Sure, here’s the translation into American English:
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Amazon Web Services (AWS) has taken a significant step toward business automation with the introduction of artificial intelligence (AI) applications that employ autonomous agents. These advancements allow organizations to execute complex workflows, access sensitive data, and make real-time decisions within their infrastructure.
One of the most notable innovations in this context is Amazon Bedrock AgentCore, a platform aimed at accelerating digital transformation through fully managed services. This solution eliminates the complexity of existing infrastructure, ensures session separation, and facilitates smooth integration with business tools, enabling the scalable deployment of reliable AI agents.
The AgentCore Gateway, a modular component within AgentCore, securely transforms AWS APIs and Lambda functions to be compatible with the Model Context Protocol (MCP). This is achieved through a single access point that implements authentication and operates with a serverless infrastructure, thereby minimizing operational overhead for businesses.
To maintain secure access in production environments, AI agents are typically deployed in virtual private clouds (VPCs). AWS VPC endpoints enhance security by establishing private connections between agents hosted in VPCs and the AgentCore Gateway, ensuring that sensitive communications remain within AWS’s secure infrastructure. These endpoints use dedicated network interfaces with private IP addresses, providing lower latency and optimized performance.
In terms of implementation, AWS has made access to the AgentCore Gateway easier through a VPC interface endpoint from Amazon EC2 instances, ensuring that access remains aligned with the principles of least privilege. This means that only authorized instances can communicate with the Gateway endpoint, reflecting a robust security approach.
Finally, it is essential to consider performance measurement and observability of these implementations. The AgentCore Gateway provides auditing and monitoring capabilities, allowing organizations to fine-tune and optimize their autonomous AI systems. With these advancements, companies can not only comply with security regulations and standards but also fully leverage the potential of distributed and scalable AI systems.
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Source: MiMub in Spanish
