Jaeger adopts OpenTelemetry at its core to solve the AI agent observability gap (thenewstack.io)

Jaeger, a prominent tool for observability in software systems, is evolving to address the unique challenges posed by generative AI applications and autonomous agents. The adoption of OpenTelemetry as its core framework enhances its ability to trace complex AI execution paths, which now involve intricate processes like prompt assembly and external tool interactions. By transitioning to Jaeger v2, which integrates OpenTelemetry natively, the platform consolidates metrics, logs, and traces into a single deployment model. This shift not only improves performance but also allows for more sophisticated tracing features critical for analyzing AI workloads. To facilitate collaboration between engineers and AI agents, Jaeger is implementing three open standards: the Model Context Protocol (MCP), Agent Client Protocol (ACP), and Agent–User Interaction Protocol (AG-UI). These protocols standardize how AI models access data and communicate with users, transforming Jaeger into an interactive workspace. As a result, developers can harness advanced querying capabilities that parse natural language constraints into deterministic trace queries, significantly enhancing debugging processes. By aligning its observability tools with the evolving demands of AI-driven architectures, Jaeger ensures that organizations can effectively monitor and analyze their AI applications from development through production.