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Answer: Implement Workflows to orchestrate the image processing tasks. Use Cloud Logging for workflow monitoring.
The question requires an efficient, scalable solution for image processing and workflow monitoring with minimal effort. Option C is correct because Google Cloud Workflows is designed for serverless orchestration of tasks, allowing easy automation of resizing, cropping, and watermarking as steps in a workflow. Cloud Logging integrates naturally for monitoring workflow execution logs. Other options have drawbacks: Option A uses Dataproc (for big data, not monitoring) and Cloud Composer (overly complex for simple workflows). Option B includes Apigee (unnecessary for the requirements) and lacks orchestration. Option D relies on Cloud Build (CI/CD tool, not event-driven for image processing) and Cloud Functions without proper orchestration. Workflows (C) provides the simplest, most scalable approach.
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How can you automate image processing tasks (resizing, cropping, watermarking) and workflow monitoring with minimal effort while ensuring scalability for large volumes of images in a Google Cloud environment?
A
Employ Cloud Composer to manage the image processing workflows. Use Dataproc for workflow monitoring and analytics.
B
Use Cloud Run to deploy the image processing functions. Use Apigee to expose the API. Use Cloud Logging for workflow monitoring.
C
Implement Workflows to orchestrate the image processing tasks. Use Cloud Logging for workflow monitoring.
D
Use Cloud Build to trigger Cloud Functions for the image processing tasks. Use Cloud Monitoring for workflow monitoring.