1-GCP-VM-Preemptible
Preemptible VM instances are available at much lower price—a 60-91% discount—compared to the price of standard VMs. However, Compute Engine might stop (preempt) these instances if it needs to reclaim the compute capacity for allocation to other VMs.
If your apps are fault-tolerant and can withstand possible instance preemptions, then preemptible instances can reduce your Compute Engine costs significantly. For example, batch processing jobs can run on preemptible instances. If some of those instances stop during processing, the job slows but does not completely stop. Preemptible instances complete your batch processing tasks without placing additional workload on your existing instances and without requiring you to pay full price for additional normal instances.
Preemptible instances function like normal instances but have the following limitations:
Compute Engine might stop preemptible instances at any time due to system events. The probability that Compute Engine stops a preemptible instance for a system event is generally low, but might vary from day to day and from zone to zone depending on current conditions.
Compute Engine always stops preemptible instances after they run for 24 hours. Certain actions reset this 24-hour counter.
Preemptible instances are finite Compute Engine resources, so they might not always be available.
Preemptible instances can’t live migrate to a regular VM instance, or be set to automatically restart when there is a maintenance event.
Due to the preceding limitations, preemptible instances are not covered by any Service Level Agreement and are excluded from the Compute Engine SLA.
machine type
https://cloud.google.com/compute/docs/machine-resource
Workload type
General-purpose workloads Compute-optimized Memory-optimized Accelerator-optimized
E2 N2, N2D, N1 C3 Tau T2D, Tau T2A C2, C2D M3, M2, M1 A2, G2
Day-to-day computing at a lower cost Balanced price/performance across a wide range of machine types Consistently high performance for a variety of workloads Best per-core performance/cost for scale-out workloads Ultra high performance for compute-intensive workloads Highest memory to compute ratios for memory-intensive workloads Optimized for accelerated high performance computing workloads