Google Cloud has enhanced its Observability suite with new capabilities for developers and SREs. Observability Analytics, formerly Log Analytics, now integrates trace data generally available to provide a unified experience. This allows for detailed root-cause analysis of traditional and agentic workloads. The Observability API for management and configuration is also generally available. A key feature is support for SQL in Cloud Trace. This enables joining application logs with trace spans for in-depth analysis. For AI agents, it allows analysis of telemetry across thousands of runs to identify tool failures and performance bottlenecks. Observability Analytics leverages BigQuery and SQL for direct analysis of telemetry data. This unification breaks down data silos, accelerating troubleshooting and enabling business correlation by joining observability data with business metrics. In-place analysis reduces data duplication and storage costs. Use cases include optimizing AI agents by analyzing tool failures and latency at scale. It also helps identify specific customers experiencing performance issues. While log and trace explorers are for individual investigations, Observability Analytics is designed for aggregations and broad analytical questions. The Observability API also allows AI agents to query telemetry programmatically through BigQuery. Users can start analyzing trace data in Observability Analytics today via the Google Cloud console.