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Difficulty: MediumPlanning and Assessing Cloud Compute Solutions

A medical device company is evaluating Google Cloud compute solutions for two new application workloads:

1. Workload Alpha: An event-driven task that processes uploaded medical images whenever a new file arrives in a Cloud Storage bucket. Each processing task takes 10 to 15 seconds to execute a Python metadata extraction script.
2. Workload Beta: A legacy web service packaged as a container image that requires custom OS-level kernel tuning (sysctl parameters) and specific root privileges on the underlying host node.

Which TWO deployment choices should the team select to satisfy the technical requirements of these workloads while following Google Cloud architectural best practices? (Select TWO)

  1. Deploy Workload Alpha on Cloud Functions triggered directly by Cloud Storage event notifications.Answer
  2. Deploy Workload Beta on Google Kubernetes Engine (GKE) Standard clusters using custom node pools.Answer
  3. C
    Deploy Workload Alpha on Compute Engine Spot VMs running a continuous polling script.
  4. D
    Deploy Workload Beta on Google Kubernetes Engine (GKE) Autopilot mode.
  5. E
    Deploy Workload Beta on Cloud Run to leverage automatic instance scaling to zero.

Answer

Deploying Workload Alpha on Cloud Functions and deploying Workload Beta on Google Kubernetes Engine (GKE) Standard clusters.
Cloud Functions is designed specifically for event-driven processing triggered by Cloud Storage events with zero infrastructure management. For workloads requiring explicit host OS kernel modifications such as custom sysctl settings, GKE Standard provides full operational control over node pools and underlying virtual machine configurations.

Step-by-Step Solution

1
Analyze Workload Alpha requirements
Workload Alpha requires short (10-15 seconds) event-driven execution upon file creation in Cloud Storage.
Cloud Functions (or Cloud Run with Eventarc) is specifically designed for quick, event-triggered serverless execution without managing infrastructure.
2
Analyze Workload Beta requirements
Workload Beta requires custom OS-level kernel tuning (sysctl parameters) and host root access.
Fully managed environments like Cloud Run and GKE Autopilot restrict host node access and kernel configuration. GKE Standard provides administrator access to node configurations via custom node pools.
3
Combine the optimal service choices
Match Workload Alpha to Cloud Functions and Workload Beta to GKE Standard.
This pairing minimizes management overhead for the event-driven task while meeting the strict host-level customization demands of the legacy workload.

Key Concept

Selecting GCP Compute Services Based on Workload Granularity and Host OS Control Requirements
Estimated Time:1m 30s
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Topics

Planning and Assessing Cloud Compute Solutions

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