AI Agent Observability and Control: Building the New Monitoring Stack
AI agents are not single API calls; they are multi-step workflows that plan, fetch information, call tools, and synthesize outputs under uncertainty...
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AI agents are not single API calls; they are multi-step workflows that plan, fetch information, call tools, and synthesize outputs under uncertainty...
APM stands for application performance monitoring and refers to tools and practices that track how software applications perform. It measures things like response time, error rates, throughput, database queries, and how much CPU and memory the application uses. APM tools often tie together logs, metrics, and traces so you can follow an individual user request from start to finish. This lets engineers see where slowdowns or failures happen and which part of the system is responsible. Many APM systems also include real-user monitoring and synthetic tests to see performance from an end-user perspective. APM matters because slow or unreliable applications frustrate users, cost money, and harm a business’s reputation. By finding bottlenecks and root causes quickly, teams can fix issues before they become outages. APM also helps with capacity planning, cost control, and measuring the impact of code changes. In modern cloud and distributed systems, good APM is essential to keep complex applications running smoothly and to provide a consistent user experience.