SAA-C03 Amazon Web Services AWS Certified Solutions Architect - Associate (SAA-C03) Free Practice Exam Questions (2026 Updated)

Amazon S3 presigned URLs are the most secure fit because they providetime-limited access to specific objectswithout requiring the external vendor to have AWS credentials or direct bucket permissions. AWS documentation states that presigned URLs grant temporary access to private S3 objects and can be used for downloads through a browser or program. This is stronger than creating an IAM user or sharing temporary keys because those methods still expose AWS credentials to a third party. A bucket policy based only on source IP is broader and less precise than object-level, time-bounded access. Presigned URLs let the company control exactlywhich objectcan be downloaded andfor how long, which is exactly what the scenario requires. (AWS Documentation)

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AWS Backup supports cross-Region backup for Amazon EFS, allowing automated, scheduled backups and replication to another Region. This managed service simplifies backup management and ensures data resilience without the need for custom scripts or manual processes

AWS Lake Formationis designed for managing fine-grained access control to data in an efficient manner:

Granular Permissions: Lake Formation allows column-level, row-level, and table-level access controls, which can precisely define access to PII data.

Integration with AWS Glue Catalog: Lake Formation natively integrates with AWS Glue for seamless data cataloging and access control.

Operational Efficiency: Centralized access control policies minimize the need for separate IAM roles or policies.

Why Other Options Are Not Ideal:

Option A:

Creating multiple IAM policies introduces complexity and lacks column-level access control.Not efficient.

Option B:

Managing multiple IAM roles for granular access is operationally complex.Not efficient.

Option D:

Creating views in Glue adds unnecessary complexity and may not provide the level of granularity that Lake Formation offers.Not the best choice.

AWS References:

AWS Lake Formation:AWS Documentation - Lake Formation

Fine-Grained Permissions with Lake Formation:AWS Documentation - Fine-Grained Permissions

Amazon Cognitoprovides scalable, serverless authentication, andLambda@Edgeis used for authorization, providing low-latency access control at the edge.Amazon CloudFrontserves the web application globally with reduced latency and ensures secure access for users around the world. This solution minimizes operational overhead while providing scalability and security.

Option B (Directory Service): Directory Service is more suitable for enterprise use cases involving Active Directory, not for web-based applications.

Option C (S3 Transfer Acceleration): S3 Transfer Acceleration helps with file transfers but does not provide authorization features.

Option D (Elastic Beanstalk): Elastic Beanstalk adds unnecessary overhead when CloudFront can handle global delivery efficiently.

AWS References:

Amazon Cognito

Lambda@Edge

Spot Instances are the best pricing model because the jobscan tolerate interruptions, and the company wants the most cost-effective option. AWS recommends theprice-capacity-optimizedstrategy for Spot because it selects pools that balancelow pricewithlower interruption risk. Using multiple instance types in the Auto Scaling group also helps the company stay flexible enough to adopt newer generations over time. Reserved Instances do not fit as well because they reduce flexibility and do not align with the requirement to keep shifting toward the latest instance generations each year. Capacity-optimized alone minimizes interruption risk, but AWS recommends price-capacity-optimized when you want both lower interruption rates and better prices. Therefore, Spot with price-capacity-optimized allocation is the strongest answer.

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Detailed Explanation:

A. EventBridge Rule:Detects modifications to CloudFront distributions in real time and triggers the Lambda function for further action.

B. ALB + Config:Focuses on ALB security violations, not relevant for CloudFront logging changes.

C. Lambda + SNS:Provides real-time notifications about changes in logging configuration.

D. GuardDuty:Focuses on threat detection, not logging configuration changes.

E. API Gateway + WAF:Unrelated to CloudFront logging changes.

Amazon DynamoDB supports both TTL (Time to Live) for automatic deletion and Point-in-Time Recovery (PITR) for backup and restore of table data. It ' s ideal for frequently updated data with short retention requirements and minimal operational overhead.

TTL attribute ensures expired items are automatically removed.

PITR enables recovery from accidental deletes or application errors.

AWS Transfer Family: This service provides fully managed support for file transfers directly into and out of Amazon S3 using the SFTP, FTPS, and FTP protocols.

SFTP Endpoints:

Set up an AWS Transfer Family server and configure SFTP endpoints to handle the file transfers.

