The architecture centers on a Saga Orchestration pattern decoupled by an Event-Driven backbone. At the ingress, an API Gateway (Kong or Envoy) validates JWT tokens and routes requests to a Policy Enforcement Point (PEP), which queries a Policy Decision Point (PDP) using Open Policy Agent (OPA) for real-time AML and KYC checks against sanctions lists.
The core is the Cross-Ledger Transaction Coordinator, implemented as a state machine using Temporal or a custom Saga engine over Apache Kafka. This coordinator manages the distributed transaction across two distinct domains: the Fiat Ledger Adapter (integrating with SWIFT, ACH, or SEPA via ISO 20022 messaging) and the Blockchain Adapter (supporting EVM chains via Alchemy or Infura, and Stellar via Horizon API).
For atomicity without 2PC (which is unavailable on public blockchains), we employ the Saga pattern with compensating transactions. The coordinator first executes the "debit fiat" local transaction, then the "mint/transfer stablecoin" local transaction. If the latter fails, the former is compensated by a "credit fiat" transaction. Event sourcing ensures all state changes are persisted in PostgreSQL and published to Kafka for auditability.
Liquidity management utilizes a Geographically Distributed Cache (Redis Cluster) with WAL backing to Cassandra for cross-region consistency. gRPC connections between microservices ensure low latency, while Prometheus and Grafana provide observability. The entire stack runs on Kubernetes with Istio for service mesh capabilities, ensuring mTLS between components.
At CrossBridge Payments, we faced a critical requirement to enable instant remittance from a US customer using ACH to a German recipient receiving SEPA credits, routed through a USDC stablecoin bridge on Ethereum and Stellar to reduce correspondent banking delays. The primary challenge was ensuring atomicity: if the blockchain transaction failed after the ACH debit succeeded, the customer would lose funds, yet blockchain finality takes 12 seconds on Ethereum while ACH settlement is T+1 but debits are immediate.
We evaluated three architectural approaches. The first option involved a Centralized Oracle that held custody of both fiat and crypto, acting as a trusted intermediary. While this simplified coordination and reduced latency to milliseconds, it introduced unacceptable counterparty risk and failed to meet regulatory requirements for decentralized custody in certain jurisdictions.
The second option proposed Hash Time-Locked Contracts (HTLC) for trustless atomic swaps between the fiat bank and the blockchain. However, this proved infeasible because traditional banking rails lack cryptographic primitives to verify hashes on-chain, and the timeout mechanisms created poor user experience requiring active client participation.
We ultimately selected Saga Orchestration with Event Sourcing using Apache Kafka and Temporal. This approach treated the fiat debit and crypto minting as separate local transactions within a Saga. The orchestrator first locked funds in a master escrow account via the ACH adapter, then initiated the USDC transfer on Stellar (chosen for 5-second finality). If the crypto step failed, the orchestrator triggered a compensating transaction to reverse the ACH lock.
The result was a 99.95% success rate with 800ms average UI confirmation time, full regulatory audit trails stored in PostgreSQL, and zero customer fund losses due to atomicity failures during the six-month pilot.
How do you reconcile the synchronous nature of REST API client expectations with the asynchronous, probabilistic finality of public blockchain networks without holding HTTP connections open for minutes?
Many candidates suggest long-polling or blocking HTTP requests until blockchain confirmation, which exhausts server threads and triggers gateway timeouts. The correct approach involves the CQRS pattern combined with Event Sourcing. The initial settlement request returns immediately with a 202 Accepted status and a unique transaction correlation ID. The client subscribes to a WebSocket or Server-Sent Events (SSE) endpoint, or polls a lightweight status endpoint backed by Redis. The backend processes the blockchain confirmation asynchronously via Kafka consumers. Once the Saga reaches a terminal state (completed or compensated), the status is pushed to the client.
What strategy ensures exactly-once execution of fiat debits when the downstream banking API (JPMorgan Access or Stripe Treasury) returns a timeout, leaving ambiguity about whether the funds were actually moved?
Candidates often incorrectly assume that retries are safe or that idempotency keys alone suffice. The robust solution implements an Idempotency Ledger using PostgreSQL with a PENDING state machine. Before calling the external API, the service writes an intent record with a deterministic key (SHA-256 of transaction ID + timestamp bucket). If the API times out, a background Saga worker queries the bank's idempotency query endpoint (or uses Webhook reconciliation). Only upon explicit confirmation or denial does the state transition to SUCCESS or FAILED.
How do you prevent liquidity fragmentation and double-spending in the shared liquidity pool when high-frequency arbitrage bots simultaneously access the same USDC reserves via the REST API and incoming blockchain deposit events?
This requires Optimistic Locking at the database level and Distributed Locking for critical sections. The liquidity service maintains versioned rows in PostgreSQL; any update increments the version. When a withdrawal is attempted, the system checks the version. If a concurrent blockchain event has modified the row (version mismatch), the transaction retries. For the hot path, a Redis Redlock is acquired before checking balances, ensuring sequential access. Additionally, a Circuit Breaker (Resilience4j) monitors the liquidity pool's contention ratio.