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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A financial analytics company runs large-scale, fault-tolerant nightly batch processing workloads on Google Compute Engine. The processing application can gracefully checkpoint progress, handle node terminations, and run on various CPU architectures and sizes.
Management requires a compute architecture that minimizes infrastructure costs using Spot VMs while mitigating the risk of batch processing delays caused by high localized preemption rates or capacity shortages for a single machine type.
Which configuration should the cloud architect recommend?
Instance flexibility in a regional Managed Instance Group (MIG) allows the group to provision virtual machines from a list of multiple configured machine types rather than being constrained to a single VM size or family. When applied to Spot VMs, the MIG intelligently selects from the specified machine types and zones based on real-time resource availability and historical stability.
Using Spot VMs with instance flexibility provides the best balance of aggressive cost reduction and workload reliability for batch processing. Because the application can run across different CPU types and handles terminations gracefully, opening the resource pool across multiple machine types prevents job stalls caused by localized Spot preemption spikes.
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