All unit tests pass locally (pytest summary attached).
Manual End-to-End (E2E) Tests:
Deployed locally with Redis running in Docker.
Verified login flow persists sessions across multiple app restarts.
Tested session sharing across two app instances connected to the same Redis server.
Confirmed expired sessions are correctly removed.
Checklist
[x] Read the CONTRIBUTING.md.
[x] Self-reviewed code and added inline comments.
[x] Added unit tests for new functionality.
[x] Verified all tests pass locally.
[x] Manually tested end-to-end with Redis.
Additional Context
This change lays the groundwork for scaling ADK-based applications in production environments where multiple instances need to share session state. Future improvements could include support for Redis clusters and configurable connection pooling.