🌐 vBASK DataMesh Architecture

Ultra-Low Latency Real-Time Skill Inferencing Platform

Powered by DataMesh, CloudFront, Local Zones, Wavelength & Outposts

🎯 DataMesh-Driven Skill Intelligence Platform

vBASK leverages AWS DataMesh architecture to create a decentralized, domain-driven data platform that delivers real-time skill assessment and personalized learning recommendations with ultra-low latency across global edge locations.

DataMesh Core Principles:
  • Domain-oriented decentralized data ownership
  • Data as a product with self-serve infrastructure
  • Federated computational governance
  • Real-time skill data products and APIs
  • Distributed edge inference capabilities
  • Autonomous skill domain management

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🏗️ DataMesh & Edge Computing Architecture

📊 View High-Level Architecture: High-Level Architecture(on AWS)

vBASK Distributed DataMesh Architecture

Skill Domains
DataMesh
→
Data Products
APIs
→
CloudFront
Global CDN
→
Edge Zones
Local/Wavelength
→
Outposts
On-Premises
DataMesh Layer: Domain-driven skill data products with federated governance and self-serve analytics
Global Edge Layer: CloudFront with 400+ edge locations for data product delivery
Metro Edge Layer: Local Zones for sub-10ms skill inference processing
5G Edge Layer: Wavelength zones for <5ms mobile skill assessment
Enterprise Edge: AWS Outposts for <1ms on-premises skill analytics
Core Services: Lake Formation, Glue DataBrew, SageMaker, Lambda, DynamoDB

🔄 DataMesh Skill Domains

👨‍💻 Technical Skills Domain

Data Products:

  • Programming language proficiency APIs
  • Framework expertise datasets
  • Certification tracking services
  • Code quality assessment models

🤝 Soft Skills Domain

Data Products:

  • Communication assessment APIs
  • Leadership capability models
  • Teamwork evaluation services
  • Emotional intelligence datasets

🏢 Industry Skills Domain

Data Products:

  • Sector-specific competency APIs
  • Regulatory knowledge datasets
  • Market trend analysis services
  • Industry benchmark models

📈 Career Progression Domain

Data Products:

  • Career path recommendation APIs
  • Salary prediction models
  • Job market analysis services
  • Skills gap identification datasets

⚡ Edge Computing Services

🌐 Amazon CloudFront

DataMesh Integration: Global data product delivery

Tachyon Use Cases:

  • Skill data product API acceleration
  • ML model artifact distribution
  • Real-time analytics dashboards
  • Edge-cached skill assessments
  • Lambda@Edge data transformations

Latency: 50-100ms globally

🏙️ AWS Local Zones

DataMesh Integration: Metro-area data processing

Tachyon Use Cases:

  • Real-time skill inference engines
  • Local data product processing
  • Interactive skill simulations
  • Video-based competency analysis
  • Live mentoring data streams

Latency: 5-10ms in metro areas

📱 AWS Wavelength

DataMesh Integration: 5G edge data products

Tachyon Use Cases:

  • Mobile skill assessment apps
  • AR/VR training data streams
  • IoT skill tracking devices
  • Real-time collaboration analytics
  • Edge ML model inference

Latency: 1-5ms for 5G users

🏢 AWS Outposts

DataMesh Integration: On-premises data sovereignty

Tachyon Use Cases:

  • Enterprise skill data lakes
  • Sensitive HR analytics
  • Compliance-driven processing
  • Hybrid data product delivery
  • Local governance enforcement

Latency: <1ms on-premises

🎯 Real-Time DataMesh Inference Pipeline

Skill Assessment DataMesh Flow

User Input
Multi-Domain
→
Data Products
Federation
→
Edge Processing
Local/Wavelength
→
ML Inference
Distributed
→
Real-time Results
Global Delivery
Data Product Discovery: AWS Glue Data Catalog, Lake Formation, DataZone
Federated Governance: IAM, Lake Formation permissions, Data lineage
Self-Serve Analytics: QuickSight, Athena, SageMaker Studio
Edge Inference: SageMaker Edge, Lambda@Edge, Container instances
Real-time Delivery: API Gateway, WebSocket, Server-Sent Events

📊 DataMesh Performance & Benefits

🔄 Data Product Scalability

10x

Faster data product development

  • Domain-driven autonomous teams
  • Self-serve data infrastructure
  • Federated computational governance

⚡ Ultra-Low Latency

< 5ms

Real-time skill inference response

  • Wavelength: 1-5ms for 5G users
  • Local Zones: 5-10ms metro areas
  • Outposts: <1ms on-premises

