Devops AI Agent

DevOps人工智能代理

构建在以下基础上的智能DevOps代理 AWS基岩代理核心 使用 模型上下文协议（MCP） 通过Microsoft Teams管理AWS基础架构、监控资源运行状况和报告事件。

建筑

flowchart LR
    subgraph Triggers
        CW[CloudWatch Alarm] --> EB[EventBridge Rule]
        EB --> LH[Lambda Handler]
    end

    subgraph Agent
        LH --> AC[AgentCore\nReasoning Loop]
        AC --> MC[MCP Client]
    end

    subgraph MCP Servers
        MC --> AWS[AWS Infra Server\nEC2 tools]
        MC --> MON[Monitoring Server\nCloudWatch tools]
        MC --> TMS[Teams Server\nWebhook tools]
    end

    AWS --> EC2[(EC2)]
    MON --> CWM[(CloudWatch\nMetrics)]
    TMS --> TEA[(Teams\nWebhook)]

快速开始

# 1. Create & activate virtual environment
python -m venv .venv
.venv\Scripts\activate          # Windows PowerShell
source .venv/bin/activate       # Linux / macOS

# 2. Install dependencies (dev + infra extras)
make install
# or manually:
pip install -e ".[dev,infra]"

# 3. Run linter & type checker
make lint
make typecheck

# 4. Run tests
make test

# 5. Start an MCP server locally (stdio transport)
make run-mcp-aws

CDK部署

先决条件

# Install the CDK CLI (one-time)
npm install -g aws-cdk

# Bootstrap CDK in your account/region (one-time)
cdk bootstrap aws://650251690796/ap-southeast-2

部署所有堆栈

# Activate venv first
.venv\Scripts\activate

# Deploy everything (Networking → Monitoring → Runner)
cdk deploy --all --require-approval never

部署单个堆栈

# Monitoring stack (CloudWatch alarm + EventBridge rule)
cdk deploy DevOpsAgent-Monitoring --require-approval never

# Agent Runner stack (Lambda function)
cdk deploy DevOpsAgent-Runner --require-approval never

其他CDK命令

# Synthesize CloudFormation templates (no deploy)
cdk synth

# Show diff between deployed and local
cdk diff

# Destroy all stacks
cdk destroy --all

CDK上下文(cdk.json)

以下上下文值配置部署：

测试Lambda

使用测试事件调用

CloudWatch警报事件示例见 test_event.json:

aws lambda invoke \
  --function-name devops-ai-agent-handler \
  --payload fileb://test_event.json \
  --cli-binary-format raw-in-base64-out \
  response.json \
  --region ap-southeast-2

查看响应

# Linux / macOS
cat response.json | python -m json.tool

# Windows PowerShell
Get-Content response.json | python -m json.tool

预期成功响应

{
  "statusCode": 200,
  "body": {
    "alarm_name": "devops-agent-high-cpu",
    "instance_id": "i-0bf11b006e8f12844",
    "agent_response": "...",
    "tool_calls_count": 3,
    "session_id": "..."
  }
}

运行测试

# All tests
make test
# or: pytest -v

# Unit tests only
make test-unit
# or: pytest tests/unit/ -v

# Integration tests only
make test-integration
# or: pytest tests/integration/ -v

装订和格式化

# Lint (check only)
make lint

# Auto-format + fix
make format

# Type check with mypy
make typecheck

在本地运行MCP服务器

make run-mcp-aws          # AWS Infra server (EC2 tools)
make run-mcp-monitoring   # Monitoring server (CloudWatch tools)
make run-mcp-teams        # Teams server (webhook tools)

基岩模型验证

# List available models
aws bedrock list-foundation-models \
  --region ap-southeast-2 \
  --by-provider Anthropic \
  --query "modelSummaries[].modelId" \
  --output json

# Test direct model invocation
aws bedrock-runtime invoke-model \
  --model-id "amazon.nova-lite-v1:0" \
  --region ap-southeast-2 \
  --body '{"inputText":"hello"}' \
  --content-type application/json \
  response_model.json

# Test inline agent from Python
python -c "
import boto3
c = boto3.client('bedrock-agent-runtime', region_name='ap-southeast-2')
r = c.invoke_inline_agent(
    foundationModel='amazon.nova-lite-v1:0',
    instruction='You are a helpful DevOps assistant that diagnoses infrastructure issues.',
    sessionId='test-123',
    inputText='Say hello',
)
print([e for e in r['completion']])
"

清理

# Remove Python caches and build artifacts
make clean

# Destroy all deployed AWS resources
cdk destroy --all

目录结构

devops-ai-agent/
├── infra/                        # IaC (CDK stacks)
│   ├── stacks/
│   │   ├── monitoring_stack.py   # CloudWatch alarms, EventBridge rules
│   │   ├── agent_runner_stack.py # Lambda for agent invocation
│   │   └── networking_stack.py   # VPC, subnets, security groups
│   └── app.py
├── src/
│   ├── agent/
│   │   ├── agent_core.py         # AgentCore client & reasoning bridge
│   │   ├── system_prompt.py      # Agent persona & instructions
│   │   └── config.py             # Env-based settings (Pydantic)
│   ├── mcp_servers/
│   │   ├── aws_infra/            # MCP server: EC2 tools
│   │   ├── monitoring/           # MCP server: CloudWatch metrics
│   │   └── teams/                # MCP server: Teams webhook
│   ├── mcp_client/
│   │   └── client.py             # Unified MCP client adapter
│   ├── handlers/
│   │   ├── lambda_handler.py     # EventBridge → Agent entry point
│   │   └── event_parser.py       # Alarm event → typed dataclass
│   └── utils/
│       ├── aws_helpers.py        # Shared boto3 helpers
│       └── teams_webhook.py      # Low-level webhook HTTP helper
├── tests/
├── demo.py                       # 🚀 Interactive demo — see below
├── pyproject.toml
├── Makefile
└── README.md

演示/帮助脚本

跑吧 demo.py 每个模块的指导性演练脚本：

python demo.py

它将：

1. 展示如何加载配置
2. 演示MCP工具发现和调用（模拟）
3. 模拟EventBridge报警事件解析
4. 模拟团队通知
5. 展示完整的代理端到端推理流程

先决条件

环境变量

内联模式与注册模式： 当 AGENT_ID 和 AGENT_ALIAS_ID 两者都已设置，代理将使用 invoke_agent （预先注册）。如果省略，则使用 invoke_inline_agent （在每个请求中内联发送系统提示和工具）。

许可证

麻省理工学院