AWS Case Studies: Solutions and Costs for Specific Projects

1. IoT Project (100,000 Sensors)

Context

An industrial monitoring system with:

• 100,000 sensors
• 1M data points/minute
• Real-time analysis
• Long-term storage

AWS Solution

• Ingestion: IoT Core

  • 100,000 devices
  • 1M messages/minute
  • Cost: ~$500/month

• Processing: Kinesis

  • 2 shards
  • 1M records/minute
  • Cost: ~$200/month

• Storage: Timestream

  • 1 TB of data/month
  • 30 days in memory
  • Cost: ~$300/month

• Visualization: QuickSight

  • 10 users
  • Cost: ~$100/month

Total Cost: ~$1,100/month

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2. ML Project (Prediction Model)

Context

A prediction system with:

• Monthly training
• 100 GB of data
• Real-time inference
• REST API

AWS Solution

• Training: SageMaker

  • ml.p3.2xlarge (GPU)
  • 20 hours/month
  • Cost: ~$600/month

• Inference: Lambda

  • 1M predictions/month
  • 1 GB of memory
  • Cost: ~$20/month

• Storage: S3

  • 100 GB of data
  • Cost: ~$3/month

• API: API Gateway

  • 1M requests/month
  • Cost: ~$5/month

Total Cost: ~$628/month

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3. Big Data Project (1 TB/Day)

Context

A data analytics system with:

• 1 TB of data/day
• Daily ETL
• Data warehouse
• Dashboards

AWS Solution

• Storage: S3

  • 30 TB/month
  • Cost: ~$750/month

• ETL: Glue

  • 30 jobs/month
  • 100 DPU-hours
  • Cost: ~$300/month

• Data Warehouse: Redshift

  • 2 nodes (dc2.large)
  • 1 TB of storage
  • Cost: ~$1,000/month

• Visualization: QuickSight

  • 20 users
  • Cost: ~$200/month

Total Cost: ~$2,250/month

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4. Gaming Project (100,000 Players)

Context

A multiplayer game with:

• 100,000 players
• 10,000 concurrent matches
• Matchmaking
• Leaderboards

AWS Solution

• Game Servers: GameLift

  • 100 instances
  • Auto Scaling
  • Cost: ~$3,000/month

• Matchmaking: Lambda

  • 1M matches/month
  • Cost: ~$20/month

• Database: DynamoDB

  • 50 GB of data
  • Provisioned mode
  • Cost: ~$200/month

• CDN: CloudFront

  • 50 TB of transfer/month
  • Cost: ~$1,000/month

Total Cost: ~$4,220/month

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Cost Comparison Table

Project Type	Main Solution	Monthly Cost	Key Points
IoT	IoT Core + Timestream	~$1,100	Scalability, real time
ML	SageMaker + Lambda	~$628	Performance, optimized cost
Big Data	Redshift + Glue	~$2,250	Volume, analytics
Gaming	GameLift + DynamoDB	~$4,220	Latency, scale

Tips for Optimizing Costs:

1. For IoT:

   • Use batch processing
   • Optimize Timestream retention
   • Compress your data
   • Use caching

2. For ML:

   • Use Spot Instances for training
   • Optimize model size
   • Use batch inference
   • Enable prediction caching

3. For Big Data:

   • Optimize your Redshift queries
   • Use S3 compression
   • Schedule your ETL jobs
   • Enable QuickSight caching

4. For Gaming:

   • Use Spot Instances
   • Optimize matchmaking
   • Enable DynamoDB caching
   • Use the CDN effectively

Key Takeaways:

For specific projects:

• Choose specialized services
• Optimize for usage peaks
• Monitor costs by component
• Use auto scaling wisely