# Architecture overview This chapter provides a high-level overview of the Automotive Data Platform architecture, including the three integrated solutions and their deployment options. ![Automotive Data Platform Architecture Overview](http://docs.aws.amazon.com/guidance/latest/automotive-data-platform-on-aws/images/mesh.png) ## Solution Components The Automotive Data Platform consists of four integrated solutions that can be deployed independently or together: ### Automotive Data Mesh A domain-oriented decentralized data architecture with centralized governance using [Amazon SageMaker Unified Studio](https://aws.amazon.com/sagemaker/unified-studio/) and [Amazon DataZone](https://aws.amazon.com/datazone/). This foundation enables cross-domain collaboration, data product discovery, and federated governance across all automotive data domains. **Key capabilities**: Data product catalog, self-service data access, automated lineage tracking, federated governance, and collaborative workspaces. ### Customer 360 Analytics Unify customer data from CRM, service, telemetry, and external sources to create comprehensive customer profiles. Enable AI-powered insights through natural language queries using [Amazon Bedrock](https://aws.amazon.com/bedrock/) agents and interactive dashboards with [Amazon QuickSight](https://aws.amazon.com/quicksight/). **Key capabilities**: Entity resolution, unified customer profiles, AI-powered analytics, and real-time dashboards. ### Predictive Maintenance Predict vehicle component failures using machine learning models trained on connected vehicle telemetry. Enable proactive service scheduling to reduce downtime and improve customer satisfaction using [Amazon SageMaker](https://aws.amazon.com/sagemaker/) and [AWS IoT Core](https://aws.amazon.com/iot-core/). **Key capabilities**: Real-time telemetry ingestion, ML-based failure prediction, proactive service alerts, and dealer integration. ### Automotive Data Governance Implement comprehensive data governance with automated PII detection, multi-region compliance, and fine-grained access control using [AWS Lake Formation](https://aws.amazon.com/lake-formation/) and [Amazon Macie](https://aws.amazon.com/macie/). Support GDPR, CCPA, and regional data residency requirements. **Key capabilities**: Automated PII classification, policy-based access control, cross-region governance, and compliance monitoring. ## High-Level Architecture The Automotive Data Platform consists of six layers that work together to provide comprehensive data management, analytics, and AI capabilities: ### 1. Data Sources Layer **Internal Systems**: + CRM platforms (Salesforce, Microsoft Dynamics) + ERP systems (SAP, Oracle) + Dealer management systems + Service management platforms + Finance and billing systems + Collaboration tools **External Systems**: + Connected vehicle telemetry (IoT Core, MQTT) + Warranty claims databases + Social media sentiment feeds + Third-party market data + Supply chain systems + Sales and inventory data ### 2. Data Ingestion Layer **Real-Time Streaming**: + [AWS IoT Core](https://aws.amazon.com/iot-core/) for vehicle telemetry (MQTT, X.509 mTLS) + [Amazon Kinesis Data Streams](https://aws.amazon.com/kinesis/data-streams/) for high-throughput ingestion + [Amazon MSK](https://aws.amazon.com/msk/) (Managed Streaming for Apache Kafka) for event streaming + AWS IoT Core Basic Ingest with direct MSK integration **Near Real-Time APIs**: + [Amazon API Gateway](https://aws.amazon.com/api-gateway/) for transactional updates + [AWS Lambda](https://aws.amazon.com/lambda/) for event-driven processing + [Amazon EventBridge](https://aws.amazon.com/eventbridge/) for event routing **Batch Processing**: + [AWS Glue](https://aws.amazon.com/glue/) ETL for scheduled data loads + [Amazon Data Firehose](https://aws.amazon.com/firehose/) for S3 delivery + [AWS DataSync](https://aws.amazon.com/datasync/) for on-premises data transfer + [AWS Transfer Family](https://aws.amazon.com/aws-transfer-family/) for SFTP/FTPS ingestion ### 3. Data Storage and Governance Layer **Data Lake Storage**: + [Amazon S3](https://aws.amazon.com/s3/) for scalable object storage + Parquet files for columnar analytics + Apache Iceberg tables for ACID transactions + Vector embeddings for semantic search **Metadata and Governance**: + [AWS Glue Data Catalog](https://aws.amazon.com/glue/) for centralized metadata + [AWS