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PROFESSIONAL-CLOUD-DEVELOPER · Question #112

You are developing a marquee stateless web application that will run on Google Cloud. The rate of the incoming user traffic is expected to be unpredictable, with no traffic on some days and large spik

The correct answer is A. Build the application in Python with Firestore as the database. Deploy the application to Cloud. For highly variable and unpredictable traffic - including days with zero traffic - Cloud Run is the optimal compute platform because it scales down to zero instances when idle (incurring no cost) and scales up rapidly during traffic spikes. Paired with Firestore, a serverless and

Building and deploying highly scalable, available, and resilient cloud-native applications

Question

You are developing a marquee stateless web application that will run on Google Cloud. The rate of the incoming user traffic is expected to be unpredictable, with no traffic on some days and large spikes on other days. You need the application to automatically scale up and down, and you need to minimize the cost associated with running the application. What should you do?

Options

  • ABuild the application in Python with Firestore as the database. Deploy the application to Cloud
  • BBuild the application in C# with Firestore as the database. Deploy the application to App Engine
  • CBuild the application in Python with CloudSQL as the database. Deploy the application to App
  • DBuild the application in Python with Firestore as the database. Deploy the application to a

How the community answered

(32 responses)
  • A
    81% (26)
  • B
    3% (1)
  • C
    9% (3)
  • D
    6% (2)

Explanation

For highly variable and unpredictable traffic - including days with zero traffic - Cloud Run is the optimal compute platform because it scales down to zero instances when idle (incurring no cost) and scales up rapidly during traffic spikes. Paired with Firestore, a serverless and fully managed NoSQL database that also scales automatically, the entire stack costs nothing when unused and handles bursts efficiently. Option B (C# on App Engine flexible) and Option C (App Engine with Cloud SQL) either use languages/runtimes less suited for serverless-scale-to-zero or include Cloud SQL, which has a minimum hourly cost even when idle. Option D (deploying to a VM-based solution) requires manual scaling and incurs cost even during zero-traffic periods.

Topics

#Serverless Computing#Cost Optimization#Auto Scaling#Database Selection

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