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Zorluk: ZorPlanning Serverless Compute Options (Cloud Run and Cloud Functions)

An enterprise health-tech company is designing a serverless telemetry and diagnostic platform on Google Cloud. The system consists of two distinct workload components:

1. Workload 1: A diagnostic image processing microservice that relies on custom-compiled C++ binaries, requires handling up to 50 concurrent HTTP/2 requests per instance, and executes batch image transformations lasting up to 30 minutes.
2. Workload 2: A lightweight Node.js event handler that parses metadata whenever a diagnostic JSON report is uploaded to a Cloud Storage bucket and saves the parsed data to Cloud Firestore.

Which serverless compute configurations should the architecture team choose to meet these requirements while optimizing for operational efficiency? (Select TWO.)

  1. Deploy Workload 1 to Cloud Run because it supports custom container images containing native binary dependencies, HTTP/2 multi-concurrency, and request timeouts up to 60 minutes.Cevap
  2. Deploy Workload 2 to Cloud Functions because it provides a fully managed, event-driven execution environment for lightweight code snippets triggered directly by Cloud Storage bucket events without requiring container management.Cevap
  3. C
    Deploy Workload 1 to Cloud Functions because Cloud Functions provides native multi-container orchestration and execution timeouts up to 2 hours for C++ binaries.
  4. D
    Deploy Workload 2 to Compute Engine virtual machines because Google Cloud serverless options cannot directly integrate with Cloud Storage bucket events.

Cevap

Deploy Workload 1 to Cloud Run to satisfy custom container image, HTTP/2 concurrency, and 30-minute execution timeout demands; deploy Workload 2 to Cloud Functions to handle Cloud Storage events with minimal operational overhead.
Cloud Run is ideal for Workload 1 because it allows deploying arbitrary stateless container images containing custom C++ binaries, supports up to 1000 concurrent requests per instance, and supports request execution timeouts up to 60 minutes. Cloud Functions is ideal for Workload 2 because it offers a simplified, source-code-based deployment model designed for lightweight event handlers that trigger directly from Cloud Storage bucket mutations.

Adım Adım Çözüm

1
Analyze Workload 1 requirements for containerization, concurrency, and timeouts.
Workload 1 requires custom C++ binaries, 50 concurrent HTTP/2 requests per instance, and a 30-minute execution window. These capabilities match Cloud Run, which allows custom container images and supports up to 60-minute request timeouts and multi-concurrency.
Cloud Functions source-based deployment does not easily accommodate custom compiled C++ binary runtimes or container customization required for this workload.
2
Analyze Workload 2 requirements for event triggering and operational overhead.
Workload 2 is a lightweight Node.js snippet triggered by Cloud Storage object creation. Cloud Functions natively integrates with Cloud Storage events and executes code without needing a Docker container pipeline.
Using Cloud Functions for small event-driven snippets minimizes operational maintenance compared to managing containers or VM instances.
3
Select the correct pair of serverless compute options.
Choosing Cloud Run for Workload 1 and Cloud Functions for Workload 2 satisfies all architectural constraints.
This combination aligns each workload with its optimal serverless execution paradigm on Google Cloud.

Anahtar Kavram

Planning serverless compute options by evaluating containerization needs, request concurrency, execution timeout limits, and event trigger mechanisms.
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Planning Serverless Compute Options (Cloud Run and Cloud Functions)

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