Professional Cloud ArchitectAnalyze and optimize technical and business processesEasy
A global media company is building a new content delivery platform on Google Cloud. They anticipate highly variable traffic patterns, with significant spikes during major live events and holiday seasons, followed by periods of low activity. The company wants to ensure high availability and responsiveness during peak loads while minimizing costs during off-peak times. They also need to rapidly scale their compute resources up and down based on demand. Which Google Cloud compute strategy is MOST appropriate for this scenario?
- AProvision a fixed number of large Compute Engine instances and manually scale them.
- BUtilize Managed Instance Groups (MIGs) with autoscaling policies based on CPU utilization and HTTP load balancing.
- CDeploy applications on Google Kubernetes Engine (GKE) with a fixed number of nodes and manual pod scaling.
- DUse App Engine Standard environment with manual scaling configurations.
Show answer & explanationAnswer & explanation
Correct answer: B. Utilize Managed Instance Groups (MIGs) with autoscaling policies based on CPU utilization and HTTP load balancing.
Managed Instance Groups (MIGs) with autoscaling and HTTP(S) Load Balancing are designed for scenarios with variable traffic, allowing automatic scaling up during peaks and scaling down during lulls, optimizing both availability and cost efficiency. This directly addresses the company's requirements.
Why the other options are wrong
- A. Manual scaling does not meet the requirement for rapid, automatic scaling and cost optimization during variable traffic.
- C. A fixed number of GKE nodes with manual pod scaling does not provide the automatic infrastructure scaling needed for cost efficiency and rapid response to variable traffic.
- D. App Engine Standard with manual scaling lacks the automatic scaling capabilities required for cost optimization and responsiveness to highly variable traffic.
Managed Instance Groups (MIGs)
Managed Instance Groups (MIGs) allow you to run apps on multiple identical VMs, offering autoscaling, autohealing, and load balancing for high availability and scalability.
- Automates instance creation and deletion based on demand.
- Integrates with load balancing for traffic distribution.
- Provides autohealing by recreating unhealthy instances.
Memory trick: Always Scale Up, Scale Down, Keep Costs Low.