Professional Cloud ArchitectAnalyze and optimize technical and business processesEasy
A large e-commerce company experiences significant traffic spikes during seasonal sales events, leading to inconsistent website performance and occasional outages. Their current infrastructure is primarily on-premises, with some non-critical services migrated to Google Cloud. They want to ensure high availability and responsiveness for their main website during these peak times while optimizing costs. Which Google Cloud strategy should they prioritize?
- AImplement autoscaling for their web servers and frontend applications using Managed Instance Groups (MIGs) and Cloud Load Balancing.
- BMigrate all on-premises databases to Cloud SQL to improve data consistency.
- CRefactor their monolithic application into microservices running on Google Kubernetes Engine (GKE).
- DTransition their batch processing jobs to Dataflow to handle large data volumes efficiently.
Show answer & explanationAnswer & explanation
Correct answer: A. Implement autoscaling for their web servers and frontend applications using Managed Instance Groups (MIGs) and Cloud Load Balancing.
Autoscaling with Managed Instance Groups (MIGs) and Cloud Load Balancing directly addresses the problem of inconsistent website performance and outages during traffic spikes by dynamically adjusting resources to meet demand, while optimizing costs by scaling down during low traffic.
Why the other options are wrong
- B. Migrating databases to Cloud SQL improves data consistency and manageability but doesn't directly solve the scaling issues of the web servers during traffic spikes.
- C. Refactoring to microservices on GKE is a longer-term architectural change that would enable better scalability, but implementing autoscaling for existing web servers is a more immediate and direct solution to the described problem of traffic spikes and performance during sales events.
- D. Dataflow is for batch or stream processing and doesn't directly impact the real-time performance of the main website during traffic spikes.
Autoscaling with MIGs
Google Cloud's Managed Instance Groups (MIGs) automatically adjust the number of VM instances in a group based on defined policies, often combined with Cloud Load Balancing to distribute traffic efficiently.
- Dynamically scales compute resources up or down.
- Ensures application availability and performance during variable loads.
- Optimizes costs by only paying for resources when needed.
Memory trick: Auto-scaling is like a flexible team, always having just enough people to handle the rush.