💰 Cost Optimization

70%

Reduction in data infrastructure costs

  • Decentralized data ownership
  • Edge processing efficiency
  • Automated data lifecycle management

🚀 DataMesh Scalability Metrics

  • Data Products: 100+ autonomous skill data products
  • Concurrent Users: 5M+ simultaneous skill assessments
  • Throughput: 500K+ inferences per second across domains
  • Data Freshness: Real-time streaming with <1 second latency
  • Global Reach: 400+ CloudFront edge locations

📈 Business Impact

  • Time to Market: 80% faster data product delivery
  • Data Quality: 99.9% accuracy with automated governance
  • Developer Productivity: 5x improvement in data team efficiency
  • User Experience: 95% improvement in response time
  • Cost Savings: 70% reduction in data infrastructure costs

🛠️ DataMesh Implementation Strategy

Phase 1: Domain Identification

  • Map skill assessment domains
  • Define data product boundaries
  • Establish domain ownership
  • Create governance framework

Phase 2: Data Product Development

  • Build self-serve data platform
  • Implement data product APIs
  • Deploy federated governance
  • Enable data discovery catalog

Phase 3: Edge Integration

  • Deploy CloudFront distribution
  • Configure Local Zone processing
  • Implement Wavelength inference
  • Set up Outposts connectivity

Phase 4: Optimization

  • Monitor data product performance
  • Optimize edge caching strategies
  • Implement auto-scaling policies
  • Enhance governance automation

🔒 DataMesh Security & Governance

🛡️ Federated Security Framework

  • Domain-Level Security: IAM roles per skill domain with fine-grained permissions
  • Data Product Encryption: End-to-end encryption with domain-specific KMS keys
  • Federated Governance: Automated policy enforcement across all domains
  • Data Lineage: Complete traceability of skill data products
  • Privacy Controls: GDPR, CCPA compliance with automated data handling
  • Edge Security: Zero-trust architecture across all edge locations

💡 DataMesh Use Case Scenarios

🎓 Educational DataMesh

Decentralized student skill data products

  • Academic performance data products
  • Learning analytics APIs
  • Competency tracking services
  • Real-time progress dashboards

🏢 Enterprise Skill DataMesh

Autonomous HR and talent data products

  • Employee skill inventory APIs
  • Training effectiveness datasets
  • Performance prediction models
  • Career development analytics

🤝 Recruitment DataMesh

Federated talent matching data products

  • Candidate assessment APIs
  • Job-skill compatibility services
  • Market salary datasets
  • Interview analytics models

📱 Mobile Learning DataMesh

Edge-delivered learning data products

  • Micro-learning content APIs
  • AR/VR skill simulation data
  • Peer learning analytics
  • Mobile assessment services

🔬 Data Science in Key Technologies

🤖 Machine Learning Stack

  • SageMaker: End-to-end ML lifecycle management
  • TensorFlow/PyTorch: Deep learning frameworks
  • Scikit-learn: Classical ML algorithms
  • XGBoost: Gradient boosting for skill prediction
  • Hugging Face: NLP transformers for text analysis

📊 Data Processing & Analytics

  • Apache Spark: Distributed data processing
  • Pandas/NumPy: Data manipulation and analysis
  • AWS Glue: ETL and data cataloging
  • Athena: Serverless SQL analytics
  • QuickSight: Business intelligence dashboards

🧠 AI/ML Models

  • Skill Classification: Multi-class neural networks
  • Recommendation Engine: Collaborative filtering
  • NLP Processing: BERT/GPT for text understanding
  • Computer Vision: CNN for image-based assessments
  • Time Series: LSTM for career progression

📈 Real-time Analytics

  • Kinesis: Real-time data streaming
  • Lambda: Serverless data processing
  • DynamoDB: NoSQL for fast skill lookups
  • ElastiCache: In-memory caching layer
  • CloudWatch: Monitoring and alerting

🎯 Data Science Workflow

Data Ingestion
Kinesis/S3
→
Feature Engineering
Glue/Spark
→
Model Training
SageMaker
→
Model Deployment
Edge Inference
→
Real-time Scoring
Lambda/API

🎯 ROI & Business Value

📈 DataMesh Expected Returns

  • Agility: 10x faster data product development and deployment
  • Scalability: Support for 100+ autonomous skill domains
  • Performance: Sub-5ms global skill inference response times
  • Cost Efficiency: 70% reduction in data infrastructure costs
  • Innovation: Self-serve analytics enabling rapid experimentation
  • Governance: Automated compliance across all skill domains
  • Quality: 99.9% data accuracy with federated quality controls

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