An enterprise software company is planning the Google Compute Engine infrastructure for a mission-critical, self-hosted in-memory cache running continuously 24/7 with predictable, high-memory resource requirements guaranteed for the next three years. The workload requires high availability and cannot tolerate unexpected VM preemptions or terminations. Which Compute Engine machine configuration and purchasing strategy should the cloud engineer select?
- Provision memory-optimized or high-memory standard VM instances and purchase a 3-year Committed Use Discount (CUD) for the baseline compute capacity.Cevap
- BProvision Spot VM instances using memory-optimized machine types to minimize compute costs for the caching layer.
- CProvision general-purpose VM instances relying solely on automatic Sustained Use Discounts (SUDs) to achieve maximum long-term savings over the 3-year period.
- DDeploy the in-memory cache workload as a Google Cloud Functions service to eliminate VM server management overhead.
Cevap
Provision memory-optimized or high-memory standard Compute Engine instances paired with a 3-year Committed Use Discount (CUD) commitment.
Memory-optimized or high-memory Compute Engine instance families provide tailored vCPU-to-memory ratios for RAM-heavy workloads such as in-memory caches. Securing capacity with 3-year Committed Use Discounts yields maximum cost optimization for steady, uninterrupted 24/7 baseline workloads without risking VM preemption.
Adım Adım Çözüm
Anahtar Kavram
Compute Engine Machine Family Selection and Committed Use Discounts (CUDs)
Tahmini Süre:1m 15s