Your media company schedules nightly video-transcoding jobs that take about two hours and can be restarted if interrupted. Each worker requires roughly 8 vCPUs and 30 GB of RAM. You want to minimize compute cost while avoiding over-provisioning resources. Which Compute Engine configuration best meets these requirements?
Deploy a Spot VM that uses a custom machine type with 8 vCPUs and 30 GB RAM.
Run the job on regular (on-demand) e2-standard-8 instances backed by a 100 GB balanced persistent disk.
Deploy a Spot n2-standard-8 VM and attach a 375 GB Local SSD for temporary scratch space.
Use memory-optimized m2-ultramem-32 on-demand instances to guarantee the workload is never interrupted.
Spot VMs provide discounts of roughly 60-91 percent compared with standard on-demand pricing and are designed for fault-tolerant, short-lived batch workloads that can tolerate preemption-such as two-hour nightly transcoding jobs. Choosing a custom machine type with exactly 8 vCPUs and 30 GB of memory avoids paying for the extra 2 GB that comes with the n2-standard-8 preset. Alternatives either run at regular pricing, add a 375 GB Local SSD that would incur extra cost without benefiting this stateless workload, or select an oversized and expensive memory-optimized machine. Therefore, a custom Spot VM delivers the lowest cost while satisfying the performance requirements.
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Why avoid Local SSD and memory-optimized machines for this workload?
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Why is using a Local SSD with n2-standard-8 not recommended for this workload?
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