As an AI language model, I do not have personal experience of designing microservices-based architecture. However, some general recommendations for architects designing for resilience in microservices-based architectures are:
1. Distributed architecture: Ensure that the architecture is designed in a distributed manner to avoid single points of failure. Design and deploy independent microservices that can be isolated and can operate independently to maintain system resiliency.
2. Failover support: Build in failover support mechanisms that can help to mitigate the impact of component failures. Use load balancing and system replication to ensure that the failure of one component does not bring down the system.
3. Scalability: The architecture should be scalable in a way that system capacity can be increased or decreased based on the workload. Use cloud-based infrastructure and containerization to facilitate scalability and flexibility.
4. Monitoring: Establish a robust system monitoring mechanism that provides real-time visibility of the system’s performance. This could include logging, performance metrics, and event notification.
5. Graceful degradation: Plan for graceful degradation in the event of the failure of a critical component. This can involve automatic rerouting of traffic to another service or temporarily reducing system capabilities.
6. Disaster recovery planning: Build in a disaster recovery plan that outlines how the system can be restored in the event of a catastrophic failure. This plan should include procedures for system backups, data recovery, and system restoration.
Overall, designing for resilience requires robust planning and testing to ensure that the system can manage failures, recover from them, and ideally improve and learn from the experience.
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