06/17/2025 | Press release | Distributed by Public on 06/17/2025 11:27
The next big wave in artificial intelligence is agentic AI, which harnesses autonomous agents to perform tasks by reasoning, learning, and adapting to changing circumstances. The success and efficiency of agentic AI systems depend on how well these AI agents communicate. Facilitating this communication requires monitoring AI agents and their underlying communication protocols, such as Model Context Protocol (MCP).
Part 1 of this blog series, The rise of agentic AI part 1: Understanding MCP, A2A, and the future of automation,covers the fundamentals of AI agents, models, and emerging communication standards like Agent2Agent (A2A) and MCP. This blog post covers AI agent observability and monitoring,and how to scale and monitor Amazon Bedrock Agents. Together, these capabilities make it possible to achieve robust, scalable observability in agentic AI environments so teams can build reliable and trustworthy applications and services.
Given the non-deterministic nature of large language models (LLMs) and dynamic cross-agent communication, organizations need standardized telemetry. OpenTelemetry-based GenAI semantic convention libraries are emerging to unify logging, metrics, and tracing in multi-agent ecosystems. Likewise, these standardized instrumentation libraries let you collect and analyze data from each step in an agent's decision or communication chain on Dynatrace. Observability of each step lets you monitor the communications among your agents and evaluate their health and performance, regulatory compliance, and debugging.
Amazon Bedrock Agents provide an easy way to build and scale generative AI applications with foundation models.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies, such as AI21 Labs, Anthropic, Cohere, Luma, Meta, Mistral AI, poolside, and Stability AI-or from Amazon's own model, Amazon Nova-all through a single API. In addition, Amazon Bedrock Agents also provide the broad set of capabilities teams need to build generative AI applications with security, privacy, and responsible AI best practices.
Dynatrace provides an AI-powered, unified observability and security solution for tracking and revealing the full context of used technologies and service interaction topology. Using Dynatrace for AI agent monitoring and MCP monitoring, teams can analyze security vulnerabilities and observe metrics, traces, logs, and business events in real time-automatically and securely.
"With the rise of agents, the need for deep visibility and real-time insights is more essential than ever," said Atul Deo, Director of Amazon Bedrock. Through this partnership, AWS and Dynatrace are uniquely positioned to deliver performance, cost, and quality insights alongside robust compliance monitoring-empowering customers to innovate with confidence."
As with hybrid and cloud-based environments, context-based observability of AI agents and models is essential for efficient and healthy outcomes. Here are some best practices:
With Amazon Bedrock and the Dynatrace AI Observability solution, you can cover the following use cases for agent observability:
We expect to see deeper integrations between agent orchestration protocols (A2A, MCP) and open observability frameworks, delivering end-to-end visibility from data ingestion to cross-agent collaboration. As standards converge, organizations will rapidly compose advanced AI solutions while retaining full transparency and control, paving the way for even greater scalability, resilience, and confidence in autonomous agents.
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