Monitoring of HAProxy, a popular load balancer, is often done through its status page, which provides real-time performance and state information. However, this approach has several shortcomings, including the lack of historical context and granularity in detecting issues. Traditional monitoring methods are reactive and don't allow for proactive management of infrastructure. They also fail to correlate HAProxy with other systems, making it difficult to identify root causes. Furthermore, infrequent or uncorrelated monitoring lacks predictive capabilities, leading to delayed responses to emerging issues. In contrast, Datadog's approach addresses these limitations by archiving HAProxy data and correlating it with other systems, enabling proactive management and prediction of potential issues.