This service is scalable and managed, reducing operational overhead compared to running an SFTP solution on EC2 instances.

Integration with Active Directory:

Choose the AWS Directory Service option as the identity provider for the Transfer Family server.

Use AD Connector to link the on-premises Active Directory with AWS, allowing employees to use their existing AD credentials to access the SFTP service.

Operational Efficiency: This solution leverages managed services for both file transfer and identity management, ensuring minimal changes to the current authentication mechanisms and reducing operational overhead.

EBS Encryption:

Default EBS Encryption: Can be enabled for new EBS volumes.

Use of AWS KMS: Specify AWS KMS keys to handle encryption and decryption of data transparently.

Amazon RDS Encryption:

RDS Encryption: Encrypts the underlying storage for RDS instances using AWS KMS.

Configuration: Enable encryption when creating the RDS instance or modify an existing instance to enable encryption.

Least Amount of Changes:

Both EBS and RDS support seamless encryption with AWS KMS, requiring minimal changes to the existing infrastructure.

Enables compliance with regulatory requirements without modifying the application.

Operational Efficiency: Using AWS KMS for both EBS and RDS ensures a consistent, managed approach to encryption, simplifying key management and enhancing security.

Amazon RDS Proxyis the correct answer because it is specifically designed to improve connection handling for relational databases, including Aurora. AWS documentation explains that RDS Proxy providesconnection pooling, helps handleunpredictable surges in database traffic, and automatically determines the current Aurora writer instance. That reduces the stress of large numbers of short-lived connections and improves application behavior during failover events because clients reconnect through the proxy rather than directly to database endpoints. Switching database engines would be unnecessary and disruptive. DAX is for DynamoDB, not Aurora. Therefore, placingRDS Proxyin front of the Aurora cluster is the most direct way to reduce connection pressure and improve failover behavior. (AWS Documentation)

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The application must stay private in bothnetwork accessandDNS resolution. Aninternal ALBensures the load balancer is reachable only from within the VPC or connected private networks. ARoute 53 private hosted zoneensures the DNS name is resolvable only from associated VPCs. AWS documentation states that private hosted zones return answers only when queries come from associated VPCs or approved hybrid resolvers, while queries from outside are not resolved from that private zone. A public hosted zone would expose DNS resolution publicly, and an internet-facing ALB would violate the private-access requirement. Therefore, the correct solution isan internal ALB plus a private hosted zone. (AWS Documentation)

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The correct answer isBbecause the company needs order processing to beginimmediatelywhen new orders arrive and also needs ahistory of all order processing attemptsin themost cost-effectiveway. Amazon EventBridge is a serverless event bus that can respond to events as they occur, which makes it a strong fit for near real-time order processing. By using anEventBridge event patternand a rule that invokesAWS Lambdawhen a new order event is received, the solution avoids polling and processes orders only when there is actual work to perform.

This event-driven design is more cost-effective than running scheduled checks or maintaining EC2 instances.AWS Lambdaprovides fully managed compute with automatic scaling and charges based on actual execution time.Amazon DynamoDBis a highly scalable and fully managed NoSQL database that is well suited for storing order-processing results and maintaining a durable history of processing attempts with low operational overhead.

Option A is incorrect because invoking Lambda every minute to check for new orders is a polling model, which introduces delay and unnecessary invocations. Option C is incorrect because using an EC2 instance to poll for events creates higher operational cost and overhead. Option D is less appropriate becauseAmazon EFSis not the best storage choice for durable event history or structured tracking of order-processing attempts.

AWS architectural guidance favorsevent-driven, serverless patternsfor asynchronous order processing when immediate response, scalability, and low cost are required. Therefore,EventBridge + Lambda + DynamoDBis the best solution.

Why Option B is Correct:

HTTP Proxy Integration: Passes XML requests directly to the application, which already supports XML.

JSON Conversion: An AWS Lambda function converts JSON requests to XML and calls the application.

API Gateway: Acts as a front end to handle JSON requests and integrates seamlessly with Lambda for the transformation process.

Why Other Options Are Not Ideal:

Option A: Suggests using API Gateway mappings to convert JSON to XML. API Gateway mapping templates are limited in functionality and are not ideal for complex transformations.

