To be resilient for a Reactive System means that the system remains responsive even in the face of failures. This characteristic is crucial for ensuring that the system can continue to operate and provide services despite encountering issues such as component failures, load spikes, or attacks.
Resilience in Reactive Systems is achieved through several strategies:
Replication: This involves creating multiple copies of components or services to ensure high availability. For example, replicating master nodes in a Redis cluster ensures that if one node fails, another can take over without service interruption[3][4].
Containment: Failures are contained within individual components to prevent them from affecting the entire system. This means that a failure in one part of the system does not cascade to other parts, thereby isolating the impact[1][2][4].
Isolation: Components are designed to be isolated from each other, ensuring that the failure of one component does not bring down the entire system. This isolation allows parts of the system to fail and recover independently[1][3][4].
Delegation: Recovery from failures is delegated to other components, often external ones. For instance, if a primary data source fails, the system can fall back to an alternate data source[3][4].
Self-Healing: Reactive Systems are designed to detect problems quickly and take appropriate actions to mitigate them. This self-healing capability ensures that the system can recover from failures without manual intervention[3][4].
By employing these strategies, Reactive Systems can maintain their responsiveness and continue to provide a consistent quality of service even when individual components fail. This resilience is a fundamental aspect of the Reactive Manife...
