Approach: Use distributed architecture with message queues and stream processing to separate ingestion, validation, and storage layers for client order fulfillment.

Considerations: Prioritize data integrity and compliance over speed. Client capital at stake requires correctness over latency.

Key Points: Target sub-100ms latency, 99.99% uptime SLAs, immutable audit logs, and failover redundancy across datacenters.

Approach: Isolate scope via logs and metrics, roll back recent changes or enable feature flags to minimize client impact while investigating root cause.

Considerations: Restore service quickly over perfect diagnosis. Client downtime harms revenue and reputation directly.

Key Points: Use distributed tracing, check data consistency, validate market feeds, review deployments, document incidents for post-mortems.

Approach: Design real-time rule engine with configuration store and evaluation framework operating on transaction streams with minimal latency.

Considerations: Balance false positives (frustrate clients) against false negatives (compliance risk). Ensure explainability for regulatory transparency.

Key Points: Implement rules for volume, unusual geography, market manipulation; log all flagged transactions with audit trails for compliance.