While standardized protocols like Model Context Protocol (MCP) and Agent2Agent (A2A) have simplified agentic AI operations across multi-system infrastructures, development platforms have made agent building easier. However, there are still stumbling blocks for developers.
In a recent blog post, Chief Evangelist (EMEA) at AWS, Danilo Poccia, identifies these challenges as the fact that “developers and AI engineers have to spend months building foundational infrastructure for session management, identity controls, memory systems, and observability — [while] at the same time supporting security and compliance.”
The AWS solution is Amazon Bedrock AgentCore. Let’s dive into the services that Amazon Bedrock AgentCore provides and how they can assist developers in deploying and operating multiple AI agents quickly and securely at scale, using any framework, model, or host.
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Amazon Bedrock AgentCore
Now available in preview, Amazon Bedrock AgentCore is “a comprehensive set of enterprise-grade services.” These services include:
- AgentCore Runtime: Provides low-latency serverless environments with session isolation. Runtime supports various agent frameworks, including open-source tools and models, as well as multimodal workloads.
- AgentCore Memory: This feature manages session and long-term memory for developers, providing them with contextual data for models and historical knowledge for agent training.
- AgentCore Observability: Enhances transparency by providing a step-by-step visualization of agent execution, which includes metadata tagging, custom scoring, trajectory inspection, and troubleshooting/debugging filters.
- AgentCore Identity: Provides secure access to AWS services and third-party tools, including GitHub, Salesforce, and Slack, either directly for users or with pre-authorized user consent.
- AgentCore Gateway: Transforms APIs and AWS Lambda functions into tools ready for agents, deployable with unified access across various protocols.
- AgentCore Browser: Managed web browser instances designed to scale an agents’ web automation workflows.
- AgentCore Code Interpreter: Delivers a secure, isolated environment to execute code generated by agents.
All of these services are part of Amazon Bedrock AgentCore, and they are optimized to work together. However, they can also be used individually. The key advantage is that when you want to add another service, there is no complexity involved; they are designed to work seamlessly in tandem, with open-source and custom AI agent frameworks.
Ultimately, AgentCore simplifies the complexity of optimizing agent-based AI infrastructure and operations, allowing teams to deliver agents more quickly, precisely, and with less manual intervention.
Closing Thoughts
With a strong emphasis on low-code and no-code tools, along with promises from CEOs like Salesforce’s Marc Benioff about ecosystems consisting of billions of agents, the intricacies of agentic AI development can sometimes be overlooked. This is why the new suite of tools from AWS is significant.
These tools recognize the unique challenges faced by developers — not just business users — when it comes to designing and launching agentic AI solutions specific to their businesses. Are the foundational models available? Yes. Do developers have a range of platforms to choose from? Yes. Are unified protocols helping to ensure interoperability? Yes.
However, it is still critical that technologies like AgentCore bridge the gap between these innovations in a way that not only accelerates development and innovation but also ensures that the process is secure and compliant.
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