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Difficulty: HardPlanning Serverless Compute Options (Cloud Run and Cloud Functions)

A cloud architecture team at a healthcare organization is evaluating Google Cloud serverless options for two distinct microservices:

1. Service A: A legacy enterprise Java application packaged as a custom Docker container image listening on port 8080. It requires request concurrency (handling multiple concurrent HTTP requests per instance) and high memory allocation (up to 16 GB RAM).
2. Service B: A lightweight event-driven background handler written in Node.js that runs for under 30 seconds to extract metadata whenever a new patient record file is uploaded to a Cloud Storage bucket.

Which TWO deployment decisions correctly align with Google Cloud serverless compute best practices for these requirements? (Select TWO.)

  1. Deploy Service A to Cloud Run because it supports custom container images, multi-request concurrency per instance, and high memory configurations.Answer
  2. B
    Deploy Service A to Cloud Functions (1st gen) because it automatically converts legacy custom container images into serverless function packages with multi-request concurrency.
  3. Deploy Service B to Cloud Functions (or Cloud Functions 2nd gen) triggered by Cloud Storage bucket events to execute code directly without maintaining container infrastructure.Answer
  4. D
    Deploy Service B to Compute Engine Managed Instance Groups with an External HTTP Load Balancer to capture Cloud Storage file upload events natively.

Answer

The correct architectural decisions are deploying Service A to Cloud Run and deploying Service B to Cloud Functions.
Deploying Service A to Cloud Run is correct because Cloud Run fully supports custom Docker containers, configurable memory up to 32 GB, and request concurrency on a single instance. Deploying Service B to Cloud Functions is correct because it natively integrates with Cloud Storage events to execute lightweight event handlers without needing dedicated container builds or compute management.

Step-by-Step Solution

1
Analyze the requirements for Service A
Service A requires deploying a custom Docker container listening on port 8080, handling concurrent requests per instance, and allocating up to 16 GB RAM.
Cloud Run is the appropriate serverless compute service for containerized workloads that require custom runtimes, high memory limits, and request concurrency.
2
Analyze the requirements for Service B
Service B is a short-running (under 30 seconds), lightweight Node.js event handler triggered directly by Cloud Storage object upload events.
Cloud Functions is optimized for event-driven snippets responding to cloud events without requiring container packaging or infrastructure management.
3
Evaluate the combined choices against Google Cloud serverless options
Selecting Cloud Run for Service A and Cloud Functions for Service B satisfies all technical constraints with minimum operational complexity.
Matching workload paradigms to service strengths ensures cost efficiency, scaling performance, and alignment with GCP best practices.

Key Concept

Selecting serverless compute execution paradigms based on container requirements, concurrency settings, and event trigger mechanisms.
Estimated Time:2m 0s
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Topics

Planning Serverless Compute Options (Cloud Run and Cloud Functions)

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