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Zorluk: OrtaSelecting and Designing Compute and Application Platforms

An enterprise architectural team is designing a modernized data ingestion pipeline on Google Cloud. The system includes two separate workloads with distinct runtime requirements:

1. Event Ingestion Webhook: A lightweight HTTP service that receives intermittent data payloads, experiences rapid traffic spikes, requires scale-to-zero capacity during idle periods, and must minimize operational management overhead.
2. Custom Analytics Engine: A long-running backend data processing application that requires specific Linux kernel parameters (`sysctl` network tuning) and direct hardware device driver access.

Which TWO platform architectural decisions should you recommend to meet these requirements efficiently?

  1. Deploy the Event Ingestion Webhook on Cloud Run to leverage fully managed serverless container execution with automatic scaling to zero.Cevap
  2. Deploy the Custom Analytics Engine on Google Kubernetes Engine (GKE) with custom node pools configured for kernel tuning and specialized node setup.Cevap
  3. C
    Deploy the Event Ingestion Webhook on a multi-zone GKE cluster using Standard node pools to ensure baseline compute capacity is available for webhooks.
  4. D
    Deploy the Custom Analytics Engine on Cloud Run container instances with maximum CPU allocations.
  5. E
    Deploy both workloads together on App Engine Standard environment to minimize overall service deployment configuration.

Cevap

Deploying the Event Ingestion Webhook on Cloud Run and deploying the Custom Analytics Engine on Google Kubernetes Engine (GKE) with custom node configurations represent the optimal architectural design.
Cloud Run is optimized for stateless HTTP containers requiring automatic scaling to zero with zero infrastructure management. Google Kubernetes Engine (GKE) provides full node-level access and daemonset capabilities to apply custom sysctl kernel parameters and OS drivers for specialized batch processing.

Adım Adım Çözüm

1
Analyze the requirements for the Event Ingestion Webhook service.
The webhook service is stateless, handles HTTP traffic, experiences variable/intermittent load, requires scaling to zero instances, and demands low operational overhead.
Cloud Run provides serverless container hosting that automatically scales down to zero when no requests arrive and requires no cluster management.
2
Analyze the requirements for the Custom Analytics Engine.
The engine requires custom host environment settings (`sysctl` network parameter tuning) and hardware access.
Container sandboxes like Cloud Run do not grant kernel modification permissions. GKE nodes (or Compute Engine instances) are required when low-level OS/kernel customizations are mandatory.
3
Select the optimal combination of compute platforms.
Cloud Run for the webhook service and GKE with custom node configurations for the analytics engine.
This combination minimizes operational cost for the stateless endpoint while satisfying the low-level technical constraints of the processing engine.

Anahtar Kavram

Selecting GCP Compute Platforms Based on Workload Characteristics and OS Level Access
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Selecting and Designing Compute and Application Platforms