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Difficulty: HardSelecting and Designing Compute and Application Platforms

A enterprise logistics company is designing a dual-workload telemetry platform on Google Cloud. The platform consists of two main services:

1. Stateless Ingestion API: Accepts unpredictable bursts of short-lived HTTPS POST requests from IoT devices. The service must automatically scale to zero during off-peak hours to minimize cost, require minimal infrastructure management, and run standard container images.
2. Custom Protocol Engine: Maintains persistent, long-lived TCP socket connections with custom kernel-level TCP buffer configuration (`sysctl`) tunings for legacy gateway hardware.

Which architectural strategy minimizes operational overhead while satisfying the technical requirements of both workloads?

  1. Deploy the stateless Ingestion API on Cloud Run, and deploy the Custom Protocol Engine on Compute Engine Managed Instance Groups (MIGs).Answer
  2. B
    Deploy both the stateless Ingestion API and the Custom Protocol Engine onto a Google Kubernetes Engine (GKE) Standard cluster using custom node pools.
  3. C
    Deploy the stateless Ingestion API on Compute Engine Managed Instance Groups configured to scale strictly on average CPU utilization, and run the Custom Protocol Engine on Cloud Run.
  4. D
    Deploy both services on Compute Engine Virtual Machines while purchasing 3-year Committed Use Discounts (CUDs) for all instances to cover peak capacity.

Answer

Deploying the stateless Ingestion API on Cloud Run and the Custom Protocol Engine on Compute Engine Managed Instance Groups (MIGs) provides the optimal balance of scale-to-zero serverless efficiency and low-level OS configuration control.
The solution correctly assigns stateless HTTPS API workloads with bursty traffic patterns to Cloud Run (achieving zero operational overhead and automatic scaling to zero) while placing the custom protocol workload requiring OS kernel tuning on Compute Engine MIGs.

Step-by-Step Solution

1
Evaluate the Stateless Ingestion API requirements
Identified HTTPS payload handling, unpredictable bursty traffic, requirement to scale to zero, containerized packaging, and minimal management overhead.
Cloud Run is the recommended serverless compute platform on Google Cloud for stateless HTTP/HTTPS containerized services requiring automatic scale-to-zero functionality.
2
Evaluate the Custom Protocol Engine requirements
Identified persistent long-lived TCP socket connections and OS kernel-level tuning (`sysctl`).
Compute Engine Virtual Machines or MIGs provide full access to the underlying guest OS kernel parameters required for specialized network buffer tuning.
3
Combine compute platforms to optimize operational overhead and cost
Selected Cloud Run for the API ingestion layer and Compute Engine MIGs for the OS-customized protocol layer.
Decoupling workloads onto purpose-fit GCP compute platforms minimizes operational toil and prevents paying for unnecessary control planes or unused baseline instances.

Key Concept

Compute Platform Selection Strategy (Cloud Run vs Compute Engine MIGs vs GKE)
Estimated Time:2m 0s
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Topics

Selecting and Designing Compute and Application Platforms