Option C and D: Use HTTP custom integration unnecessarily, which adds complexity without additional benefits.

AWS References:

Amazon API Gateway Integration:AWS Documentation - API Gateway Integration

AWS Lambda:AWS Documentation - Lambda

Amixed Auto Scaling groupwith both On-Demand and Spot Instances is the best answer because AWS documents that mixed instances groups let you launch and automatically scale a fleet of On-Demand and Spot Instances in a single Auto Scaling group to optimize cost while maintaining scale and performance. Since the workload can tolerate occasional disruptions, Spot is appropriate, but keeping some On-Demand capacity adds stability. This is a more practical architecture than moving the whole workload to Spot alone. Continuing with only On-Demand or buying Reserved Instances would not optimize cost as well for variable usage.

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Regulatory compliance often requires immutability, meaning data cannot be altered or deleted by any user, including administrators, during a retention period. Amazon S3 Object Lock in compliance mode is specifically designed for this requirement.

Option B enforces a write-once-read-many (WORM) model. Once compliance mode is enabled and a retention period is set, no one—including root users—can delete or overwrite the objects until the retention expires. This provides the strongest level of protection and satisfies strict regulatory standards.

Option A (governance mode) allows privileged users to override the lock, which may not satisfy regulatory mandates. Option C does not prevent deletion or modification before retention expiration. Option D addresses storage cost, not immutability.

Therefore, B is the correct solution for regulatory-grade data protection.

Amazon API Gateway supportsresource policies, which allow you to control access to your API by specifying the IP addresses or ranges that can access the API. By creating a resource policythat explicitly denies access to any IP address outside the allowed set, you can ensure that only trusted IP addresses (such as those from your internal network) can access the critical information in your API. This approach provides fine-grained access control without the need for additional infrastructure or complex configurations.

Option A (Private integration): API Gateway private integrations are for creating private APIs that are only accessible within a VPC, but this solution is about restricting access to certain IP addresses.

Option C (Private subnet and ACLs): Deploying the API in a private subnet and using network ACLs adds unnecessary complexity and isn ' t the best fit for HTTP APIs.

Option D (Security group): API Gateway doesn ' t have a security group because it isn ' t a resource inside a VPC. Instead, resource policies are the correct mechanism for controlling IP-based access.

AWS References:

Controlling Access to API Gateway with Resource Policies

Amazon EFS is the correct answer because it provides aPOSIX-compliant, shared file systemthat multiple ECS tasks and instances can mount concurrently. AWS documents EFS as a managed NFS file system built for shared access and elastic growth, which fits the requirement for log and configuration sharing across Linux containers.Elastic throughputis the best cost-conscious choice when access patterns can vary, because throughput scales automatically without manual provisioning. S3 is object storage and does not provide native POSIX file system behavior. EBS is block storage and is not the right answer for shared, highly available multi-container access across a distributed environment. FSx for Lustre is optimized for specialized high-performance workloads, not general shared configuration and log storage.

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The IAM policy includes two statements:

1️⃣ Allow ec2:TerminateInstances on all resources

2️⃣ Deny ec2:TerminateInstances if the request does NOT come from:

192.0.2.0/24

203.0.113.0/24

AWS IAM policy evaluation rules state:

Explicit Deny always overrides Allow.

A request must meet all applicable conditions in the policy to be granted.

aws:SourceIp condition applies when IAM actions are invoked via the public AWS APIs.

In this scenario, the administrator is not originating the request from one of the allowed CIDR blocks, so the Deny condition is triggered, overriding the Allow statement.

Therefore, the operation is blocked with:

403 AccessDenied: explicit deny

This matches the behavior described in the AWS IAM Policy Evaluation Logic used in the Security Pillar of the Well-Architected Framework:

Explicit Deny > Allow > Default Deny

IP-based Conditions restrict API calls originating outside approved network ranges

Options A/B/C do not accurately reflect this explicit Deny condition behavior.

