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The article explains that AI agent traffic differs from traditional web application traffic because of long-lived state, branching calls, rapid retries, and bursty load. It proposes applying microservices principles, such as externalizing state and isolating dependencies, to preserve conversation context during horizontal scaling.
JetBrains explains how Service Map is built inside its development environments using OpenTelemetry traces arriving from the system while it is running, rather than relying on static diagrams or static code analysis. The feature processes late and out-of-order data to gradually update relationships between services, databases, and message-integration points.
Atlassian presents a root cause analysis methodology based on linking metrics, logs, and traces temporally and through a service dependency graph. The goal is to turn large volumes of monitoring data into ranked, verifiable hypotheses while preserving the engineer’s role in validation and decision-making.