A global online gaming studio hosts a competitive multiplayer platform on Google Cloud using Compute Engine Managed Instance Groups (MIGs) positioned behind regional External Application Load Balancers. The workload experiences predictable, extreme traffic surges during scheduled weekend global tournaments. During previous events, standard reactive autoscaling failed to provision compute instances quickly enough to absorb the rapid spike in player connections, and provisioning operations failed due to regional compute resource limitations. As the Lead Cloud Architect, you need to implement a proactive capacity planning and workload scaling strategy to ensure seamless scalability and prevent resource exhaustion during upcoming tournaments. Which TWO actions should you take to achieve this objective?
- Configure schedule-based autoscaling policy rules on the Managed Instance Groups to scale out baseline instance capacity in advance of known tournament start times.Cevap
- BRely on Compute Engine dynamic autoscaling to automatically adjust regional project vCPU quotas in real time as incoming traffic scales up.
- Perform proactive capacity planning by evaluating historical usage peak metrics and requesting regional vCPU quota increases well in advance of scheduled events.Cevap
- DConfigure the Managed Instance Groups to autoscale exclusively based on CPU utilization targeted at a high 95% threshold to maximize resource efficiency.