Post-migration performance concerns are common, particularly when on-premises systems and applications are transferred without proper remediation and testing. Let’s take a closer look at a prevalent one: failures in high-availability applications, and learn what causes them and how they may be prevented. High availability, which is often described as a system’s capacity to continue to deliver uninterrupted services under any situation, is one of the most well-known commercial benefits of cloud migration. Automatic and continuous monitoring, clustering, load balancing, identifying an approaching failure, and automated failover to a redundant backup sub-system or component are common ways to do this (when the primary fails). And all of this happens at the infrastructure layer.

Customers often anticipate high availability when migrating an on-premise system to the cloud since cloud providers provide availability targets based on the level of service committed to. Sadly, though, this assumption is inaccurate. While the cloud provider guarantees the underlying cloud infrastructure’s availability through different tactics such as those outlined above, the cloud tenant is responsible for architecting and developing the application layer for resiliency. Applications may fail abruptly if this is not done, compromising overall system availability. What is application resiliency, though? The capacity to offer and sustain acceptable levels of service in the face of numerous defects and impediments to regular operation is what application resilience is simply described as. Resilient programs are able to adapt to unexpected and disruptive changes in the environment. Under severe situations, it includes fault recovery and graceful decay.

Because the application layer was not originally architected or remediated for resiliency before migration, certain migration techniques result in production failures. In order to enjoy the full promise of the cloud, even natively created cloud apps must apply resilient best practices. A music streaming service provider recently experienced a major service outage as a result of a cascade failure of numerous microservices caused by a transitory network fault. The system had not been designed or tested to identify and recover gracefully from such an isolated temporary breakdown, which resulted in downstream problems. How to test, analyze, and define cloud application resiliency before going live so that system availability is maintained in accordance with business requirements is a major problem. For a variety of reasons, traditional testing methodologies are insufficient to detect cloud application resilience issues:

Existing test methodologies are motivated by business use cases or requirements, and thus are incapable of detecting underlying, deep, and hidden design flaws.

  • Because of the intricacy of interactions between diverse software entities, heterogeneous and multi-layer systems are prone to failure.
  • Unpredictable ’emergent’ behavior of cloud application architecture, notably hybrid and multi-cloud, due to poor determinism of production usage patterns.
  • Failures are frequently asymptomatic, remaining hidden as internal system defects until particular conditions cause them to become visible.
  • Layers inside the cloud may have distinct stakeholders and be managed by separate administrators, resulting in unanticipated configuration changes that cause interface breakdowns.


Because cloud systems are multi-tiered, multi-technology architecture, and dispersed, architecting for application resiliency is more important. Even though the underlying infrastructure resiliency is covered by the cloud provider, this might lead cloud apps to fail in unanticipated ways. Organizations may get insights into cloud application resiliency long before going live by using an architecture-driven testing strategy and allocating enough time for performance repair efforts.

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