YURKOL Ltd - Custom Software and Cloud Architectural Solutions

Common Architectural Mistakes

• Single, "monolith" database that becomes a system-wide point of failure
• Not applying loose coupling and any reasonable failover strategies when an individual component's failure leads to the whole system collapse
• Forgetting about different degrees of data priority that processes all data equally regardless of clinical urgency
• Errors in caching implementation that might lead to stale or inconsistent data
• Single-region deployment vulnerable to regional outages

The following are essential components of any healthcare-IT system that claims to be resilient

Event-Driven Architecture

• Event model instead of rigid service synchronization
• CQRS pattern to separate read/write operations for better scaling

With these in place a system continues functioning even when individual components are unavailable

Strategy for Database Failover and Database distribution model

• Cloud SQL with multi-region replication (GCP or any other cloud provider environments)
• YugabyteDB for distributed write workloads

Worth noticing: Cloud SQL in GCP includes high availability and failover, but there some practically important limitations:

• Not horizontally scalable for writes—only one master node handles all write operations
• No multi-region write capability—writes always go to a single region
• Failover takes 20-50 seconds—potentially too long for critical healthcare applications

For systems requiring truly distributed write capabilities and multi-region performance, consider Spanner or YugabyteDB despite their higher cost.

Services deployment and horizontal scaling

• Cloud Run or Kubernetes with reasonable scaling policies where auto-scaling configured to handle known traffic patterns

Robust Caching Strategy

• Redis with Sentinel for automatic failover when master nodes fail
• CDN distribution for static assets to reduce backend load

Multi-Region Deployment

• Services deployed across at least two geographic regions
• Global Load Balancer for intelligent traffic routing between regions

Continuous Monitoring

• Thorough system visibility
• OpenTelemetry for distributed tracing across service boundaries

Resilient System Reference Architecture

1. Frontend: React/Vue application distributed via CDN
2. API Gateway: Envoy/Cloud Run Ingress for request routing
3. Backend: Stateless Go microservices with independent scaling
4. Message Broker: NATS/Jetstream for event-driven patterns
5. Databases: Cloud SQL with read replicas or YugabyteDB for distributed workloads
6. Monitoring: Comprehensive observability with OpenTelemetry

Priority-Based Processing for Clinical Data

Healthcare data varies dramatically in urgency—STAT laboratory results and billing updates should not compete for the same resources. As outlined in our article on technical constraints affecting physicians, standard enterprise architectures process information in the order it arrives, which fails in clinical settings where time-sensitivity varies widely.

Implementing multi-tier processing architecture separates incoming data into distinct lanes:

1. Critical Lane: Time-sensitive clinical data with immediate processing guarantees
2. Standard Lane: Routine clinical information
3. Batch Lane: Analytics, billing, and administrative data

Each lane maintains dedicated processing resources, preventing load spikes in lower-priority queues from impacting critical data pathways.

Context-Aware Authentication

As discussed in our article on physicians' technical constraints, standard authentication systems rarely account for the unpredictable nature of clinical workflows. Hospital environments involve frequent interruptions, team handovers, and rapid context switching between patients.

Authentication systems must adapt to clinical realities:

• Context-aware timeout policies based on clinical setting and urgency
• Streamlined authentication for emergency situations
• Session persistence that survives interruptions in clinical workflows

When a physician is treating multiple critical patients, every second spent navigating login screens represents time taken away from patient care.

Event Sourcing for Healthcare Audit Trails

Healthcare systems require comprehensive audit capabilities for regulatory compliance and clinical safety. Event sourcing provides several important benefits:

• Reconstruction of patient records at any point in time
• Complete audit trails for compliance verification
• Support for temporal queries about historical patient status

While adding complexity, event sourcing delivers significant value in domains like medication administration and clinical decision documentation.

Conclusion

Building truly resilient healthcare systems requires more than simple database replication. It demands a comprehensive architectural approach that preserves clinical functionality even during system degradation.

Failover strategy must extend beyond infrastructure considerations to encompass the clinical realities of healthcare delivery—where system performance directly impacts patient care.

With properly implemented multi-tier processing, event-driven architecture, and context-aware systems, healthcare platforms can achieve both high reliability and cost-effective infrastructure utilization.