Ojasa Mirai

Ojasa Mirai

Cloud

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Learning Level

🟢 Beginner🔵 Advanced
🔧 AWS Account Setup⚙️ AWS Compute Overview🖥️ EC2 Deployment🎯 Elastic Beanstalk⚡ Lambda Serverless📁 S3 Static Hosting🗄️ RDS Relational Database📊 DynamoDB NoSQL💾 ElastiCache Caching📊 AWS Monitoring🔑 AWS Authentication📈 AWS Scaling & Load Balancing🐳 AWS ECS Containers💰 AWS Cost Optimization
Cloud/Aws Deployment/Aws Monitoring

📊 AWS Monitoring - Advanced

Custom Metrics and Dashboards

# Put composite metric
aws cloudwatch put-metric-data \
  --namespace MyApp \
  --metric-data \
  file://metrics.json

Anomaly Detection

# Create anomaly detector
aws cloudwatch put-metric-anomaly-detector \
  --namespace AWS/EC2 \
  --metric-name CPUUtilization \
  --stat Average \
  --dimensions Name=InstanceId,Value=i-1234567890abcdef0

X-Ray Tracing

from aws_xray_sdk.core import xray_recorder

@xray_recorder.capture('ProcessOrder')
def process_order(order):
  return calculate_total(order)

Key Takeaways

  • **Custom metrics** track business KPIs
  • **Anomaly detection** identifies issues
  • **X-Ray** provides distributed tracing
  • **Automation** responds to alerts

Next Steps

Learn about advanced authentication and IAM patterns.


Resources

Python Docs

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