AWS Global Accelerator is the best answer because it providesstatic anycast IP addressesand routes users to the optimal healthy endpoint over the AWS global network. AWS documentation explains that Global Accelerator continuously monitors endpoint health and redirects traffic to the next best healthy endpoint almost immediately, which avoids dependence on DNS resolver caching or client-side IP caching. That is especially important for low-latency global applications such as Voice over IP. Route 53 geolocation routing does not provide the same fast failover characteristics, and CloudFront is not the service for generic bidirectional VoIP application traffic. (docs.aws.amazon.com)

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EKS lets teams “run Kubernetes on AWS without needing to install and operate your own Kubernetes control plane,” and with AWS Fargate, you “run Kubernetes pods without managing servers,” reducing operational overhead for worker nodes. For the data layer, Amazon DocumentDB (with MongoDB compatibility) “supports the MongoDB API and drivers,” allowing existing MongoDB applications to work without application changes, while the service “automatically scales storage,” provides “high availability across multiple Availability Zones,” automatic backups, and patching. Because the company cannot change code or deployment methods, keeping Kubernetes (EKS) and the MongoDB API (DocumentDB compatibility) is essential. Options A and C either change the orchestrator (to ECS) or the database API (to DynamoDB), which would require code/deployment changes. Option A also leaves you managing EC2 nodes and a self-managed MongoDB on EC2, increasing ops burden. Therefore, EKS on Fargate + Amazon DocumentDB minimizes operations and preserves compatibility.

Amazon EFS integrates natively with Lambda, supports shared, persistent storage, and allows independent updates without redeploying functions. EBS and /tmp are not supported for this use case; FSx is unnecessary.

Creating aVPC endpointfor S3 and configuring abucket policyto allow access only from the endpoint ensures that only EC2 instances within the VPC can access the S3 bucket. This solutionimproves security by restricting access at the network level without the need for public internet access.

Option A (IAM policies): IAM policies alone cannot restrict access based on the network location.

Option B and D (Encryption): Encryption secures data at rest but does not restrict network access to the bucket.

AWS References:

Amazon S3 VPC Endpoints

Amazon FSx for Lustreis a high-performance, fully managed file system that is ideal for applications requiring low-latency access to shared storage, especially in use cases like gaming where high throughput and low latency are essential. It integrates easily with EC2 instances, providing fast and scalable shared storage, and supports custom protocols for specific application needs.

Option A (FSx File Gateway): FSx File Gateway is designed for hybrid cloud storage and is not suited for high-performance gaming workloads.

Option B (EC2 Windows instance): Setting up a file share on a Windows instance would introduce additional administrative overhead and would not provide the necessary performance.

Option C (EFS with Lustre): While Lustre is integrated with FSx, EFS does not natively support Lustre.

AWS References:

Amazon FSx for Lustre

The lowest-overhead centralized access model is to connect the existingon-premises Active Directoryby usingAD Connectorand then manage AWS account access throughIAM Identity Center permission sets. AWS documentation explains that IAM Identity Center providesone place to assign permissions to multiple AWS accounts, and AD Connector is specifically designed to let AWS services use an existing directory without storing directory information in AWS. This approach preserves the company’s current authentication source and adds centralized authorization across the organization. Creating IAM users or scripting cross-account role assignments would add significant administrative work and weaken the identity model.

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A read replica is the best answer because the new application needs to read frequently changing data while minimizing load on the production writer. Amazon RDS read replicas are designed to offload read traffic from the primary DB instance, which improves overall performance for the main workload. ElastiCache is not the best fit because the application rarely repeats the same query, so a cache would not provide strong benefit. An ALB is unrelated to database querying, and snapshots are not appropriate for querying near-current data. Since the requirement is fresh read access with minimal impact on the primary database, using a read replica is the correct architectural choice.

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Storage Gateway Volume Gateway (Cached Volumes): This configuration allows you to store your primary data in Amazon S3 while retaining frequently accessed data locally in a cache for low-latency access.

Low-Latency Access: Frequently accessed data is cached locally on-premises, providing low-latency access while the less frequently accessed data is stored cost-effectively in Amazon S3.

Implementation:

Deploy a Storage Gateway appliance on-premises or in a virtual environment.

Configure it as a volume gateway with cached volumes.

Create volumes and configure your applications to use these volumes.

Minimal Infrastructure Changes: This solution integrates seamlessly with existing on-premises infrastructure, requiring minimal changes and reducing dependency on on-premises storage servers.

