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Strands Agents SDK Deploy — Visualize Agent Traces with OpenTelemetry
Enable the Strands Agents SDK's built-in OpenTelemetry support to visualize agent reasoning and tool calls as traces in Jaeger. Only 2 lines of code change required.
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Blog Posts
Blog
Strands Agents SDK Deploy — Managed Deployment with AgentCore CLI
Use the AgentCore CLI (Node.js) to deploy a Strands agent to Bedrock AgentCore with just agentcore create + deploy. Verified that session isolation enables conversation continuity across invocations.
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Strands Agents SDK Deploy — Serverless Deployment to AWS Lambda
Deploy a Strands Agents SDK agent to AWS Lambda using the official Lambda Layer. Measured cold start Init Duration at ~1 second and warm start at under 1 second.
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Strands Agents SDK Deploy — Turn Your Agent into an HTTP API with Docker
Wrap a Strands Agents SDK agent with FastAPI to create an HTTP API, then package it as a Docker container. Covers the async def hang pitfall and SSO credential issues encountered during verification.
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Strands Agents SDK Multi-Agent — Choosing the Right Multi-Agent Pattern
Run the same task with Agents as Tools, Swarm, and Graph, then compare structural differences via metrics. Establish selection criteria for choosing the right pattern per use case.
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Strands Agents SDK Multi-Agent — Nest Swarm and Graph Together
Embed a Swarm as a node in a Graph to combine autonomous collaboration with structured workflows. Verify nested execution results and multi-agent Hooks for node monitoring.
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Strands Agents SDK Multi-Agent — Structure Workflows with Graph
Build deterministic workflows with Strands Agents SDK's Graph pattern. Define sequential, parallel, conditional, and feedback loop workflows with GraphBuilder, verified with real execution results.
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Strands Agents SDK Multi-Agent — Autonomous Agent Collaboration with Swarm
Run Strands Agents SDK's Swarm pattern hands-on and verify how agents autonomously hand off tasks to each other. Compare with the Agents as Tools pattern from the intro series.
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Strands Agents SDK Practical — Optimize Agents with Metrics
Deep dive into Strands Agents SDK's result.metrics to analyze cycle counts, token usage, and tool execution times. Compare how tool design choices impact performance and identify optimization targets.
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Strands Agents SDK Practical — Filter Agent I/O with Guardrails
Apply Bedrock Guardrails to Strands Agents SDK for automatic input/output filtering. Verify guardrail intervention behavior and implement shadow mode (monitor-only) using Hooks.
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Strands Agents SDK Practical — Control the Agent Loop with Hooks
Use Strands Agents SDK Hooks to intercept the agent loop. Log tool calls, limit invocation counts, and modify results with real code examples showing how to control agent behavior in real time.
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Strands Agents SDK Practical — Persist Conversations with Session Management
Use Strands Agents SDK's FileSessionManager to persist conversations to files and restore them after process restarts. Examine the stored data structure and the migration path to S3.
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Strands Agents SDK Practical — Type-Safe LLM Output with Structured Output
Use Strands Agents SDK's Structured Output to convert LLM responses into type-safe Pydantic objects. Verify tool integration, automatic validation retries, and conversation history extraction with code and metrics.
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AgentCore CLI in Practice — Build a Tech Trend Advisor with Key Features Combined
Combine Runtime, Memory, Gateway, and Evaluations into a single AgentCore CLI project to build a personalized tech trend advisor that remembers user expertise, searches the web for latest trends, and auto-measures response quality.
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AgentCore CLI in Practice — Measure Agent Quality with Evaluations
Hands-on verification of AgentCore CLI Evaluations with a custom LLM-as-a-Judge evaluator. Covers on-demand evaluation of agent traces, region constraints for the Evaluator CloudFormation resource, and trace indexing timing.
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AgentCore CLI in Practice — Connect External MCP Servers via Gateway
Hands-on verification of AgentCore CLI Gateway with an external MCP server target. Covers the critical project setup order, deployment-time connectivity checks, and the split between Gateway API and CloudFormation deployment.
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AgentCore CLI in Practice — Persist Conversation Memory Across Sessions
Hands-on verification of AgentCore CLI Memory with SEMANTIC, USER_PREFERENCE, SUMMARIZATION, and EPISODIC strategies. Covers async extraction timing, session ID constraints, and the gap between local dev and deployed behavior.
