Ricardo Ferreira from Elastic and Viktor Gamov from Kong explore how an effective observability (O11y) strategy can transform complex microservices environments into manageable systems by consolidating telemetry data—metrics, traces, and logs—into platforms like Elastic Observability. They discuss how traditional monitoring systems have evolved from simple setups to intricate distributed systems, likening the change to managing pets versus cattle. The blog outlines the process of integrating Kuma service mesh with Elastic Observability to simplify architecture, reduce operational overheads, and enable advanced analytics, including machine learning for anomaly detection. They emphasize the integration of telemetry data using tools like Elastic Metricbeat and OpenTelemetry, highlighting Elastic's machine learning capabilities to automate insights and alerting. By consolidating data through Elastic Observability, the authors demonstrate how it becomes easier to identify root causes and enhance the operational efficiency of microservices.