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Architectural Deep-DiveSystems Engineer
Mental Health Diary Backend
A ultra-high-performance, low-memory footprint server architecture built to process high-concurrency requests. Implements a customized engine processing binary audio data stream to execute instant automated text transcriptions via asynchronous endpoints.
Rust (Actix-web)PythonPLpgSQLPostgreSQL
System Challenge
Processing continuous, high-concurrency binary audio streams for transcription while maintaining an ultra-low memory footprint and strict privacy standards for sensitive mental health logs.
Architecture & Solution
Architected the core ingestion service in Rust using Actix-web for bare-metal performance and memory safety. Offloaded heavy transcription machine-learning tasks to a Python microservice, bridging the two via efficient PLpgSQL functions in PostgreSQL.
Performance Outcomes
- Achieved a 90% reduction in RAM overhead compared to a Node.js equivalent.
- Implemented robust asynchronous queues capable of handling simultaneous audio stream decoding.
- Secured all payloads with robust in-transit and at-rest cryptography.