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.
Content tagged with "bedrock"
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.
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.
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.
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.
Tested Stateful MCP's 3 capabilities with a DynamoDB-backed expense tracker. Verified data integrity on Elicitation decline/cancel and fallback behavior on Sampling failure to provide production design guidance.
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.
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.
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.
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.
Verified Agent Registry end-to-end: registry creation, record registration, approval workflow, and hybrid search via CLI. Measured semantic search accuracy, Japanese vs English query differences, and MCP endpoint consistency.
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.
Apply Bedrock Guardrails to Strands Agents SDK for automatic input/output filtering. Verify guardrail intervention behavior and implement shadow mode (monitor-only) using 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.
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.
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.
SAM deployment gotchas, local testing with LocalDurableTestRunner, and execution history tracking from hands-on experience. The qualified ARN requirement is the first hurdle.
Verified idempotency, DurableExecutionName, parallel callbacks, and timeout configuration hands-on. The common principle: design everything assuming replay will happen.
Deployed the official AWS fraud detection demo and verified 3 risk-score branches with suspend behavior. Confirmed zero compute charges during checkpoint-and-replay waits.
A deep dive into the AWS Security Blog's agentic AI security framework for financial services. Reorganizes the 7 design principles into three axes—permissions, traceability, and controls—with Bedrock AgentCore implementation guidance.
Hands-on verification of the AI-powered A/B testing engine from the AWS blog — implementing context-dependent variant selection with Bedrock Converse API tool use. Discovered that omitting context from the prompt reverses the variant choice, highlighting prompt design as the critical factor.
Hands-on verification of AgentCore Runtime's new managed session storage. Tested file restoration after stop/resume, pip/git workspace persistence, session isolation, and graceful shutdown behavior with real measurement data.
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.
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.
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.
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.
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.
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.
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.
Deploy a bidirectional voice streaming agent using AgentCore Runtime's new WebRTC support with Nova Sonic. Key finding: TURN-only mode is strongly recommended for AgentCore Runtime deployments.
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.
Hands-on verification of AgentCore Code Interpreter's S3 integration and PUBLIC mode. Covers direct pip install, S3 wheel offline installation, sys.path import, and cross-session persistence behavior.
Hands-on verification of AgentCore Runtime's new shell command API. Covers HTTP/2 streaming, in-session file persistence, cross-session microVM isolation, and concurrent execution behavior.
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.
Hands-on verification of Bedrock AgentCore Policy: Cedar-based tool access control via Gateway, natural language policy generation, and default deny behavior validated with real API calls.
Hands-on verification of AgentCore Memory Record Streaming. Covers Kinesis push delivery, FULL_CONTENT vs METADATA_ONLY behavior, and async extraction events with real test data.
Verifying AgentCore Runtime's new stateful MCP features. Tested elicitation (server-initiated input), sampling (LLM generation requests), and progress notifications both locally and on AgentCore.
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.
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.
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.
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.
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.
Strands Agents SDK Graph with cycles (feedback loops) fails build() auto-detection with ValueError. Use set_entry_point to specify the starting node explicitly.
Strands Agents SDK Graph's result.execution_time returns 0ms. Per-node execution_time is correct, so calculate the total yourself.
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.
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.
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.
With 3 tool types and 4 total calls needed in Bedrock Converse API tool use, the model requested all 4 in a single response instead of calling them sequentially. The implementation must handle multiple toolUse blocks per turn.
agentcore remove all --force only resets local config files. AWS resources remain until you run agentcore deploy to apply the empty state.
AgentCore Runtime's ENI in the VPC may stay in-use for hours after agentcore destroy. Wait for it to become available before deleting the subnet and VPC.
Foundation Model ARNs use arn:aws:bedrock:region::foundation-model/... with no account ID. Replacing the ACCOUNT_ID placeholder from samples breaks the IAM policy.
Mixing up bedrock-agentcore-control (create/delete) and bedrock-agentcore (session ops/code execution) gives you an AttributeError.
Uploading a raw Python file to S3 for create-agent-runtime gives 'S3 object must be in .zip format' ValidationException. You must zip the code first.
The docs say 'Stateless between commands' but the filesystem is actually shared within a session. Only shell history and environment variables are reset.
Setting entryPoint to ['python3', 'main.py'] in codeConfiguration gives 'Invalid entrypoint value' error. For Python runtimes, pass only the filename with .py extension like ['main.py'].
agentcore deploy emits 'X-Ray Delivery Destination is supported with CloudWatch Logs as a Trace Segment Destination' during memory creation, but the runtime phase auto-configures it.
agentcore configure with Direct Code Deploy fails with 'Direct Code Deploy deployment unavailable (uv not found)'. Fix with pip install uv — not mentioned in the official docs.
Creating a Cedar permit without a when clause in Bedrock AgentCore Policy fails with CREATE_FAILED due to FAIL_ON_ANY_FINDINGS automated reasoning.
Bedrock AgentCore Gateways only allow hyphens while Policy Engines only allow underscores. Using the same prefix for both causes ValidationException.
batch-update-memory-records requires timestamp, and memory-strategies uses semanticMemoryStrategy / namespaceTemplates — not what the docs suggest.