Microservices, AI Agents and the Telemetry Explosion

Modern applications generate more operational data than ever before. Microservices architectures, cloud infrastructure, and rapid development cycles have created a world where systems emit massive volumes of logs, metrics, and traces, often far more than teams can realistically analyze.

In this episode of the Built for Trust Podcast, Nick Lippis speaks with Jad Naous, Founder of Grepr, about how the observability landscape is evolving as organizations confront the reality of exponential telemetry growth. From petabytes of system data to rising observability costs, they explore why traditional monitoring approaches are reaching their limits.

Jad explains how identifying application behavior patterns within telemetry streams can massively reduce noise while preserving the signals that matter most. The conversation also looks ahead to a future where AI-powered systems can detect anomalies, surface critical insights, and help operations teams resolve issues before they escalate based upon these application behavior patterns.

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