This study introduces an IoT-based hydroponic water quality monitoring system designed to enhance the efficiency, reliability, and accessibility of hydroponic environment management. The system monitors four key parameters: pH, temperature, Total Dissolved Solids (TDS), and water level, using sensors connected to an ESP8266 microcontroller. Data is transmitted in real-time via the MQTT protocol, processed through the Node-RED middleware, and stored in a MariaDB database. Interactive web-based data visualization supports data-driven decision-making and simplifies user monitoring of system conditions. Agile methodology and DevOps were implemented to ensure iterative system development, responsiveness to changes, and continuous updates via Continuous Integration/Continuous Deployment (CI/CD). Field tests conducted in a greenhouse environment demonstrated that the system could improve operational efficiency and sustainability, while also being flexible enough to adapt to various types of plants. The User Acceptance Test (UAT) yielded an average score of 4.8 out of 5, indicating high user satisfaction with the system's functionality and interface. This study also identifies future development opportunities, including the integration of additional sensors, automated control mechanisms, and predictive analytics powered by machine learning to optimize crop yields and management efficiency. With its innovative approach, this research not only advances IoT-based hydroponic technology but also makes a significant contribution to developing resilient, scalable, and efficient smart farming solutions.