A company wants to move its application to a serverless solution. The serverless solution needs to analyze existing and new data by using SL. The company stores the data in an Amazon S3 bucket. The data requires encryption and must be replicated to a different AWS Region.
Which solution will meet these requirements with the LEAST operational overhead?
A. Create a new S3 bucket. Load the data into the new S3 bucket. Use S3 Cross-Region Replication (CRR) to replicate encrypted objects to an S3 bucket in another Region. Use server-side encryption with AWS KMS multi-Region kays (SSE-KMS). Use Amazon Athena to query the data. B. Create a new S3 bucket. Load the data into the new S3 bucket. Use S3 Cross-Region Replication (CRR) to replicate encrypted objects to an S3 bucket in another Region. Use server-side encryption with AWS KMS multi-Region keys (SSE-KMS). Use Amazon RDS to query the data. C. Load the data into the existing S3 bucket. Use S3 Cross-Region Replication (CRR) to replicate encrypted objects to an S3 bucket in another Region. Use server-side encryption with Amazon S3 managed encryption keys (SSE-S3). Use Amazon Athena to query the data. D. Load the data into the existing S3 bucket. Use S3 Cross-Region Replication (CRR) to replicate encrypted objects to an S3 bucket in another Region. Use server-side encryption with Amazon S3 managed encryption keys (SSE- S3). Use Amazon RDS to query the data.
C. Load the data into the existing S3 bucket. Use S3 Cross-Region Replication (CRR) to replicate encrypted objects to an S3 bucket in another Region. Use server-side encryption with Amazon S3 managed encryption keys (SSE-S3). Use Amazon Athena to query the data.
Question 1302:
An ecommerce company is running a multi-tier application on AWS. The front-end and backend tiers both run on Amazon EC2, and the database runs on Amazon RDS for MySQL. The backend tier communicates with the RDS instance.
There are frequent calls to return identical datasets from the database that are causing performance slowdowns.
Which action should be taken to improve the performance of the backend?
A. Implement Amazon SNS to store the database calls. B. Implement Amazon ElastiCache to cache the large datasets. C. Implement an RDS for MySQL read replica to cache database calls. D. Implement Amazon Kinesis Data Firehose to stream the calls to the database.
B. Implement Amazon ElastiCache to cache the large datasets.
Question 1303:
An ecommerce company wants a disaster recovery solution for its Amazon RDS DB instances that run Microsoft SQL Server Enterprise Edition. The company's current recovery point objective (RPO) and recovery time objective (RTO) are 24 hours.
Which solution will meet these requirements MOST cost-effectively?
A. Create a cross-Region read replica and promote the read replica to the primary instance. B. Use AWS Database Migration Service (AWS DMS) to create RDS cross-Region replication. C. Use cross-Region replication every 24 hours to copy native backups to an Amazon S3 bucket. D. Copy automatic snapshots to another Region every 24 hours.
D. Copy automatic snapshots to another Region every 24 hours.
Question 1304:
A company has deployed a database in Amazon RDS for MySQL. Due to increased transactions, the database support team is reporting slow reads against the DB instance and recommends adding a read replica.
Which combination of actions should a solutions architect take before implementing this change? (Choose two.)
A. Enable binlog replication on the RDS primary node. B. Choose a failover priority for the source DB instance. C. Allow long-running transactions to complete on the source DB instance. D. Create a global table and specify the AWS Regions where the table will be available. E. Enable automatic backups on the source instance by setting the backup retention period to a value other than 0.
C. Allow long-running transactions to complete on the source DB instance. E. Enable automatic backups on the source instance by setting the backup retention period to a value other than 0.
Question 1305:
A company runs multiple workloads in separate AWS environments. The company wants to optimize its AWS costs but must maintain the same level of performance for the environments.
The company's production environment requires resources to be highly available. The other environments do not require highly available resources.
Each environment has the same set of networking components, including the following:
1 VPC
1 Application Load Balancer
4 subnets distributed across 2 Availability Zones (2 public subnets and 2 private subnets) 2 NAT gateways (1 in each public subnet) 1 internet gateway
Which solution will meet these requirements?
A. Do not change the production environment workload. For each non-production workload, remove one NAT gateway and update the route tables for private subnets to target the remaining NAT gateway for the destination 0.0.0.0/0. B. Reduce the number of Availability Zones that all workloads in all environments use. C. Replace every NAT gateway with a t4g.large NAT instance. Update the route tables for each private subnet to target the NAT instance that is in the same Availability Zone for the destination 0.0.0.0/0. D. In each environment, create one transit gateway and remove one NAT gateway. Configure routing on the transit gateway to forward traffic for the destination 0.0.0.0/0 to the remaining NAT gateway. Update private subnet route tables to target the transit gateway for the destination 0.0.0.0/0.
