An Automated, Low-Cost AWS Cost Monitoring Framework for Daily Operational Anomaly Detection

Abstract

Cloud workloads deployed on elastic infrastructure frequently experience cost anomalies caused by scaling misconfigurations, ingestion failures, or idle resource consumption. Such anomalies often remain unnoticed until billing cycles are complete, causing financial and operational risk. Commercial cost monitoring tools provide advanced analytics but introduce licensing and operational complexity unsuitable for many teams. This paper presents an automated AWS cost monitoring framework that retrieves billing data, performs daily trend analysis, and distributes anomaly-aware cost summaries using native AWS services. Implemented using serverless components and infrastructure-as-code automation, the system operates with minimal maintenance overhead while providing actionable daily cost visibility. Production usage demonstrates improved operational awareness and early detection of workload issues without reliance on third-party platforms.