Amazon Bedrock AgentCore: Production AI Agents on AWS
Amazon Bedrock AgentCore is AWS's production platform for AI agents. Per AWS, it is "the platform for production AI agents. Any framework. Any model. Secure at scale." You bring the agent (built in LangChain, OpenAI Agents SDK, Claude Agent SDK, Strands SDK, or your own framework). AWS brings the runtime, security, observability, and infrastructure underneath.
The 30-second version
- What: AWS-managed runtime and security layer for production AI agents
- Who: teams shipping AI agents on AWS who want the security review done for them
- Price: usage-based via AWS; bring-your-own model costs separate
- Best at: running framework-agnostic agents with AWS-grade security
- Verdict: pick AgentCore when you ship agents on AWS and security review is the bottleneck
What Bedrock AgentCore actually is
AgentCore is best understood as the infrastructure layer between your agent code and the rest of AWS. You write the agent using any framework. AgentCore wraps it in a runtime that handles authentication, access policies, observability, and sandboxing. The same code that runs on your laptop deploys to production with security built into the platform.
The framework flexibility matters. Most cloud agent platforms force you into the vendor's opinions. AgentCore explicitly supports LangChain, OpenAI Agents SDK, Claude Agent SDK, Strands SDK, and custom frameworks. You can swap frameworks without re-architecting your infrastructure.
AWS positions AgentCore for the moment when your agent needs to call multiple things in the same turn: an MCP server, a knowledge base, an internal API, and a Lambda function. Wiring all of that with proper access controls is the work AgentCore takes off your plate. Security controls are enforced at the platform layer with access policies verified by automated reasoning.
Key capabilities
- Framework-agnostic: LangChain, OpenAI Agents SDK, Claude Agent SDK, Strands SDK, custom
- Model-agnostic: any Bedrock-supported model (Anthropic Claude, Amazon Nova, Mistral, others)
- Authentication and access control across multiple systems
- Observability: debugging and tracing built-in
- Security policies verified by automated reasoning
- Same-code deploy: laptop to production without rewriting
- Integration with MCP servers, knowledge bases, internal APIs, Lambda
Pricing
AgentCore is usage-based and billed through AWS. You pay for runtime usage plus the model inference costs (Anthropic Claude, Amazon Nova, etc.) plus any AWS services your agent calls. Specific tier pricing changes over time; check the AWS Bedrock AgentCore page for current rates.
Who Bedrock AgentCore fits
- Teams shipping production agents on AWS (the security review savings alone justify it)
- Enterprises that need access controls verified by automated reasoning
- Companies running multiple frameworks (LangChain agents + OpenAI agents) on one runtime
- Builders using Anthropic Claude via Bedrock for compliance reasons
Who it does not fit
- Teams not on AWS (the value is wrapped in AWS infrastructure)
- Solo developers prototyping (the AWS overhead is more friction than your laptop)
- Workflows that fit a simpler tool (n8n self-host, OpenAI Agents SDK direct) without enterprise security needs
Bedrock AgentCore vs Vertex AI Agent Engine and Azure AI Foundry
| Axis | AgentCore (AWS) | Vertex Agent Engine (Google) | Azure AI Foundry (Microsoft) |
|---|---|---|---|
| Cloud | AWS | Google Cloud | Azure |
| Framework flexibility | LangChain, OpenAI, Claude, Strands, custom | ADK, LangChain, custom | Microsoft Agent Framework, LangChain |
| Model options | Anthropic, Amazon Nova, Mistral, others | Gemini, third-party via Vertex | OpenAI, Anthropic, others via Foundry |
| Security model | Verified by automated reasoning | Google Cloud IAM | Microsoft Entra + Defender |
| Best for | AWS-native enterprises | Google Cloud + Gemini stacks | Microsoft 365 + Azure stacks |
Pros and cons
Pros:
- Framework-agnostic in a category where most clouds lock you in
- Automated-reasoning security policies are the strongest in the category
- Same code on laptop and in production removes a usual cause of bugs
Cons:
- AWS-only (no value outside the AWS ecosystem)
- Pricing requires planning for production volume
- Learning curve if your team is new to AWS IAM and policies
How I'd think about Bedrock AgentCore on SellerShorts
For SellerShorts tool builders targeting enterprise Amazon brands, AgentCore is one of the cleanest production paths in 2026. Many large Amazon sellers already run on AWS, and AgentCore lets your agent inherit their security posture instead of rebuilding it. For smaller builders selling to individual sellers, the AWS overhead is more than you need. Start with a simpler framework, move to AgentCore when enterprise buyers ask for SOC 2 evidence.
Try Bedrock AgentCore
Get started with Bedrock AgentCore
Available through AWS. You need an AWS account to start.
Building agents for Amazon sellers? See the Amazon AI hub.
Frequently asked questions
What is Bedrock AgentCore?
Amazon Bedrock AgentCore is AWS's platform for building and deploying production AI agents. Per AWS, it is 'The platform for production AI agents. Any framework. Any model. Secure at scale.' It works with LangChain, OpenAI Agents SDK, Claude Agent SDK, Strands SDK, or your own framework.
Is Bedrock AgentCore the same as Bedrock Agents?
AgentCore is the newer, broader platform. Earlier 'Bedrock Agents' referred to a more constrained, AWS-managed agent feature. AgentCore lets you bring your own framework and run it on AWS infrastructure with built-in security, observability, and access control. AWS documentation in 2026 uses 'AgentCore' as the umbrella term.
What does AgentCore actually give me?
Per the AWS product page: framework flexibility (LangChain, OpenAI SDK, Claude SDK, Strands, or custom), connection and control (authentication and access across systems), observability (debugging and tracing), and security infrastructure built on AWS with access policies verified by automated reasoning.
Should I use AgentCore vs running my own agent on EC2?
AgentCore replaces the hours you would spend wiring up secrets management, access policies, observability, and sandboxing. For prototypes, your own EC2 or Lambda is fine. For production agents in regulated environments, AgentCore saves the security review cycle.