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Google PCA Practice Question: Implement an event-driven architecture where…
A company wants to implement an event-driven architecture where uploads to a Cloud Storage bucket trigger processing in a serverless function. The function must process each object within a few seconds and handle bursts of thousands of uploads. Which service should they use?
⚠ Common exam trap
Candidates often mistakenly think that container-based or VM-based services like GKE, Cloud Run for Anthos, or Compute Engine can handle event-driven bursts as efficiently as Cloud Functions, ignoring the cold-start latency and management overhead.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Cloud Functions
Cloud Functions is the correct choice because it is a fully managed, event-driven serverless compute service that natively triggers on Cloud Storage bucket events (e.g., object finalize/create). It automatically scales from zero to thousands of concurrent invocations within seconds, meeting the burst requirement, and has a maximum timeout of 9 minutes (well above the 'few seconds' requirement).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Google Kubernetes Engine
Why it's wrong here
GKE requires managing node pools and cluster capacity, and object events need extra plumbing rather than direct invocation, so per-object latency and burst handling suffer. It is tempting because Kubernetes offers fine-grained control, which suits containerised microservices rather than simple event-triggered functions.
- ✗
Cloud Run for Anthos
Why it's wrong here
Cloud Run for Anthos runs containerised workloads on Kubernetes clusters, requiring cluster provisioning and no native Cloud Storage event trigger with per-object invocation. It is tempting because it executes containers serverlessly, which suits request-driven HTTP services rather than bursty object-upload event processing.
- ✗
Compute Engine with autoscaling
Why it's wrong here
Compute Engine autoscaling manages VM instances, which take minutes to boot and cannot react to thousands of individual object events within seconds. It is tempting because autoscaling handles sustained load economically, and would be correct for long-running compute rather than per-object event-driven invocation.
- ✓
Cloud Functions
Why this is correct
Cloud Functions scales automatically per event, invoking once per object upload and completing within seconds, which satisfies the burst requirement of thousands of concurrent uploads. Its event-driven trigger integrates natively with Cloud Storage object-finalise notifications, avoiding polling overhead and keeping per-invocation cost low.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
Go deeper
Related to this question
Learn chapter
IAM Policies, Service Accounts, and Auditing
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
Key term
Event-driven architecture
Event-driven architecture is a software design pattern where components communicate by producing, detecting, and reacting to events, enabling decoupled, scalable, and responsive systems.
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Senior Network & Security Engineer · founder of Courseiva
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