Analisis Kinerja Auto Configuration Server (ACS) Berbasis GenieAcs Untuk Manajemen Perangkat TR-069

Manually managing TR-069 protocol-based network devices requires considerable time and effort and has the potential to cause configuration inconsistencies, especially when the number of customer devices increases. Auto Configuration Server (ACS) is one solution for centralized device management through remote provisioning, monitoring, and configuration processes. This study aims to analyze the performance of GenieACS-based Auto Configuration Server in managing TR-069 devices and determine the system's ability to handle the increasing number of Customer Premises Equipment (CPE) devices. The system implementation was carried out using GenieACS as the ACS, MongoDB as the database, and Prometheus and Grafana as monitoring components. Testing was carried out in a laboratory environment using the Black Box Testing method and performance testing with load scenarios of 10, 15, 20, 25, and 30 CPEs. The performance parameters analyzed included the success of system functions, provisioning throughput, CPU and RAM usage, TR-069 communication latency, and device configuration response time. Black Box testing results showed that all key functions—ACS Web login, CPE monitoring, Summon, provisioning, and data refresh—operated successfully. Throughput testing increased from 120 CPE/minute at 10 CPEs to 360 CPE/minute at 30 CPEs. CPU usage increased from 10% to 21%, while RAM usage remained relatively stable at 33–34%. Latency testing showed a value of 165–240 ms, while configuration response time was in the range of 275–355 ms, still well below the 3-second limit. These results demonstrate that GenieACS demonstrates stable, responsive, and efficient performance in managing TR-069 devices on a laboratory scale. This research demonstrates that GenieACS is suitable for use as an ACS solution to support network device automation and management, although testing with a larger number of CPEs is still needed to more thoroughly understand the system's capacity limits.