Monthly overview for 2025-03 - ntu-pear/PEAR_WebFE: Delivered Logger Timestamp Filtering and Date Range Query, enabling API to accept start/end dates for log retrieval and updating UI to support date-range input. This enhances observability, accelerates debugging, and strengthens audit readiness by allowing precise time-bound log analysis. The feature was implemented with a focused change set and a single commit (b9aba6e84c82b38fbf63521c98ee96e3517d9d1c) and integrates cleanly with existing log retrieval paths.

February 2025 monthly summary for ntu-pear/PEAR_patient_service: Progress focused on testability, deployment automation, and codebase cleanup to enable reliable releases and on-prem capabilities. Key outcomes include establishing a comprehensive test suite across modules, enabling self-hosted deployment configurations, expanding CI/CD workflows with secret handling and trigger controls, removing deprecated components to reduce maintenance burden, and enhancing observability with patient data logging and metadata tagging for traceability. These efforts improved quality, speed of delivery, and operational transparency for customers.

January 2025 (PEAR_patient_service) focused on streamlining CI/CD, strengthening data integrity, and stabilizing test automation to accelerate delivery of patient-prescription features and reduce production risk. Key outcomes include faster CI feedback, safer data migrations, and a more maintainable test suite with clearer ownership of changes across the service.

December 2024 — Summary focused on delivering core data-model features, stabilizing tests, and establishing robust deployment and observability workflows for ntu-pear/PEAR_patient_service. Key outcomes include: (1) data-model enhancements and feature work around patient_vital and prescriptions, (2) database schema cleanup for consistency and data integrity, (3) CI/CD and infrastructure configuration, (4) environment handling and secret management, (5) enhanced logging/observability and testing infrastructure, and (6) server run orchestration and CLI improvements. Major bugs fixed include reverting an unintended isDeleted addition to patient_vital due to issues, and addressing an unrelated 10-second sleep delay in the command runner. Overall, these efforts improve data integrity, deployment reliability, and production operability, enabling faster, safer feature delivery. Technologies demonstrated include Python, SQL schema migrations, pytest-based testing, CI/CD pipelines, environment management, logging/observability tooling, and server/CLI orchestration.