How Spring AI Observability Exposes Latency and Tool Call Issues in AI Agents

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A Senior Software Engineer at BS23 in Dhaka encountered unexplained latency spikes and incorrect responses in a production AI agent built with Spring Boot and Spring AI. A two-tool query that previously took 10 seconds suddenly took 40 seconds, but without per-step instrumentation, the source of the delay could not be identified. A separate issue, where a keyword search query incorrectly triggered a fuzzy semantic search tool, was also only diagnosed after tool-level observability was added. Spring AI natively instruments key components such as ChatClient, ChatModel, and tool calls, generating metrics and traces following the standard gen_ai naming convention. By adding Micrometer and Prometheus dependencies alongside minimal configuration, developers can expose detailed per-step timing data through the Actuator endpoint without modifying core agent logic.

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ProgrammingDEV Community ·

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ProgrammingDEV Community ·

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