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Real-time tracking of stablecoin transfers such as USDC and USDT is a growing need for financial teams, exchanges, and decentralized applications. However, building a reliable watcher on blockchain networks using free RPC providers involves navigating several technical hurdles. In this article, we analyze an architecture based on NestJS, viem, and BullMQ, and share lessons learned on how to handle block limits, disconnections, and differences between networks. At Q2BSTUDIO, specialists in custom applications, we apply these patterns to deliver robust blockchain monitoring solutions.
The core strategy consists of using a subscription to new blocks as a simple trigger, while log retrieval is performed via getLogs with ranges chained from a last processed block persisted in the database. This allows free recovery after crashes or restarts, without needing a separate recovery mode. A first common pitfall appears with free providers: for example, Alchemy limits the eth_getLogs range to 10 blocks. The solution is to split synchronization into configurable chunks (backfillChunk), enabling both real-time execution and catch-up after periods of inactivity.
Another recurring issue is that the production server's IP address may be blocked by the RPC provider, while everything works perfectly from local. It is essential to test endpoints from the real IP and not assume that a key will work in any environment. In one of our deployments, we moved the system to a cloud instance and discovered that the same Alchemy key returned 403 Forbidden with istio-envoy headers, indicating a datacenter-level block. We opted for PublicNode for Base and TronGrid for Tron, always verifying that both methods (subscription and HTTP query) operate correctly.
The architecture benefits from a job queue with at-least-once semantics: the event is first enqueued and then marked as processed, combining txHash and logIndex for deduplication in BullMQ. This ensures that no transfer is lost, although it may be repeated. Additionally, a confirmation delay (e.g., 2 blocks) is introduced to avoid consistency issues between nodes in a load-balanced pool, where the WebSocket subscription may see a block before the HTTP node responding to getLogs. This same delay protects against superficial chain reorganizations.
When adding USDT on Tron (TRC-20), we discovered that viem, not being tied to a specific chain, works directly against the java-tron JSON-RPC API, which exposes an Ethereum-compatible subset. The only adaptation needed was changing the WebSocket subscription trigger to periodic polling (every 3 seconds), since TronGrid does not offer subscriptions. Tron addresses are stored internally in hex, and conversion from base58 format is performed with cryptographic validation without additional dependencies. This approach allowed reusing 90% of the Base watcher code, demonstrating the advantages of a network-agnostic pipeline.
Implementing real-time monitoring systems requires not only blockchain knowledge but also infrastructure expertise. At Q2BSTUDIO, we integrate AWS and Azure cloud services to deploy these watchers with high availability, auto-scaling, and monitoring. Cybersecurity also plays a crucial role: protecting API keys, encrypting communications, and auditing access to RPC endpoints are mandatory practices. Furthermore, enterprise artificial intelligence can enhance these systems through AI agents that analyze transfer patterns, detect anomalies, or automate responses. Our business intelligence services with Power BI allow visualizing stablecoin flow in real time, combining on-chain data with financial metrics.
The most valuable lesson is that careful design, with chunking, confirmations, and progress persistence, turns free RPCs into a viable option for production environments. However, each network and provider has its own peculiarities: always test in the target environment and with the exact methods that will be used in production. At Q2BSTUDIO, we offer custom software for blockchain integrations, from notification bots to complete financial monitoring platforms, combining enterprise AI with process automation. If you are looking to build your own watcher or need advice on scalable architectures, we are ready to help you.