Lake Formation](https://aws.amazon.com/lake-formation/) for fine-grained access control + [Amazon DataZone](https://aws.amazon.com/datazone/) for data discovery and lineage + [AWS Glue Data Quality](https://aws.amazon.com/glue/) for validation rules **Security and Compliance**: + [AWS IAM](https://aws.amazon.com/iam/) for access control + [AWS CloudTrail](https://aws.amazon.com/cloudtrail/) for audit logging + [Amazon Macie](https://aws.amazon.com/macie/) for PII detection + [AWS Security Hub](https://aws.amazon.com/security-hub/) for security monitoring + [AWS KMS](https://aws.amazon.com/kms/) for encryption key management ### 4. Data Processing Layer **Batch Processing**: + [AWS Glue ETL](https://aws.amazon.com/glue/) for data transformation + AWS Glue crawlers for schema discovery + [Amazon EMR](https://aws.amazon.com/emr/) for large-scale processing + [AWS Step Functions](https://aws.amazon.com/step-functions/) for workflow orchestration **Stream Processing**: + [Amazon Managed Service for Apache Flink](https://aws.amazon.com/managed-service-apache-flink/) for real-time analytics + [AWS Lambda](https://aws.amazon.com/lambda/) for event-driven transformations + [Amazon Kinesis Data Analytics](https://aws.amazon.com/kinesis/data-analytics/) for SQL-based streaming **Entity Resolution**: + [AWS Entity Resolution](https://aws.amazon.com/entity-resolution/) for customer deduplication + [AWS Glue DataBrew](https://aws.amazon.com/glue/features/databrew/) for data preparation + Custom Lambda functions for business logic **ML Training and Inference**: + [Amazon SageMaker](https://aws.amazon.com/sagemaker/) for model training + SageMaker Pipelines for ML workflows + SageMaker endpoints for real-time inference + SageMaker batch transform for bulk predictions ### 5. Analytics and AI Layer **SQL Analytics**: + [Amazon Athena](https://aws.amazon.com/athena/) for serverless SQL queries + [Amazon Redshift](https://aws.amazon.com/redshift/) for data warehousing + [Amazon EMR](https://aws.amazon.com/emr/) for Spark analytics **Interactive Dashboards**: + [Amazon QuickSight](https://aws.amazon.com/quicksight/) for dashboards and reports + [Amazon Q in QuickSight](https://aws.amazon.com/quicksight/q/) for natural language queries + Embedded insights and anomaly detection + Role-based access with Lake Formation integration **AI and Machine Learning**: + [Amazon Bedrock](https://aws.amazon.com/bedrock/) for generative AI + [Amazon Bedrock Agents](https://aws.amazon.com/bedrock/agents/) for autonomous workflows + [Amazon Bedrock Knowledge Bases](https://aws.amazon.com/bedrock/knowledge-bases/) with Aurora pgvector + [Amazon SageMaker](https://aws.amazon.com/sagemaker/) for custom ML models + [Amazon Comprehend](https://aws.amazon.com/comprehend/) for sentiment analysis **Caching and State Management**: + [Amazon ElastiCache for Redis](https://aws.amazon.com/elasticache/redis/) for last known vehicle state + [Amazon DynamoDB](https://aws.amazon.com/dynamodb/) for low-latency lookups + [Amazon MemoryDB for Redis](https://aws.amazon.com/memorydb/) for durable caching ### 6. Consumption Layer **Business Users**: + [Amazon QuickSight](https://aws.amazon.com/quicksight/) dashboards + [Amazon Q in QuickSight](https://aws.amazon.com/quicksight/q/) conversational analytics + [Amazon Bedrock Agent](https://aws.amazon.com/bedrock/agents/) chat interface + Email alerts and notifications **Data Scientists and Analysts**: + [Amazon SageMaker Studio](https://aws.amazon.com/sagemaker/studio/) for ML development + [Amazon Athena](https://aws.amazon.com/athena/) for ad-hoc SQL queries + [Amazon EMR](https://aws.amazon.com/emr/) notebooks for Spark analytics + Jupyter notebooks with SageMaker **Applications and APIs**: + [Amazon API Gateway](https://aws.amazon.com/api-gateway/) for REST APIs + [AWS AppSync](https://aws.amazon.com/appsync/) for GraphQL APIs + [AWS Lambda](https://aws.amazon.com/lambda/) for serverless functions + [Amazon EventBridge](https://aws.amazon.com/eventbridge/) for event-driven integration **Third-Party Systems**: + Dealer management systems + Usage-based insurance platforms + Fleet management applications + Mobile apps for vehicle owners ## Data Flow Architecture ### Customer 360 Data Flow ``` 1. Data Sources (CRM, Service, Telemetry) ↓ 2. Ingestion (API Gateway, Kinesis, Glue ETL) ↓ 3. Raw Storage (S3 Bronze Layer) ↓ 4. Entity Resolution (AWS Entity