Question 109 of 835
easyMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A machine learning engineer is deploying a model…
A machine learning engineer is deploying a model using AWS Lambda for inference. The model is a small scikit-learn classifier with a size of 50 MB. The Lambda function is invoked by an API Gateway REST API. The engineer notices that cold starts are causing high latency. Which action would most effectively reduce cold start latency without increasing costs significantly?
⚠ Common exam trap
Many exam-takers confuse 'reducing cold start latency' with 'reducing compute time' or 'improving model loading speed', leading them to choose options like increasing memory or using EFS, which do not address the fundamental issue of environment initialization.
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
✓
Configure provisioned concurrency for the Lambda function.
Provisioned concurrency pre-initializes the Lambda execution environment, keeping it warm and ready to handle requests immediately. This eliminates the cold start overhead for the first request, directly reducing latency without incurring the ongoing costs of a larger memory allocation or the complexity of EFS/container management.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Store the model in Amazon EFS and load it at runtime.
Why it's wrong here
Loading from EFS adds latency and does not prevent cold starts; it only reduces deployment size.
- ✗
Increase the Lambda function memory to the maximum of 10,240 MB.
Why it's wrong here
More memory increases cost and may not eliminate cold starts; it only reduces CPU-bound latency.
- ✓
Configure provisioned concurrency for the Lambda function.
Why this is correct
Provisioned concurrency keeps instances initialized and ready to respond immediately.
- ✗
Package the model in a container image and deploy using Lambda container support.
Why it's wrong here
Container images have similar cold start behavior; larger images may even increase cold start time.
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 |
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Last reviewed: Jun 24, 2026
This MLA-C01 practice question is part of Courseiva's free Amazon Web Services 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 MLA-C01 exam.
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