Monitoring Agents in Production

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import boto3
from datetime import datetime

cloudwatch = boto3.client('cloudwatch')

def emit_agent_metrics(agent_id: str, invocation_data: dict):
    """Emit comprehensive agent metrics to CloudWatch."""
    
    timestamp = datetime.utcnow()
    
    metrics = [
        # Operational metrics

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import boto3
from datetime import datetime
from dataclasses import dataclass
from typing import List, Dict, Optional
import json

@dataclass
class AgentMetrics:
    request_id: str
    agent_type: str
    llm_calls: List[Dict]
    tool_calls: List[Dict]

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import json
import logging
import uuid
from datetime import datetime
from typing import Any, Dict, Optional
from contextlib import contextmanager
import time

class AgentLogger:
    def __init__(self, agent_type: str, request_id: Optional[str] = None):
        self.agent_type = agent_type
        self.request_id = request_id or str(uuid.uuid4())

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import boto3
import time
import json
import uuid
from aws_xray_sdk.core import xray_recorder, patch_all
from functools import wraps
from typing import Any, Dict, Optional
from dataclasses import dataclass, asdict
from datetime import datetime

patch_all()

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import * as cdk from 'aws-cdk-lib';
import * as cloudwatch from 'aws-cdk-lib/aws-cloudwatch';

export class AgentDashboardStack extends cdk.Stack {
  constructor(scope: cdk.App, id: string, props?: cdk.StackProps) {
    super(scope, id, props);
    
    const namespace = 'AIAgents/production';
    const agentTypes = ['research', 'analysis', 'synthesis', 'orchestrator'];
    
    // Create metrics for each agent type
    const createAgentMetric = (agentType: string, metricName: string, stat: string = 'Average') => {

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import boto3
import json
import os
from datetime import datetime, timedelta

cloudwatch = boto3.client('cloudwatch')
logs = boto3.client('logs')
xray = boto3.client('xray')
s3 = boto3.client('s3')
sns = boto3.client('sns')

def lambda_handler(event, context):