This study focuses on improving High-Performance Liquid Chromatography (HPLC) in the Cloud Lab. HPLC is an essential analytical technique used across various scientific disciplines, from pharmaceuticals and biotechnology to environmental studies, making it a prime target for automation in a Cloud Lab environment. In a traditional lab, modern HPLC instruments incorporate basic automation (e.g. for liquid handling, sample collection, and executing predefined protocols); however, a scientist is still often required to be present to monitor the data readout and ensure its validity as well as proper functioning of the instrument. This manual oversight enables experts to catch issues such as pressure fluctuations due to air bubbles, clogs, leaks, empty mobile phase bottles, and other unexpected system behaviors. In contrast, in autonomous closed-loop systems like Cloud Lab, such real-time human intervention is impractical given the high-throughput use of instruments and the need for a fully closed data flow in the Design-Make-Test-Analyze (DMTA) cycle.