Phase 2 · Ship to AgentCore
Ship the agent
You build the agent. The platform handles the cloud. Each stage is one command. up N provisions everything up to task N; a lower N switches later tasks off again. Your work is the app: agent code, prompts, tools, memory use, config and tests.
0 of 8 tasks complete
Your toolbox
uv run bootcamp.py up 4 # provision stages 0..4
uv run bootcamp.py deploy # ship your edited agent / MCP code
uv run bootcamp.py status # ids: POOL_ID, GATEWAY_ID, MEMORY_ID, ...
uv run bootcamp.py test --only 4 # check one stage (or: test 4 for 0..4)
uv run bootcamp.py invoke "Hi" --actor alice-chen
uv run bootcamp.py token # bearer token for manual calls
uv run bootcamp.py llm # gateway URL, models, budget spent / max
uv run bootcamp.py down # remove your whole stackbootcamp/. test N checks stages 0 to N; test --only N just one.Stages at a glance
| Stage | The platform provisions | Check | What passing proves |
|---|---|---|---|
| 0 | Cognito identity | test --only 0 | M2M token is issued; keyless LiteLLM identity works; direct Bedrock is denied |
| 1 | MCP server on AgentCore Runtime, JWT inbound | test --only 1 | tools/list and a SELECT work |
| 2 | AgentCore Gateway, OAuth provider, semantic search | test --only 2 | Gateway lists DataStreamDatabase___query_db |
| 3 | AgentCore Memory, UserFacts strategy | test --only 3 | Memory is ACTIVE |
| 4 | Agent runtime wired to Gateway, Memory, LiteLLM | test --only 4 | Agent answers, recalls across sessions, spend lands on your budget |
| 5 | Observability (traces in CloudWatch) | test --only 5 | Spans arrive (can take ~10 min) |
| 6 | Online evaluations | test --only 6 | Config is ACTIVE |
| 7 | Cedar policy on the Gateway | test --only 7 | SELECT allowed, DELETE denied |
Tasks
Identity with Cognito
Get a machine-to-machine token so everything you deploy can prove who is calling.
The “Enterprise Readiness” challenge
1MCP server on AgentCore Runtime
Your Phase 1 MCP server goes to the cloud behind JWT auth. You own its tools.
The “Tool Server Deployment” challenge
2AgentCore Gateway
Put a single, governed front door in front of your tools, with semantic tool search.
The “Tool Discovery” challenge
3AgentCore Memory
Long-term, per-user memory that learns facts across sessions and keeps users apart.
The “Remember Me, Not Jordan” crisis
4Your agent on AgentCore Runtime
Deploy the Phase 1 orchestrator, wired to Gateway, Memory and LiteLLM. This is where you code.
The “Agent Deployment and Tool Access” challenge
5Observability
See every model call, tool call and millisecond your agent spends, without adding code.
The “Black Box” panic
6Online evaluations
Score live traffic for helpfulness, goal success and correctness with LLM-as-a-judge.
The “Quality Crisis” panic
7Cedar policy on the Gateway
Enforce SELECT-only at the Gateway, so no prompt or code change can delete data.
The “Runaway Query” nightmare
Optional add-ons
For fast finishers: switch on an AgentCore built-in tool with one .env flag and teach your agent to use it.
0 of 2 optional add-ons complete
Optional: Code Interpreter
Give the agent a sandboxed Python environment so it computes answers instead of guessing at arithmetic.
The “Numbers, Not Prose” request
+Optional: Browser
Let the agent read public web pages through a managed, sandboxed headless browser.
The “What Are Competitors Doing?” request