Resolution, Glue ETL) ↓ 5. Unified Profiles (S3 Silver Layer) ↓ 6. Aggregated Metrics (S3 Gold Layer) ↓ 7. Glue Data Catalog + Lake Formation Permissions ↓ 8. Analytics (Athena Views, Quick Suite Datasets) ↓ 9. AI Agent (Bedrock Knowledge Base + Agent) ↓ 10. Business Users (Dashboards, Natural Language Queries) ``` ### Predictive Maintenance Data Flow ``` 1. Connected Vehicles (MQTT over IoT Core) ↓ 2. IoT Core Basic Ingest → Amazon MSK ↓ 3. Apache Flink (Decode, Decompress, Enrich) ↓ 4. Processed Telemetry → S3 + ElastiCache ↓ 5. ML Training Pipeline (Step Functions + SageMaker) ↓ 6. Trained Model → SageMaker Endpoint ↓ 7. Inference API (API Gateway + Lambda) ↓ 8. Predictions → DynamoDB + EventBridge ↓ 9. Alerts (SNS, Email, Dealer Systems) ↓ 10. Service Scheduling (Proactive Outreach) ``` ### Multi-Region Governance Data Flow ``` Central Governance Region: - Lake Formation (Global Policies) - DataZone (Catalog + Lineage) - CloudTrail (Audit Logs) - Macie (PII Monitoring) ↓ EU Producer Region: - IoT Core → Kinesis → S3 - Glue ETL Streaming (PII Classification) - PII Data Store (GPS, Driver Info) - Anonymized Data Store (Hashed IDs, City-Level) - Cognito + API Gateway (Vehicle Owner Access) ↓ Global Consumer Region: - SageMaker (ML Training on Anonymized Data) - Quick Suite (Analytics Dashboards) - Lake Formation (Enforce Anonymized-Only Access) ``` ## AWS Services Used This solution uses the following AWS services: ### Data Lake and Storage + [https://aws.amazon.com/s3/](https://aws.amazon.com/s3/) - Scalable object storage for data lake with support for Parquet, Iceberg, and vector embeddings + [https://aws.amazon.com/glue/](https://aws.amazon.com/glue/) - Centralized metadata repository for all data assets + [https://aws.amazon.com/lake-formation/](https://aws.amazon.com/lake-formation/) - Fine-grained access control at database, table, and column level + [https://aws.amazon.com/athena/](https://aws.amazon.com/athena/) - Serverless SQL queries with Lake Formation permission inheritance ### Data Ingestion + [https://aws.amazon.com/iot-core/](https://aws.amazon.com/iot-core/) - Managed MQTT broker for vehicle connectivity with X.509 mTLS authentication + [https://aws.amazon.com/kinesis/data-streams/](https://aws.amazon.com/kinesis/data-streams/) - Real-time data streaming for high-throughput telemetry + [https://aws.amazon.com/msk/](https://aws.amazon.com/msk/) - Managed Apache Kafka for event streaming and message buffering + [https://aws.amazon.com/firehose/](https://aws.amazon.com/firehose/) - Serverless data delivery to S3 with transformation capabilities + [https://aws.amazon.com/api-gateway/](https://aws.amazon.com/api-gateway/) - REST APIs for transactional data ingestion ### Data Processing + [https://aws.amazon.com/glue/](https://aws.amazon.com/glue/) - Serverless data transformation with Apache Spark + [https://aws.amazon.com/managed-service-apache-flink/](https://aws.amazon.com/managed-service-apache-flink/) - Real-time stream processing for vehicle telemetry + [https://aws.amazon.com/entity-resolution/](https://aws.amazon.com/entity-resolution/) - Customer deduplication and identity linking across systems + [https://aws.amazon.com/step-functions/](https://aws.amazon.com/step-functions/) - Workflow orchestration for ML pipelines and data processing + [https://aws.amazon.com/lambda/](https://aws.amazon.com/lambda/) - Event-driven serverless compute for data transformations ### Analytics and Visualization + [https://aws.amazon.com/quicksight/](https://aws.amazon.com/quicksight/) - Interactive dashboards with natural language queries and embedded insights + [https://aws.amazon.com/quicksight/q/](https://aws.amazon.com/quicksight/q/) - Conversational analytics with role-based access + [https://aws.amazon.com/athena/](https://aws.amazon.com/athena/) - Serverless SQL analytics on S3 data lake ### AI and Machine Learning + [https://aws.amazon.com/bedrock/](https://aws.amazon.com/bedrock/) - Generative AI with Claude 3.5 Sonnet for natural language understanding + [https://aws.amazon.com/bedrock/agents/](https://aws.amazon.com/bedrock/agents/) - Autonomous AI workflows with multi-step reasoning + [https://aws.amazon.com/bedrock/knowledge-bases/](https://aws.amazon.com/bedrock/knowledge-bases/) - Retrieval-augmented generation with vector search + [https://aws.amazon.com/sagemaker/](https://aws.amazon.com/sagemaker/) - ML model