Internet Engineering task Force (IETF) L4S and Low Latency DOCSIS (LLD) specifications enable cable ISPs to offer low latency and low jitter services over current DOCSIS 3.1 deployments. However, successful deployment of those services depends on the effective management of latency and jitter factors from source to destination, including WiFi and access and core networks. Although many tests have been conducted to evaluate LLD with IETF non-queue building per hop behavior (NQB-PHB) and L4S traffic cross the access network, the performance evaluation on real production networks is very limited. This paper will demonstrate the benefits of access layer improvement in the form of Active Queue Management (AQM) for latency-sensitive applications in queue-building scenarios. It will also assess the advantages of AQM in a production environment with a mix of queue-building and non-queue-building traffic types to assess the quantitative and qualitative gaming performance of wired and wireless private client connectivity in the presence of passive features, which increase the end customers’ network throughput. The production environment will demonstrate and characterize the network gaming experience over air interface on a private client in the presence of other mobile clients with this enabled speed increase, out-of-home WiFi connectivity, etc. Not only will this paper demonstrate performance gain for latency-sensitive traffic when implementing AQM, but it will also indicate the lack of performance degradation for latency-insensitive applications that are running simultaneously. To determine the effectiveness of AQM in improving the client experience in the production environment, network monitoring tools were used to observe baseline latency and latency under incremental load in a real-world test-house serviced by a Cable Modem Termination System (CMTS) without AQM versus a CMTS with AQM. Different qualitative and quantitative network metrics – like network latency (RTT), jitter, user input latency (application responsiveness/lag) based on frame-per-second (fps) degradation – were calculated for a cloud gaming client in the presence of various congestion scenarios. AQM provides a superior Quality of Experience (QoE) for queue-building traffic when multiple applications simultaneously contend for airtime on a user’s network. In situations where the overall network utilization is higher than the actual cable modem’s provisioned speed or link rate, efficient buffering of these packets at the CMTS will avoid excessive packet drops during network congestion. In these airtime bottleneck scenarios, AQM serves to efficiently process the packets at the CMTS to provide a better quality of experience by proactively dropping just enough packets to avoid queue build up from data bursts.