What are the considerations for setting up custom autoscaling policies in Google Compute Engine?
- Considerations for setting up custom autoscaling policies in Google Compute Engine include defining appropriate scaling triggers based on metrics such as CPU utilization, request latency, or custom application-specific metrics. Additionally, it's essential to set meaningful thresholds and scale-in and scale-out policies to ensure efficient resource allocation and cost optimization.
- Custom autoscaling policies in Google Compute Engine should prioritize simplicity and minimize the number of scaling triggers and policies to reduce complexity and improve manageability.
- Custom autoscaling policies in Google Compute Engine should rely solely on manual intervention, allowing administrators to make scaling decisions based on real-time observations and insights.
- Custom autoscaling policies in Google Compute Engine should be based solely on historical usage patterns, ignoring real-time metrics and workload characteristics to simplify configuration and management.
Setting up custom autoscaling policies in Google Compute Engine requires careful planning and consideration of various factors to ensure they align with business requirements and effectively manage resource utilization while maintaining application performance and availability.
Loading...
Related Quiz
- Scenario: A company needs to store large amounts of archival data that is rarely accessed. Which storage class of Google Cloud Storage should they use, and why?
- What are the benefits of using templates in Cloud Deployment Manager?
- How does Cloud DNS handle DNS queries to ensure high availability and low latency?
- _______ is a feature of AI Platform that allows users to automatically select the best hyperparameters for their machine learning models.
- What is the primary advantage of using Cloud SQL over managing your own database servers?