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Professional Cloud Architect

Intrigued by the art of cloud architecture? Discover how to design, develop, and manage robust, secure, scalable, and dynamic solutions on Google Cloud as you prepare for the Professional Cloud Architect exam!

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Chaos Engineering Failure Injection Resilience Testing

Section: Ensuring the reliability of solutions in production (e.g., chaos engineering, penetration testing, and load testing)

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An e-commerce platform running on Google Cloud uses Regional Managed Instance Groups (MIGs) behind an external Application Load Balancer, with Cloud Monitoring tracking Service Level Indicators (SLIs) against a 99.99% availability Service Level Objective (SLO). The Site Reliability Engineering (SRE) team wants to conduct a chaos engineering experiment in a staging environment that mirrors production to validate that automated recovery mechanisms function properly during infrastructure disruptions without exceeding the allocated error budget.

Which strategy should the team implement to design and validate this failure injection experiment?

Disable health checks on the Application Load Balancer backend service, terminate all virtual machines across all zones simultaneously, and measure the time required for engineers to execute manual disaster recovery runbooks.

Simulate a live migration event on all instances and verify that Compute Engine host maintenance policies restart the virtual machines sequentially without using load balancing.

Increase the target CPU utilization threshold on the Managed Instance Group autoscaler to 100%, disable scale-out actions, and monitor system degradation under unthrottled load.

Establish a steady-state baseline using SLI metrics, inject automated VM terminations and network latency within a single zone under synthetic load, and evaluate whether Regional MIG autohealing and load balancing preserve the SLO within error budget thresholds.

Professional Cloud Architect

Chaos Engineering Failure Injection Resilience Testing

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