Google Professional Cloud Developer Question 441
Single answerGoogle Cloud PlatformYou are developing a serverless application on Google Cloud that processes incoming data from IoT devices. Due to high request volumes, you want to optimize the API usage and reduce the number of requests made to an external backend service by batching them together. Which approach would best achieve this in a scalable and cost-efficient manner?
- A
Use Google Cloud Pub/Sub to collect incoming data and use Cloud Functions to batch messages before sending them to the backend service.
- B
Set up multiple Compute Engine instances to handle incoming requests and write custom logic to batch them before sending to the backend service.
- C
Use Firebase Realtime Database to collect incoming data and perform batching with Firebase Functions before sending them to the backend.
- D
Use Cloud Tasks to queue incoming requests and batch them at regular intervals using an App Engine application.
Show answer and explanation
Correct answer: A
Explanation
Using Google Cloud Pub/Sub to collect incoming IoT data and Cloud Functions to process and batch the messages before sending them to an external backend service is the most scalable and cost-efficient solution. Pub/Sub can handle high-throughput data ingestion, and Cloud Functions can process batches of messages without requiring custom server management. This approach leverages Google Cloud's serverless offerings to simplify development and optimize resource usage.
- A. Correct.
Correct. Google Cloud Pub/Sub is designed to handle high volumes of messages and can act as a buffer for incoming data. Cloud Functions can then process these messages in batches and send them to the backend service, making this a scalable and cost-efficient solution.
- B. Incorrect.
Incorrect. While Compute Engine can be used to handle incoming requests, managing multiple instances and writing custom batching logic increases operational overhead and is not as scalable or cost-efficient as serverless solutions like Pub/Sub and Cloud Functions.
- C. Incorrect.
Incorrect. Firebase Realtime Database is not optimized for high throughput IoT data ingestion and batching. While Firebase Functions could be used, it is not the best approach for this scenario compared to Pub/Sub and Cloud Functions.
- D. Incorrect.
Incorrect. Cloud Tasks is designed for managing asynchronous task execution and retries, but it does not inherently support batching tasks. App Engine applications would require additional custom logic to implement batching, making it less efficient.