MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
This MLA-C01 practice question tests your understanding of deployment and orchestration of ml workflows. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
A company wants to deploy a trained model to a SageMaker endpoint with automatic scaling based on traffic. Which TWO configurations are required? (Choose two.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set up an Application Auto Scaling policy
Option C is correct because Application Auto Scaling is the AWS service that automatically adjusts the number of instances for a SageMaker endpoint based on demand. You define a scaling policy (e.g., target tracking, step scaling) that tells Auto Scaling when to add or remove instances, which is essential for handling variable traffic without manual intervention.
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.
✗
Use a multi-model endpoint
Why it's wrong here
Multi-model endpoint is not required for auto scaling.
✗
Enable data capture
Why it's wrong here
Data capture is for logging, not scaling.
✓
Set up an Application Auto Scaling policy
Why this is correct
Auto Scaling policy defines how to scale the endpoint.
Related concept
Read the scenario before looking for a memorised answer.
✗
Configure a lifecycle configuration
Why it's wrong here
Lifecycle configuration is for notebook instances, not endpoints.
✓
Create a CloudWatch alarm
Why this is correct
CloudWatch alarm triggers the scaling policy based on a metric.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse 'required configurations for scaling' with 'optional features that improve monitoring or cost efficiency,' leading them to select data capture or multi-model endpoints instead of recognizing that a CloudWatch alarm is the trigger mechanism for the scaling policy.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker integrates with Application Auto Scaling via the `RegisterScalableTarget` API, which registers the endpoint variant as a scalable target. You then create a scaling policy that references a CloudWatch alarm (Option E) — for example, an alarm on the `InvocationsPerInstance` metric — and when the alarm triggers, Auto Scaling adjusts the `DesiredInstanceCount` for the endpoint variant. In a real-world scenario, if traffic spikes during a flash sale, the CloudWatch alarm detects high invocation rates and triggers a step scaling policy to add instances, ensuring low latency without over-provisioning during off-peak hours.
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.
Deployment and Orchestration of ML Workflows — This question tests Deployment and Orchestration of ML Workflows — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set up an Application Auto Scaling policy — Option C is correct because Application Auto Scaling is the AWS service that automatically adjusts the number of instances for a SageMaker endpoint based on demand. You define a scaling policy (e.g., target tracking, step scaling) that tells Auto Scaling when to add or remove instances, which is essential for handling variable traffic without manual intervention.
What should I do if I get this MLA-C01 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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Question Discussion
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