Developed a configurable tick interval feature for Video Search and Summarization within the open-edge-platform/edge-ai-libraries repository, enabling dynamic adjustment of processing speeds based on user-defined settings. This work focused on creating a scalable, config-driven foundation to optimize throughput, resource utilization, and responsiveness for variable workloads, supporting service level objectives and cost management. The implementation leveraged TypeScript and YAML, utilizing Docker and Kubernetes for deployment and orchestration. Emphasis was placed on maintainability through code instrumentation and signed-off commits, with all changes traceable to a specific ticket and commit. No major bugs were addressed, as efforts centered on robust feature delivery.