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Test The AWS Integration
This step tests the Kiro interactions with the remote AWS environment:
Compute
- 1 EC2 instance: i-03456018d00d13504 (t3.small, stopped)
- No active ECS clusters or EKS clusters running (stacks exist, clusters likely deleted)
Lambda
- AgentCore-mcpBedrockRustA-ApplicationAgentMcpServe-rWGgAcNdRUnH
S3 Buckets (5)
- bedrock-agentcore-runtime-... (us-west-2)
- cdk-hnb659fds-assets-... (CDK bootstrap)
- elasticbeanstalk-us-east-1-...
- my-adk-comic-artifacts
- xbill-test
CloudFormation Stacks (13 active)
- Multiple AgentCore-* stacks (Bedrock, ADK, MCP variants)
- eksctl-* stacks for 3 EKS clusters (mcp-eks, adkui-eks, biometric-scout) — infrastructure stacks remain even if clusters
are torn down
- CDKToolkit bootstrap
ECR Repositories (33)
- Heavy focus on AI agent workloads: course creator pipelines (orchestrator, researcher, content-builder, judge), MCP
servers, ADK agents, biometric-scout
- Both Python and Rust MCP server variants
No active: RDS, EKS clusters, ECS, Elastic Beanstalk environments
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The environment is clearly an AI agent development platform — experimenting with Bedrock AgentCore, ADK (Agent Development
Kit), and MCP (Model Context Protocol) server patterns, with both Python and Rust implementations.
So Why? Just Why? Why Mix and Match Cloud Setups?
Kiro was used to summarize the advantages of the approach:
summarize the benefits of using Kiro from the Google Cloud Shell
Based on your specific environment — an AI agent developer working across GCP and AWS from Cloud Shell — here's where Kiro
adds real value:
Cross-Cloud Visibility in One Place
You just saw this: Kiro can summarize your GCP project and AWS environment in a single conversation, correlating context
across both clouds without switching tools or consoles.
Codebase Intelligence
Cloud Shell gives you a terminal; Kiro gives you a coding partner. For your agent repos (ADK, MCP servers, Bedrock
AgentCore), Kiro can read, understand, and modify code across files — not just run commands.
Infrastructure as Code Assistance
With 13 CloudFormation stacks and CDK in use, Kiro can help write, debug, and refactor IaC — understanding the intent
behind stacks like eksctl-adkui-eks-cluster rather than just listing them.
Agentic Workflows Without Context Switching
You're building AI agents. Kiro can help you design, implement, and deploy them — writing the Cloud Run service configs,
Dockerfiles, Lambda handlers, and Bedrock agent definitions — all from the same shell session where you're already
working.
Persistent Task Execution
Unlike a plain terminal, Kiro tracks multi-step tasks, catches errors, and adapts — useful when deploying across regions
(your us-central1 / us-east4 Cloud Run pattern) or debugging failed services like gpu-31b-l4-devops-agent.
No Extra Tooling
Cloud Shell already has gcloud, aws, docker, git, and python — everything Kiro needs. There's nothing to install; you get
AI-assisted development on top of the environment you already have.
Summary
The Google Cloud Shell and Cloud Shell Terminal provides an environment for rapid prototyping Agentic development. With some configuration and customization- it provides core functionality cross cloud using the Kiro CLI.