Restricting SageMaker Notebook Access to a Specific IAM Role

Which TWO actions are recommended best practices for securing an Amazon SageMaker notebook instance? (Select TWO.)

⚠ Common exam trap

Test-takers frequently confuse network-level controls (network ACLs) with API-level controls (IAM/VPC endpoints), or they mistakenly think Multi-AZ applies to all AWS services, when in fact it is specific to database and high-availability services.

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

✓

Use AWS KMS to encrypt the notebook instance's storage volume.

Option C is correct because SageMaker notebook instances store data on an attached EBS volume, and AWS best practices recommend encrypting that storage with an AWS KMS customer managed key to protect data at rest, including notebooks, scripts, and artifacts. Option E is correct because disabling direct internet access forces the notebook instance to route traffic through a VPC (with NAT gateway or VPC endpoints), which prevents unauthorized outbound access and helps protect against data exfiltration while still allowing controlled access to AWS services. Option A is not a recommended best practice for securing a notebook instance because network ACLs are stateless subnet-level controls and do not govern SageMaker API calls, which are authorized via IAM policies and VPC endpoint policies. Option B is incorrect because Multi-AZ deployment is not a feature of SageMaker notebook instances; they run in a single Availability Zone. Option D is incorrect because placing a notebook instance in a public subnet with an internet gateway exposes it to inbound internet traffic and violates the recommendation to keep notebook instances in private subnets without direct internet access.

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 network ACLs to restrict API calls to the SageMaker API.
Why it's wrong here
Network ACLs filter subnet-level IP traffic; they do not govern authenticated API calls to the SageMaker control plane, which IAM policies and VPC endpoint policies control. NACLs are tempting as a network control, but they cannot restrict API operations.
✗
Enable Multi-AZ deployment for the notebook instance.
Why it's wrong here
Multi-AZ deployment applies to managed database and compute services, not SageMaker notebook instances, which run in a single subnet within one Availability Zone. It is tempting as a general resilience measure, but notebook security relies on IAM roles, VPC placement and encryption instead.
✓
Use AWS KMS to encrypt the notebook instance's storage volume.
Why this is correct
AWS KMS encryption protects the notebook instance's attached EBS storage volume at rest, satisfying the requirement to secure stored data, including notebooks and datasets. SageMaker integrates natively with customer managed KMS keys, so encryption applies to the volume without altering the instance's runtime behaviour or interrupting interactive development sessions.
✗
Associate the notebook instance with a public subnet that has an internet gateway.
Why it's wrong here
A public subnet with an internet gateway exposes the notebook instance directly to inbound internet traffic, contradicting the isolation that secure notebook configuration requires. Public subnets suit resources deliberately serving external traffic, whereas notebooks should sit in private subnets with controlled egress.
✓
Disable direct internet access for the notebook instance.
Why this is correct
Disabling direct internet access forces the notebook instance to route traffic through a VPC endpoint, removing exposure to the public internet. This satisfies the stem's security requirement by preventing unauthorised outbound access and data exfiltration, a documented SageMaker best practice.

Visual reference

Quick reference

AWS S3 Storage Class Comparison

Storage Class	Min Duration	Retrieval	Use Case
S3 Standard	None	Immediate	Frequently accessed data
S3 Standard-IA	30 days	Immediate	Infrequent access, rapid retrieval
S3 One Zone-IA	30 days	Immediate	Non-critical infrequent data
S3 Intelligent-Tiering	None	Immediate–hours	Unknown or changing access patterns
S3 Glacier Instant	90 days	Milliseconds	Archive with instant retrieval
S3 Glacier Flexible	90 days	Minutes–hours	Archive, flexible retrieval
S3 Glacier Deep Archive	180 days	Hours	Long-term compliance archive

Go deeper

Restricting SageMaker Notebook Access to a Specific IAM Role

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

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