Sales teams faced challenges in efficiently processing and acting on telemetry data across multiple Kubernetes clusters. With isolated data streams and manual workflows, response times were delayed, and system performance suffered. The client required an automated solution to streamline data ingestion, prioritize events, and enable real-time orchestration. 

Solution 

Calsoft implemented a closed-loop automation framework, enhancing telemetry data processing with machine learning-driven event prioritization and real-time orchestration across edge and core clusters. 

• Centralized telemetry from all clusters into one unified processing pipeline 
• Automated orchestration using Apache Airflow for seamless scheduling and execution 
• Machine learning-powered event ranking for context-aware decision-making 
• Real-time monitoring dashboard for global visibility and orchestration insights