Optimizing a Data-Intensive Enterprise System for Stability and Operational Efficiency
Industries
Public Space Management
Services
Enterprise Application Optimization
Backend Architecture Refactoring
Database Performance & Query Optimization
Cloud Infrastructure & Cost Optimization
Technologies
Node.js, ReactJS, React Native
AWS (EC2, RDS, S3), BullMQ
MySQL, Redis, PostgreSQL
Microservices Workflows
About Block By Block
Block By Block is an enterprise platform designed to manage and process large volumes of operational and transactional data for public-serving environments. The system supports complex workflows, reporting, and data-intensive modules, serving multiple stakeholders while maintaining reliability and performance.

Challenge
- Monolithic architecture caused slow response times under heavy data load
- Inefficient database queries impacted reporting and core workflows
- High infrastructure costs due to poor resource utilization
- Limited observability made performance bottlenecks difficult to diagnose
Block By Block faced performance degradation and operational inefficiencies as its data volume increased, limiting the system’s ability to support growing workloads.
Our Solution

- Refactored critical backend components to improve responsiveness and handle data-intensive workloads.
- Optimized database queries, indexing, and data access patterns to accelerate reporting and core workflows.
- Converted reporting and GeoLogs generation into asynchronous processes to eliminate blocking operations and improve system stability.
- Introduced end-to-end automated tests and monitoring to ensure reliability, prevent regressions, and proactively detect performance issues.
Results
- 70% faster response times for critical workflows
- Asynchronous reporting and geo log tracking eliminated long-running blocking operations
- Improved system stability during peak data processing
- Reduced operational overhead through optimized resource usage
Our solution helped Block By Block achieve 70% faster workflows and reduced operational costs through optimized architecture.
