Teva Project Work Summary Link to heading

Executive Summary Link to heading

The Teva project involved extensive work on a comprehensive data analytics platform built primarily on Vertica database infrastructure with cloud-based ETL processes, performance benchmarking, and automated data collection systems. The work spanned multiple domains including database infrastructure, data migration, stream processing, monitoring systems, and performance optimization.

Major Project Components Link to heading

1. Database Infrastructure & Migration Link to heading

  • Vertica Cluster Management: Implemented and managed EON mode Vertica clusters across QA and Production environments
  • Schema Migration: Executed multiple phases of data migration including “first-migration”, “march-migration”, and “third-migration” projects
  • DDL Management: Comprehensive database schema management through the vertica-ddl and duck-ddl projects
  • Performance Testing: Extensive TPC-DS benchmark testing with S3 object storage compatibility testing

2. ETL & Data Processing Infrastructure Link to heading

  • Stream Processing: Built multiple Ruby-based streaming applications:
    • ftp-file-producer: FTP file processing and ingestion
    • s3-file-producer: S3-based file processing
    • salesforce-extract: Salesforce data extraction pipeline
    • sneaql-transform: Data transformation workflows
    • ingestion-consumer: Data ingestion processing

3. Data Collection & Monitoring Systems Link to heading

  • Data Collector Tables (dc_tables): Python-based system for processing Vertica data collector metrics
    • Automated S3 data retrieval and processing
    • Focus on 5 key metrics: RequestsIssued, RequestsCompleted, ResourceReleases, Errors, ResourceAcquisitions
    • Template-based SQL generation and execution
  • CloudWatch Integration: Metrics collection and monitoring setup
  • Control Tables: HPS control table management system

4. Performance & Benchmarking Link to heading

  • TPC-DS Benchmarking: Comprehensive performance testing framework
    • 3-node Vertica EON clusters with 32 CPUs, 256GB memory per node
    • S3 object storage compatibility testing
    • Multiple data size configurations (10GB to 5TB)
    • Concurrent user load testing (1-30 users)
    • Depot on/off performance comparisons
  • Performance Analysis: Detailed performance metrics collection and analysis
  • Resource Pool Management: Database resource optimization

5. Cloud Infrastructure & DevOps Link to heading

  • Terraform Infrastructure: Complete infrastructure as code implementation
  • AWS Integration: Extensive use of AWS services (S3, ECS, DynamoDB, CloudWatch)
  • Container Orchestration: Docker-based application deployment
  • Security Management: Encrypted secrets management using Biscuit
  • Environment Management: Multi-environment setup (DEV, QA, PROD)

6. Support & Maintenance Systems Link to heading

  • Automated Workflows: Various automation scripts and utilities
  • Troubleshooting Tools: Comprehensive diagnostic and monitoring tools
  • Backup & Recovery: S3-based backup and restore procedures
  • Database Maintenance: Automated maintenance tasks and monitoring

Key Technical Achievements Link to heading

Database Performance Link to heading

  • Successfully implemented and tested Vertica EON mode with S3 object storage
  • Achieved performance benchmarks with TPC-DS queries across multiple concurrency levels
  • Implemented automated backup/restore procedures with S3 integration
  • Database revive functionality for disaster recovery scenarios

Data Processing Pipeline Link to heading

  • Built scalable ETL infrastructure capable of processing various data sources
  • Implemented streaming data ingestion from FTP, S3, and Salesforce
  • Created automated data validation and error handling systems
  • Developed template-based SQL generation for dynamic data processing

Infrastructure Automation Link to heading

  • Complete infrastructure automation using Terraform
  • Multi-environment deployment capabilities
  • Automated scaling and resource management
  • Comprehensive monitoring and alerting systems

Data Migration Success Link to heading

  • Successfully migrated data across multiple phases
  • Implemented parallel processing for large-scale data operations
  • Created tools for schema comparison and validation between environments
  • Developed automated DDL generation and deployment processes

Project Files and Structure Link to heading

The project comprises over 40 major components including:

  • Infrastructure Projects: 8 major infrastructure repositories
  • ETL Applications: 6 streaming/processing applications
  • Migration Tools: 4 data migration projects
  • Performance Testing: Comprehensive TPC-DS benchmark suite
  • Monitoring Systems: 3 monitoring and collection systems
  • Support Tools: Multiple utility and support applications

Outcomes and Impact Link to heading

Performance Results Link to heading

  • Completed TPC-DS benchmarks with various data sizes (10GB - 5TB)
  • Achieved target performance metrics across different user concurrency levels
  • Validated S3 object storage compatibility with Vertica EON mode
  • Successful backup/restore operations with S3 storage

Infrastructure Reliability Link to heading

  • Established robust multi-environment infrastructure
  • Implemented automated deployment and scaling capabilities
  • Created comprehensive monitoring and alerting systems
  • Achieved high availability through proper cluster management

Data Processing Efficiency Link to heading

  • Automated data ingestion from multiple sources
  • Implemented efficient ETL pipelines with error handling
  • Created scalable processing architecture
  • Established data quality validation processes

Technology Stack Link to heading

Databases: Vertica (EON Mode), DynamoDB Cloud Platform: AWS (S3, ECS, CloudWatch, EC2) Languages: Python 3.11, Ruby, SQL, Go Infrastructure: Terraform, Docker, Linux Monitoring: CloudWatch, Vertica Data Collector, Custom metrics Development Tools: Git, Makefiles, Shell scripting

Status: Project Completed Successfully Link to heading

All major deliverables have been completed including:

  • ✅ Database infrastructure deployment and optimization
  • ✅ ETL pipeline development and deployment
  • ✅ Performance benchmarking and validation
  • ✅ Data migration execution across all phases
  • ✅ Monitoring and alerting system implementation
  • ✅ Documentation and runbook creation
  • ✅ Multi-environment testing and validation

The Teva analytics platform is fully operational and meeting all performance and reliability requirements.