Tag: rdbms

Sensing Data

Posted on by lechuck park

From Claude with some prompting
This image is a diagram showing the data processing flow from TSDB (Time Series Database) to RDBMS (Relational Database Management System). Let me explain the main components and processes:

  1. Data Collection Stage:
  • Analog to Digital (conversion from analog to digital)
  • Time (time information)
  • Meta data
    These three elements combine to generate Time Series Data.
  1. ETL (Extract, Transform, Load) Processing: Data is processed through two paths:
  • Upper path:
  • Easy Calculation
  • Shorter Time Range
  • Stored in Time Series Database
  • Lower path:
  • Complex & Programmatic processing
  • Bigger Time Range
  • Stored in Relational Database
  1. Final Data Utilization:
  • Raw Data → Realtime Monitoring
  • Analyzed Data → Monitoring & Prediction

This diagram explains the overall data pipeline showing how time series data is collected, processed, and ultimately utilized for real-time monitoring and predictive analysis.

WEB SERVICE 3-TIERS

Posted on by lechuck park

From Claude with some prompting
WEB(Front) Layer

  • Primary Components:
    • Static Data: HTML, CSS, JavaScript files
    • Storage: Browser-based storage solutions
  • Performance Optimization:
    • CDN: Global content delivery
    • Caching: Response time improvement
  • Enhanced Custom Experience:
    • Optimized user interface
    • Client-side performance enhancements
  1. WAS(Back) Layer
  • Core Functions:
    • Program Code: Server-side application logic
    • Computing: Business process handling
  • Development Features:
    • Enhanced Development Environment (CI/CD):
      • Continuous Integration for automated testing
      • Continuous Deployment for automated delivery
      • Automated build and release processes
      • Development workflow optimization
    • Biz Logic: Business rules implementation
    • Microservices: Modular service architecture
  1. DB Layer
  • Data Management:
    • Dynamic Data: Real-time data processing
    • Variable(Memory): Memory-based data handling
  • Business Data:
    • Biz Data Scheme & ACID:
      • Data structure and relationships
      • Transaction integrity
      • Data consistency
    • RDBMS/NoSQL: Flexible database solutions
  1. Infrastructure Characteristics
  • High Availability (Biz Continues):
    • Uninterrupted service operation
    • Fault tolerance
    • Business continuity
  • Scalability (Biz Changes):
    • System expansion capability
    • Business growth support
    • Flexible architecture
  1. Key Integration Points
  • WEB ↔ WAS: Static data and program code interaction
  • WAS ↔ DB: Dynamic data and business logic connection
  • Biz Logic ↔ Biz Data: Direct business data operations

This architecture demonstrates a modern, well-structured web service that emphasizes:

Robust business logic handling
Efficient data management
Clear separation of concerns
Automated development processes
Scalable infrastructure
High availability
Enhanced user experience