⚙️ Horizontal Scaling via Queue Workers #68
Description
📌 Overview
High transaction volume, especially from meta-transactions, can overwhelm the API and backend services. Processing everything synchronously leads to bottlenecks and latency spikes.
This task introduces horizontal scaling using queue workers, enabling asynchronous processing to handle spikes efficiently and improve system reliability.
🎯 Objective
Build a system that:
- Offloads intensive tasks to a queue for asynchronous processing
- Supports horizontal scaling by adding multiple worker instances
- Ensures reliable and fault-tolerant task execution
- Improves throughput and response times during peak loads
🛠 Scope of Work
1️⃣ Queue Integration
-
Integrate BullMQ for queue management:
- Job creation for meta-transactions or other high-load tasks
- Worker processes for executing queued jobs asynchronously
- Retry and failure handling
-
Example job flow:
Client -> API -> Job Queued in BullMQ -> Worker Executes Task -> Result Stored / Callback
2️⃣ Horizontal Scaling
- Deploy multiple worker instances to process jobs concurrently
- Ensure job deduplication and ordering if necessary
- Load balancing across workers using Redis as the queue backend
3️⃣ Monitoring & Metrics
- Track job metrics:
- Queue length
- Job processing time
- Failed / retried jobs
- Optional Prometheus/Grafana integration for real-time monitoring
- Logging for troubleshooting and audit
4️⃣ Security & Reliability
- Secure queue access via Redis authentication
- Ensure idempotent job execution to prevent duplicate effects
- Handle worker failures gracefully with retries and backoff
🧰 Suggested Tech Stack
Core
- TypeScript
- Node.js
- BullMQ for job queues
- Redis as queue backend
- NestJS / Express / Fastify for API endpoints
Optional Enhancements
- Prometheus / Grafana for monitoring
- Docker for worker instance scaling
- Jest (unit testing)
🧠 Implementation Expectations
- Clear separation between:
- API request layer
- Job queue and worker layer
- Result storage / callback layer
- Ensure deterministic and reliable job execution
- Unit tests covering:
- Job creation and queueing
- Worker execution and retries
- Error handling and backoff logic
- Multi-worker concurrency
📊 Deliverables
- BullMQ queue integrated with GasGuard backend
- Worker processes for asynchronous task execution
- Metrics and logging for queue performance
- Documentation explaining:
- Job flow
- Worker scaling strategy
- Retry and failure handling
- Unit tests (minimum 70% coverage)
- Updated README
🏷 Difficulty Level
Advanced
Ideal for contributors with:
- Backend TypeScript experience
- Knowledge of queue systems and asynchronous processing
- Experience with Redis and horizontal scaling
- Familiarity with high-volume blockchain transaction workflows
🕒 Estimated Time
24hrs or less
✅ Acceptance Criteria
- Jobs are queued and processed asynchronously
- Multiple workers can scale horizontally without conflict
- Job retries and failure handling implemented
- Metrics and monitoring functional
- Documentation updated
- All tests passing
🎯 Expected Outcome
GasGuard supports high-volume transaction processing, reducing API bottlenecks and enabling scalable, asynchronous handling of meta-transactions and other heavy workloads.