The issue described is a classic case of read-heavy reporting workloads interfering with transactional application traffic. Although the RDS instance is configured for Multi-AZ, Multi-AZ deployments are designed for high availability and failover, not for scaling read performance. All reads and writes still occur on the primary instance, which explains why reporting queries negatively affect customer-facing performance.

Option C, adding an Amazon RDS read replica, is the most effective and AWS-recommended solution. Read replicas asynchronously replicate data from the primary instance and provide a separate endpoint for read-only workloads such as reporting, analytics, and dashboards. By redirecting the finance team’s reporting queries to the replica endpoint, the primary database is freed to handle transactional workloads, significantly improving overall application performance.

Option A (RDS Proxy) helps manage database connections efficiently, especially for bursty workloads, but it does not offload query execution or isolate heavy read traffic. Option B is invalid because RDS Multi-AZ does not support spreading a single DB instance across three AZs, and even if it did, it would not reduce read contention. Option D increases instance resources but does not solve the root cause; reporting queries would still compete with production traffic and would also increase cost unnecessarily.

Therefore, C is the optimal solution because it isolates reporting workloads, scales read capacity, improves application responsiveness, and aligns with AWS best practices for high-performance database architectures.

AWS documentation states that the most secure method for granting private S3 access from VPCs is to use gateway VPC endpoints for Amazon S3. Endpoint policies enforce least privilege by allowing only specific IAM roles access to specific S3 buckets. Because users can obtain temporary credentials through IAM roles, no permanent access keys must be distributed.

S3 bucket policies based on CIDR ranges (Option B) are less secure because CIDR-based access is broader and can grant unintended access. Access points (Option C) still rely on public S3 endpoints unless combined with VPC-only access, which is not stated here. Option D exposes S3 to public internet egress and depends on public IPs, violating least-privilege principles.

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The correct answer isAbecause the company wants engineers to reach aspecific development EC2 instancethrough aRoute 53 hosted zone, while ensuring that traffic continues to route correctlyeven if the development instance is replaced. The best way to achieve this is to point the Route 53 record for the development website to theApplication Load Balancerand then configure anALB listener rulethat forwards requests for the development hostname to adedicated target groupcontaining the development instance.

This design works well because the ALB provides a stable endpoint, and Route 53 can alias the development DNS name to the ALB. If the development EC2 instance is replaced, the target group can simply register the new instance. The DNS record does not need to change, and engineers continue to use the same development URL. This minimizes operational effort and supports automatic continuity.

Option B is incorrect because using a public IP address for a specific instance does not automatically handle instance replacement unless additional manual steps are taken. Option C is incorrect because redirecting users to a public IP is not the intended design and introduces unnecessary exposure and management complexity. Option D is incorrect because placing all instances in the same target group would not ensure that requests for the development website are sent only to the specific development instance.

AWS best practices favor usingload balancers and target groupsas stable routing layers rather than binding DNS names directly to ephemeral instance IP addresses. Therefore, the most reliable and maintainable solution is to useRoute 53 + ALB + a dedicated target groupfor the development instance.

AWS WAF (Web Application Firewall): AWS WAF allows you to create custom rules to block or allow web requests based on conditions that you specify.

Web ACL (Access Control List):

Create a web ACL and associate it with the ALB.

Use IP rule sets to specify the IP addresses of the retail locations that are allowed to access the application.

Security and Flexibility:

AWS WAF provides a scalable way to manage access control, ensuring that only traffic from registered IP addresses is allowed.

You can dynamically update the IP rule sets to add or remove IP addresses as needed.

Operational Simplicity: Using AWS WAF with a web ACL is straightforward and integrates seamlessly with the ALB, providing an efficient solution for managing access control based on IP addresses.

Analysis:

The solution must handle variable sales volumes, preserve transaction information, and store data in an Amazon Aurora database with minimal operational overhead. UsingAPI Gateway, AWS Lambda, and SQSis the best option because it provides scalability, reliability, and resilience.

Why Option A is Correct:

API Gateway: Serves as an entry point for transaction data in a serverless, scalable manner.

AWS Lambda: Processes the transactions and sends them to Amazon SQS for queuing.

Amazon SQS: Buffers the transaction data, ensuring durability and resilience against spikes in transaction volume.

Second Lambda Function: Processes messages from the SQS queue and updates the Aurora database, decoupling the workflow for better scalability.

