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Answer: Create synthetic random user input, replay synthetic load until autoscale logic is triggered on at least one layer, and introduce chaos to the system by terminating random resources in both zones.
The correct answer is B. When developing a resiliency testing strategy, it is important to test both the system's ability to handle increased user load and its ability to recover from failures. Option B involves creating synthetic random user input and replaying synthetic load until autoscale logic is triggered, which simulates the expected increased user traffic. Introducing chaos by terminating random resources in both zones tests the resiliency and redundancy of the system under stress. This comprehensive approach ensures that the system can maintain the 99.99% availability SLA when subjected to additional user load, making it the best choice for evaluating system resilience.
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Your company's user-feedback portal comprises a standard LAMP stack (Linux, Apache, MySQL, PHP) replicated across two zones. It is deployed in the us-central1 region on Google Cloud Platform and utilizes autoscaled managed instance groups for all layers, except the database. Currently, a small group of select customers has access to the portal, and the portal meets a 99.99% availability SLA under these conditions. However, next quarter, your company plans to make the portal available to all users, including unauthenticated users. You need to develop a resiliency testing strategy to ensure the system maintains the SLA once there is an additional user load. What should you do?
A
Capture existing user input and replay captured user load until autoscale is triggered on all layers. Simultaneously, terminate all resources in one of the zones.
B
Create synthetic random user input, replay synthetic load until autoscale logic is triggered on at least one layer, and introduce chaos to the system by terminating random resources in both zones.
C
Expose the new system to a larger group of users, and increase group size each day until autoscale logic is triggered on all layers. Simultaneously, terminate random resources in both zones.
D
Capture existing user input and replay captured user load until resource utilization exceeds 80%. Also, estimate the number of users based on existing users' usage of the app, and deploy enough resources to handle 200% of the expected load.