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AgentCore CLI in Practice — Deploy an AI Agent to AWS in Four Commands
Hands-on verification of the AgentCore CLI — from creating a Strands Agents project to local development, AWS deployment, and observability. CDK knowledge not required; initial deployment completes in about 90 seconds.
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Agentic AI on EKS — Multi-Agent Coordination with A2A
Validating A2A delegation from Travel Agent to Weather Agent on EKS. Two gotchas: agent card URL defaults to 0.0.0.0, and S3 session history poisons LLM context with stale URLs.
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Agentic AI on EKS — Deploying AI Agents
Hands-on validation of the AWS 'Agentic AI on EKS' workshop. Covers Strands Agents SDK, MCP-based tool auto-discovery, and building container images with Kaniko on EKS.
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Evaluating AI Agents with Strands Evals — Hands-on Testing of 6 Key Features
A practical walkthrough of Strands Evals' core features: deterministic checks, LLM-based scoring, multi-turn simulation, and auto-generated test cases. Includes gotchas discovered through real testing.
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Stream Agent Responses to UIs with Bedrock AgentCore Runtime AG-UI Protocol
Deploy an AG-UI protocol server to Bedrock AgentCore Runtime and stream real-time agent responses via SSE events. Hands-on walkthrough with agentcore CLI Direct Code Deploy.
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Strands Agents SDK Guide — Building a Team of Specialists with Multi-Agent
Coordinate multiple agents using the Agents as Tools pattern in Strands Agents SDK. Build a summarizer and translator as specialized agents, orchestrated by a coordinator — verified with real code and metrics.
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Strands Agents SDK Guide — Conversation Memory and Context Management
Explore multi-turn conversations and SlidingWindowConversationManager in Strands Agents SDK. See how agents remember past exchanges and what happens when the context window fills up — verified with real code.
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Strands Agents SDK Guide — Connecting External Tools with MCP
Connect MCP (Model Context Protocol) servers to Strands Agents SDK and extend your agent with external tools. Walk through the AWS documentation search MCP server hands-on, and combine MCP tools with custom @tool functions.
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Strands Agents SDK Guide — Custom Tool Design Patterns
Deep dive into Strands Agents SDK custom tools. Build multi-step tool chains, observe how the LLM handles tool errors gracefully, and control agent behavior with system prompts — all verified with real code and metrics.
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Strands Agents SDK Guide — Understanding the Agent Loop with Quickstart
Walk through the Strands Agents SDK Python Quickstart hands-on, explaining the agent loop, custom tools, and metrics with working code. A few dozen lines of Python is all it takes.
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Strands agent() hangs inside FastAPI async def endpoints
Strands Agents SDK's agent() is a blocking call. Calling it inside an async def FastAPI endpoint blocks the event loop and hangs the request. Switching to def fixes it.
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Cyclic Graph requires explicit set_entry_point
Strands Agents SDK Graph with cycles (feedback loops) fails build() auto-detection with ValueError. Use set_entry_point to specify the starting node explicitly.
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Graph's result.execution_time returns 0ms — use node sum instead
Strands Agents SDK Graph's result.execution_time returns 0ms. Per-node execution_time is correct, so calculate the total yourself.
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Swarm agents that hand off produce no text output
In Strands Agents SDK Swarm, agents that hand off via handoff_to_agent have no text block in their result. The final text output comes from the last agent that didn't hand off.
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Bedrock Guardrails automatically rewrites user input on block
When Bedrock Guardrails blocks a request in Strands Agents, the user input in conversation history is auto-replaced with [User input redacted.]. If user input disappears during debugging, this is why.
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Strands Agents Structured Output internally works as a tool
Pydantic models passed to structured_output_model appear as tools in metrics tool_usage. If you see an unfamiliar tool name during debugging, it's the Structured Output mechanism.
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A2A agent card URL defaults to 0.0.0.0 and breaks Kubernetes inter-pod communication
Strands SDK A2A server sets the card url to http://0.0.0.0:9000/ by default. Fix by setting a2a.http_url to the Kubernetes Service FQDN in Helm values.
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AI agent S3 session history poisons LLM decisions even after config changes
After fixing an A2A URL, the agent kept using the old one. Stale tool call results in S3 session history were restored into the LLM context. Fixed by clearing sessions.
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