A. Do not change the production environment workload. For each non-production workload, remove one NAT gateway and update the route tables for private subnets to target the remaining NAT gateway for the destination 0.0.0.0/0.
Explanation
Maintaining two NAT gateways for production ensures high availability. Reducing to one NAT gateway in non-production environments lowers cost while maintaining necessary connectivity. This approach is recommended by AWS for cost optimization in non-critical environments.
References:
" For environments that do not require high availability, you can reduce costs by using a single NAT gateway and updating route tables accordingly. "
Source: AWS Certified Solutions Architect?Official Study Guide, Cost Optimization and NAT Gateway section.
Question 1306:
A company is developing a social media application that must scale rapidly and handle long-running, ordered processes that store large amounts of relational data. Components must scale independently and evolve without downtime.
Which combination of AWS services will meet these requirements?
A. Amazon ECS with Fargate, Amazon RDS, and Amazon SQS B. Amazon ECS with Fargate, Amazon RDS, and Amazon SNS C. AWS Lambda, Amazon DynamoDB Streams, and AWS Step Functions D. AWS Elastic Beanstalk, Amazon RDS, and Amazon SNS
A. Amazon ECS with Fargate, Amazon RDS, and Amazon SQS
Explanation
The application requires independent scaling, ordered asynchronous processing, and relational data storage. Option A provides a microservices-oriented, decoupled architecture using managed services.
Amazon ECS with AWS Fargate enables containerized workloads without server management and allows each component to scale independently. Amazon RDS supports relational data storage for user profiles and content. Amazon SQS ensures reliable, ordered message processing and decouples long-running background tasks, allowing services to evolve independently.
Option B uses SNS, which does not guarantee message ordering.
Option C uses DynamoDB, which does not meet the relational data requirement.
Option D offers less granular scaling and higher coupling.
Therefore, A best meets scalability, resilience, and modularity requirements.
Question 1307:
A gaming company is developing a game that requires significant compute resources to process game logic, player interactions, and real-time updates. The company needs a compute solution that can dynamically scale based on fluctuating player demand while maintaining high performance. The company must use a relational database that can run complex queries.
Which solution will meet these requirements?
A. Deploy Amazon EC2 instances to supply compute capacity. Configure Auto Scaling groups to achieve dynamic scaling based on player count. Use Amazon RDS for MySQL as the database. B. Refactor the game logic into small, stateless functions. Use AWS Lambda to process the game logic. Use Amazon DynamoDB as the database. C. Deploy an Amazon Elastic Container Service (Amazon ECS) cluster on AWS Fargate to supply compute capacity. Scale the ECS tasks based on player demand. Use Amazon Aurora Serverless v2 as the database. D. Use AWS ParallelCluster for high performance computing (HPC). Provision compute nodes that have GPU instances to process the game logic and player interactions. Use Amazon RDS for MySQL as the database.
C. Deploy an Amazon Elastic Container Service (Amazon ECS) cluster on AWS Fargate to supply compute capacity. Scale the ECS tasks based on player demand. Use Amazon Aurora Serverless v2 as the database.
Explanation
Amazon ECS with AWS Fargate provides serverless container compute that can scale tasks dynamically in response to demand. This matches the unpredictable scaling requirements of a gaming workload.
EC2 with Auto Scaling (A) works but requires significant management overhead.
Lambda with DynamoDB (B) is not suitable because the workload requires a relational database and long-running processes.
ParallelCluster with HPC (D) is designed for batch scientific workloads, not dynamic, interactive gaming.
Option C provides the correct balance of elasticity, performance, and managed services for both compute and relational database needs.
References:
Amazon ECS User Guide -- Scaling ECS tasks with Fargate?Amazon Aurora User Guide -- Aurora Serverless v2 for dynamic workloads
Question 1308:
A company runs an internal browser-based application. The application runs on Amazon EC2 instances behind an Application Load Balancer. The instances run in an Amazon EC2 Auto Scaling group across multiple Availability Zones. The Auto Scaling group scales up to 20 instances during work hours, but scales down to 2 instances overnight. Staff are complaining that the application is very slow when the day begins, although it runs well by mid-morning.
How should the scaling be changed to address the staff complaints and keep costs to a minimum?
A. Implement a scheduled action that sets the desired capacity to 20 shortly before the office opens. B. Implement a step scaling action triggered at a lower CPU threshold, and decrease the cooldown period. C. