🤖WSO2 Unveils Agent Manager for Centralized AI Governance
Centralized control for your AI agents
TL;DR
WSO2's Agent Manager offers centralized governance for AI agents, supporting multiple frameworks and deployment environments. It includes identity management, security controls, and operational oversight, addressing the growing challenge of managing AI agents.
WSO2 has released Agent Manager, an open-source platform providing centralized governance, identity management, and security controls for AI agents across various models and frameworks. This platform separates governance from agent logic, allowing common controls to be applied independently of the underlying technology. Agent Manager supports cloud, on-premises, and hybrid environments, with a focus on agent identity and authorization. It includes lifecycle controls, more than 40 built-in policies, and a Kubernetes-native sandboxed runtime for monitoring and managing agent activity. This is crucial for teams managing diverse AI technologies, ensuring consistent governance and security across different deployment environments.
Key Points
Agent Manager supports LangChain, CrewAI, Amazon Bedrock, Azure, Ballerina, and custom-built agents.
The platform includes over 40 built-in controls covering areas like PII masking and rate limiting.
Agent Manager provides lifecycle controls for moving agents through development, staging, and production.
The Kubernetes-native runtime offers a controlled environment for executing and monitoring agents.
Agent Manager uses OpenTelemetry for tracing and includes evaluation capabilities for monitoring agent behavior.
Why It Matters
If you're managing AI agents across different models and frameworks, WSO2's Agent Manager offers a centralized governance solution. It supports cloud, on-premises, and hybrid environments, ensuring consistent security and identity management. For teams using LangChain, CrewAI, or custom agents, Agent Manager provides a robust platform for lifecycle management and policy enforcement.
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