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Difficulty: MediumSelecting and Designing Compute and Application Platforms

A renewable energy enterprise is designing the architecture for a new web application backend that ingests real-time telemetry from solar inverter gateways over HTTPS. The application logic is packaged into a stateless container image that requires custom system-level C libraries. Traffic fluctuates heavily throughout the day, dropping to zero during nighttime hours. The engineering team has strict instructions to minimize operational overhead and avoid paying for compute resources when idle. Which compute platform should you recommend to meet these requirements?

  1. Deploy the application container on Cloud Run, setting the minimum number of instances to zero and allowing fully managed autoscaling based on HTTP request concurrency.Answer
  2. B
    Deploy the application container to a Google Kubernetes Engine (GKE) cluster using Standard mode with the Cluster Autoscaler enabled to scale nodes down during off-peak hours.
  3. C
    Deploy the application container across a Compute Engine Managed Instance Group (MIG) using custom VM images, and configure autoscaling strictly based on target CPU utilization.
  4. D
    Provision a fixed cluster of Compute Engine virtual machines covered by a 3-year Committed Use Discount (CUD) to handle the daily peak load at the lowest hourly rate.

Answer

Deploy the application container on Cloud Run, setting the minimum number of instances to zero and allowing fully managed autoscaling based on HTTP request concurrency.
Cloud Run is the optimal Google Cloud compute platform for stateless containerized web microservices with variable HTTP/HTTPS traffic. It supports custom binary dependencies within standard Docker images, abstracts all underlying infrastructure management, and natively scales instances down to zero when no requests are being processed, satisfying the zero idle cost mandate.

Step-by-Step Solution

1
Analyze workload requirements
Identified a stateless containerized web service with custom binary dependencies, variable HTTPS traffic, zero night traffic, and a requirement for minimal operational overhead.
Determining container compatibility and scaling dynamics dictates compute choice.
2
Evaluate candidate compute platforms against constraints
Cloud Run supports arbitrary containers with custom C libraries, automatically scales down to 0 instances when traffic stops, and requires zero infrastructure management.
Serverless containers fit stateless HTTP workloads without cluster management overhead.
3
Eliminate non-optimal options
GKE adds unnecessary cluster management complexity, Compute Engine MIGs require OS maintenance, and Committed Use Discounts lead to paying for unused capacity during zero-traffic periods.
Avoiding operational overhead and idle costs excludes GKE and VM-based options.

Key Concept

Selecting serverless container platforms (Cloud Run) for stateless HTTP workloads with variable demand and zero-scale requirements
Estimated Time:1m 30s
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Topics

Selecting and Designing Compute and Application Platforms