Description: Dataflow monitoring refers to the tools and features designed to oversee the performance of data processing jobs in real-time. These tools allow users to observe the flow of data through different processing stages, ensuring that jobs run efficiently and without interruptions. Monitoring includes visualizing key metrics such as execution time, resource usage, and latency, which facilitates the identification of bottlenecks and potential issues. Additionally, it provides alerts and notifications in case of failures or anomalies, enabling administrators to make informed and swift decisions to optimize performance. The ability to monitor dataflows is essential in environments where data processing is critical, such as in large-scale data analytics, machine learning, and real-time applications. In summary, dataflow monitoring is a fundamental practice that ensures the health and efficiency of data processing systems, enhancing the quality and speed of operations.