Dead-Letter Queue (DLQ): Ensures failed transactions are logged for later debugging or reprocessing.

Why Other Options Are Not Ideal:

Option B:

Using an ALB with ECS on EC2 introduces operational overhead, such as managing EC2 instances and scaling ECS tasks.Not cost-effective.

Option C:

EKS is highly operationally intensive and requires Kubernetes cluster management, which is unnecessary for this use case.Too complex.

Option D:

Amazon Data Firehose and DMS are not designed for real-time transactional workflows. They are better suited for data analytics pipelines.Not suitable.

AWS References:

Amazon API Gateway:AWS Documentation - API Gateway

AWS Lambda:AWS Documentation - Lambda

Amazon SQS:AWS Documentation - SQS

Amazon Aurora:AWS Documentation - Aurora

To track costs by department, you must activate the custom department tag as a cost allocation tag in the AWS Organizations management account. Once activated, Cost Explorer and cost and usage reports can group costs by this tag for all linked accounts. The most operationally efficient way is to activate only the relevant department tag and create a cost and usage report grouped by that tag.

AWS Documentation Extract:

“To use a tag for cost allocation, you must activate it in the AWS Billing and Cost Management console. After activation, you can use the tag to group costs in Cost Explorer and reports.”

(Source: AWS Cost Management documentation)

A, E: aws:createdBy is not related to department cost grouping and is unnecessary.

B: Applying extra filters is optional; D is more direct and operationally efficient.

Comprehensive and Detailed Step-by-Step Explanation:

To meet the requirements of copying only relevant data as soon as possible and receiving notifications upon completion, the following steps are recommended:

Generate a Manifest File (Option A):

Action:Modify the on-premises data generation process to create a manifest file at the end of each data generation cycle. This manifest should list the names of the objects that need to be copied to Amazon S3.

Implementation:Develop a custom script that runs after data generation. This script compiles the list of relevant data files into a manifest file and uploads it to a designated S3 bucket.

Justification:Using a manifest allows AWS DataSync to transfer only the specified files, reducing unnecessary data transfer and associated costs.

docs.aws.amazon.com

Automate DataSync Task Execution (Option D):

Action:Set up an S3 Event Notification to trigger an AWS Lambda function whenever a new manifest file is uploaded to the S3 bucket.

Implementation:Configure the Lambda function to invoke the DataSync task by calling the StartTaskExecution API action, specifying the manifest file. This ensures that only the files listed in the manifest are copied from on-premises storage to Amazon S3.

Justification:This automation ensures timely data transfer as soon as relevant data is available, minimizing delays and manual intervention.

docs.aws.amazon.com

Set Up Completion Notifications (Option E):

Action:Create an Amazon SNS topic to handle notifications. Then, establish an Amazon EventBridge rule that monitors the DataSync task execution status and sends an email notification to the SNS topic when the status changes to SUCCESS or ERROR.

Implementation:Configure EventBridge to capture state changes of the DataSync task. When a task completes successfully or encounters an error, EventBridge triggers a notification to the SNS topic, which then sends an email to the subscribed recipients.

Justification:This setup provides immediate feedback on the data transfer process, allowing the analytics team to act promptly based on the success or failure of the data copy operation.

docs.aws.amazon.com

The correct answer isAbecause the legacy mainframe requires asynchronous RESTful APIand the new service takes approximately3 minutesto complete each request. Among the choices,Amazon API Gateway REST APIis the appropriate option for exposing a synchronous REST endpoint to the mainframe. API Gateway REST APIs support longer integration timeouts than HTTP APIs, which makes them more suitable for workloads that take an extended time to process. The REST API can invoke an AWS Lambda function to execute the stock price calculation and return the result synchronously.

Option B is incorrect becauseAPI Gateway HTTP APIshave a shorter integration timeout and are not the best fit for a request that takes around 3 minutes. Option C is incorrect becauseWebSocket APIsare not RESTful and do not meet the requirement for synchronous REST-based integration with the mainframe. Option D is incorrect becauseLambda function URLsdo not provide the same API management features and are not the best choice for a long-running synchronous enterprise integration requirement of this kind.

AWS design guidance favors API Gateway when exposing managed APIs to external consumers. In this case, theREST APIoption best matches the requirement for synchronous RESTful access while supporting the longer processing duration. It also provides a managed front door for authentication, throttling, and operational control if the company needs those features later.

