Amazon Web Services Released CloudWatch Omni
The new monitoring platform tracks the performance of agentic artificial intelligence systems.
Updated on Sept. 28, 2026 in Artificial Intelligence
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Amazon Web Services has launched Amazon CloudWatch Omni to monitor agentic artificial intelligence. The platform provides tools for developers to evaluate the performance of AI agents.
Why it matters
Traditional observability tools often struggle to determine if an AI agent provides accurate answers. This platform addresses that gap by scoring agent outputs for faithfulness, helpfulness, and coherence.
Amazon CloudWatch Omni includes 17 built-in evaluators designed to score AI agent outputs for faithfulness and routing correctness. It also supports OpenTelemetry and OpenInference standards for broad compatibility.
The players
Amazon Web Services
Amazon Web Services is a comprehensive cloud computing platform providing scalable infrastructure and artificial intelligence tools to developers globally.
Sony
Sony is a multinational conglomerate that served as an early design partner for the CloudWatch Omni platform.
Capital One
Capital One is a major financial services company that functioned as an early adopter of the new observability platform.
The details
The platform captures traces and shares a single data layer between developer IDE extensions and web interfaces. It integrates with Visual Studio Code, Cursor, and Kiro, while allowing data ingestion from Azure and third-party tools.
Timeline
September 2026: Amazon CloudWatch Omni reached general availability.
2029: IDC projects that more than 1 billion agents will be deployed.
The Tech Race
The adoption of OpenTelemetry standardizes how Amazon CloudWatch Omni interacts with external AI agent traces. This platform extends the utility of existing open-source telemetry standards by applying them specifically to the unique requirements of agentic AI monitoring.
Developers gain the ability to monitor AI performance across platforms like Azure, reducing the need for manual agent output review. Additionally, the AWS DevOps Agent automates signal correlation to improve troubleshooting speed in complex environments.
The takeaway
As businesses scale their use of agentic AI, monitoring for output faithfulness has become a critical operational requirement. Adopting unified data standards allows teams to maintain visibility across disparate AI systems and development environments.
Further reading
Learn more about the latest developments in Artificial Intelligence.
Source note: This article includes information reported by SiliconANGLE.
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