Question 614 of 1,000
Serving and Scaling ModelseasyMultiple ChoiceObjective-mapped

PMLE Serving and Scaling Models Practice Question

This PMLE practice question tests your understanding of serving and scaling models. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Your company runs a high-traffic web application that serves the same machine learning model prediction for many identical requests (e.g., product recommendations for the same user profile). You want to reduce latency and load on the prediction endpoint by caching responses. Which Google Cloud service should you use?

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 Memorystore

Cloud Memorystore (B) is correct because it provides a managed in-memory cache (Redis or Memcached) that can store the results of identical prediction requests, reducing latency and load on the prediction endpoint. By caching responses keyed on the user profile or request parameters, subsequent identical requests can be served directly from Memorystore in microseconds, avoiding redundant model inference.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Cloud CDN

    Why it's wrong here

    Cloud CDN caches static content at edge locations, not dynamic API responses.

  • Cloud Memorystore

    Why this is correct

    Memorystore (Redis) provides low-latency caching for prediction responses.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Cloud Spanner

    Why it's wrong here

    Spanner is a relational database, not a cache; it is not designed for sub-millisecond caching.

  • BigQuery

    Why it's wrong here

    BigQuery is an analytics warehouse, not suitable for real-time caching.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates confuse caching at the edge (CDN) with caching at the application layer (Memorystore), assuming any cache service works for dynamic API responses, but Cloud CDN cannot cache POST requests or application-specific payloads without significant configuration and still lacks the fine-grained key-value semantics needed for identical prediction requests.

Detailed technical explanation

How to think about this question

Cloud Memorystore for Redis supports TTL-based key expiration, allowing cached predictions to automatically invalidate after a configurable period (e.g., 5 minutes) to balance freshness and performance. In a real-world scenario, a product recommendation service might cache per-user profile results with a TTL of 10 minutes, reducing prediction endpoint load by 80% while still serving reasonably up-to-date recommendations. Under the hood, Redis uses an in-memory data store with sub-millisecond read latencies, making it ideal for caching identical inference requests that would otherwise require expensive model computation.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this PMLE question test?

Serving and Scaling Models — This question tests Serving and Scaling Models — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Cloud Memorystore — Cloud Memorystore (B) is correct because it provides a managed in-memory cache (Redis or Memcached) that can store the results of identical prediction requests, reducing latency and load on the prediction endpoint. By caching responses keyed on the user profile or request parameters, subsequent identical requests can be served directly from Memorystore in microseconds, avoiding redundant model inference.

What should I do if I get this PMLE question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jul 4, 2026

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This PMLE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PMLE exam.