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+# Data Storage and Routing
+
+## Status
+
+Proposed
+
+## Context
+
+Currently, all encoded files are stored locally in a directory on each worker node. This approach suits our live streaming requirements due to its low latency and direct access. However, the system lacks a defined method for efficiently routing data requests to the appropriate worker, which is crucial for targeting specific live streams.
+
+## Decision
+
+To address this, we propose the following:
+* Maintain local storage of data in each worker to leverage quick access and response times.
+* Implement a monitoring and routing routine that starts with each new transcoding session.
+
+This routine will:
+* Periodically verify (every 5 seconds) if the worker is correctly transcoding the stream.
+* Notify a central API with status updates and routing metadata necessary for efficiently directing incoming requests.
+* Every key (stream) lasts for 30 seconds, after which it is deleted from the central API. This ensures the system always has the most up-to-date information.
+
+## Consequences
+
+* By avoiding the use of services like S3 for data storage, we anticipate significant cost savings without sacrificing performance for low latency streaming.
+* Without S3, we need to store which worker is responsible for each stream in a central key-value database to ensure efficient routing keeping resources usage low - probably Redis.