training and inference for predictive maintenance + [https://aws.amazon.com/rds/aurora/](https://aws.amazon.com/rds/aurora/) - Vector database for semantic search ### Governance and Security + [https://aws.amazon.com/datazone/](https://aws.amazon.com/datazone/) - Data discovery, lineage tracking, and self-service collaboration + [https://aws.amazon.com/cloudtrail/](https://aws.amazon.com/cloudtrail/) - Immutable audit log of all API calls and data access + [https://aws.amazon.com/macie/](https://aws.amazon.com/macie/) - Automated PII discovery and classification + [https://aws.amazon.com/security-hub/](https://aws.amazon.com/security-hub/) - Centralized security findings and compliance monitoring + [https://aws.amazon.com/iam/](https://aws.amazon.com/iam/) - Identity and access management for all AWS resources + [https://aws.amazon.com/kms/](https://aws.amazon.com/kms/) - Encryption key management for data at rest + [https://aws.amazon.com/secrets-manager/](https://aws.amazon.com/secrets-manager/) - Secure storage for database credentials and API keys ### Caching and State Management + [https://aws.amazon.com/elasticache/redis/](https://aws.amazon.com/elasticache/redis/) - In-memory caching for last known vehicle state + [https://aws.amazon.com/dynamodb/](https://aws.amazon.com/dynamodb/) - Low-latency NoSQL database for vehicle profiles and predictions + [https://aws.amazon.com/memorydb/](https://aws.amazon.com/memorydb/) - Durable in-memory database for real-time state ### Authentication and Access + [https://aws.amazon.com/cognito/](https://aws.amazon.com/cognito/) - User authentication for vehicle owner portals + [https://aws.amazon.com/iam/identity-center/](https://aws.amazon.com/iam/identity-center/) - Single sign-on for enterprise users + [https://aws.amazon.com/organizations/](https://aws.amazon.com/organizations/) - Multi-account management and governance ### Monitoring and Observability + [https://aws.amazon.com/cloudwatch/](https://aws.amazon.com/cloudwatch/) - Logs, metrics, and alarms for all services + [https://aws.amazon.com/xray/](https://aws.amazon.com/xray/) - Distributed tracing for API requests and ML inference + [https://aws.amazon.com/servicecatalog/](https://aws.amazon.com/servicecatalog/) - Application resource grouping and cost tracking ## Well-Architected Framework Alignment This solution aligns with the AWS Well-Architected Framework across all six pillars: ### Operational Excellence + CloudFormation/CDK for infrastructure as code + CloudWatch for centralized logging and monitoring + X-Ray for distributed tracing across ML pipelines + Step Functions for visual workflow monitoring + Athena query history for audit trails ### Security + IAM and Lake Formation for fine-grained access control + KMS encryption for data at rest + VPC isolation for Aurora and SageMaker + Secrets Manager for credential rotation + Bedrock Guardrails for PII protection + CloudTrail for complete audit trails ### Reliability + S3 with 99.999999999% durability + Aurora Multi-AZ for automatic failover + SageMaker multi-instance endpoints + Step Functions automatic retry logic + Serverless architecture eliminates infrastructure failures ### Performance Efficiency + Athena partition pruning for fast queries + Glue Spark for distributed processing + Aurora pgvector HNSW indexing for vector search + SageMaker GPU instances for ML training + CloudFront caching for Quick Suite dashboards ### Cost Optimization + Serverless architecture (Lambda, Athena, Glue) for pay-per-use + S3 Intelligent-Tiering for automatic storage optimization + Aurora Serverless v2 for automatic capacity scaling + SageMaker auto-scaling for inference endpoints + Quick Suite pay-per-session pricing for occasional users ### Sustainability + Serverless architecture minimizes idle resources + Graviton processors for 60% better energy efficiency + S3 Intelligent-Tiering reduces storage energy consumption + Aurora Serverless v2 scales down during low-traffic periods + Deployment in renewable energy AWS Regions ## Next Steps For detailed architecture of each solution, see the respective chapter: + Automotive Data Mesh Architecture + Customer 360 Analytics Architecture + Predictive Maintenance Architecture + Automotive Data Governance Architecture For deployment planning, see the Plan Your Deployment chapter for cost estimates, security considerations, and compliance requirements.