About This Architecture

Autonomous trading bot powered by AWS Bedrock AgentCore orchestrates multi-step trading decisions using Claude LLM with specialized agent tools for market analysis, order execution, and risk management. EventBridge Scheduler triggers Lambda every 5 minutes, invoking Bedrock AgentCore Runtime which executes bot_loop.py, a Strands Agent that calls Claude for reasoning and dynamically invokes tools like technical_analysis (RSI/MACD/SMA/BB), execute_order, and portfolio management. Secrets Manager secures Binance testnet credentials while Parameter Store provides a kill-switch control, and CloudWatch GenAI Observability tracks model invocations, tool calls, and trading cycles for compliance and debugging. This architecture demonstrates production-ready patterns for agentic AI: least-privilege IAM roles, infrastructure-as-code via Terraform, centralized secret and configuration management, and comprehensive observability of LLM reasoning and external API interactions. Fork this diagram on Diagrams.so to customize tool definitions, adjust scheduling intervals, or adapt for live trading environments with additional safeguards.

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How do I build an autonomous trading bot using AWS Bedrock AgentCore with Claude LLM and agent tools?

This diagram shows a complete autonomous trading bot using AWS Bedrock AgentCore: EventBridge Scheduler triggers Lambda every 5 minutes, which invokes Bedrock AgentCore Runtime running bot_loop.py. The Strands Agent calls Claude LLM to reason about market conditions, then dynamically invokes agent tools (technical_analysis, execute_order, portfolio, risk_management) to gather data and execute trad