One note of honesty: some exam versions treat the REST API timeout detail as the deciding factor here. That is the key reasonREST APIis preferred overHTTP APIfor this question.

The correct answer isBbecause the company has apredictable baseline workloadthat will run forat least 1 year, plus atemporary 2-week increasein demand during a holiday period. The most cost-effective approach is to use a long-term discount option for the steady-state workload and a flexible pricing model for the short-term burst capacity.

AnEC2 Instance Savings Planis a strong fit for the existing workload because it provides cost savings for committed EC2 usage while matching a stable, predictable application footprint. Since the company is already using EC2 and the workload pattern is known, this is an efficient commitment for the baseline capacity. For the additional temporary holiday demand,On-Demand Instancesare appropriate because the extra capacity is needed only for a short duration. This avoids overcommitting to capacity that will not be used after the holiday period ends.

Option A is less cost-effective because it misses the savings opportunity for the predictable baseline workload. Option C is incorrect because the application is described asstateful, which makesSpot Instancesa poor fit due to potential interruption. Option D is incorrect because purchasing a 12-month commitment for both the normal workload and the temporary holiday increase would likely result in paying for excess committed usage after the 2-week peak ends.

AWS cost optimization guidance recommends usingdiscounted commitment models for steady-state usageandOn-Demandfor short-lived, temporary spikes. Therefore, the best answer is to use anEC2 Instance Savings Planfor the baseline andOn-Demand Instancesfor the seasonal increase.

The correct design is to useRoute 53 failover records, with theprimary record pointing to the ALB and associated with a health check, and thesecondary record pointing to the static website. Route 53 failover routing is designed to return the primary resource when it is healthy and automatically return the secondary resource when the primary becomes unhealthy. The health check is attached to the primary failover record so Route 53 knows when to fail over. You do not need a Lambda function to switch records manually, because Route 53 provides built-in DNS failover. The secondary record does not need its own health check for this pattern. That is whyC and Eare the right combination. (AWS Documentation)

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AWS Lambda SnapStart is designed to improve the cold start performance of Java Lambda functions by initializing the function, taking a snapshot of the execution environment, and then reusing that snapshot for subsequent invocations. However, some code (such as code that generates unique IDs or session-specific data) should run during each invocation, not during the snapshot process. By using a pre-snapshot hook and moving the unique ID generation into the handler, you ensure that non-deterministic or per-invocation code is executed correctly, while the rest of the initialization benefits from SnapStart. This delivers the lowest latency and cost, as you do not need to pay for provisioned concurrency.

AWS Documentation Extract:

" Lambda SnapStart is ideal for Java functions with long cold starts due to heavy initialization. Move non-deterministic code such as unique ID generation to the handler, and use pre-snapshot hooks to customize what gets snapshotted. SnapStart works only for published versions, not $LATEST. "

(Source: AWS Lambda documentation, Using SnapStart for Java Functions)

Other options:

A: SnapStart is not supported for the $LATEST version; must be a published version.

B & C: Provisioned concurrency removes cold starts but is more expensive than SnapStart for most workloads.

C: You must use SnapStart on published versions, but provisioned concurrency is not required for SnapStart and adds cost.

EC2 Image Builder is the AWS-managed service specifically designed to automate the creation, patching, hardening, and testing of AMIs.

For this scenario, best practice is to:

Use EC2 Image Builder pipelines to generate new golden AMIs whenever features are deployed or on a schedule.

Include build components such as update-linux to automatically apply OS security patches and updates during image creation.

Deploy the new AMIs through existing Auto Scaling groups, ensuring that every newly launched instance is already patched and compliant.

This approach:

Prevents OS vulnerabilities from being introduced at deployment time.

Scales across dozens of applications because AMI pipelines are reusable and automated.

Minimizes manual effort and reduces drift between instances.

Amazon Inspector (Option A) identifies vulnerabilities but does not itself patch AMIs.

AWS Backup (Option B) is for data protection, not vulnerability management.

Patch Manager (Option C) patches running instances, but the requirement is to ensure vulnerabilities are not introduced with new AMIs; golden image pipelines with EC2 Image Builder are the recommended solution.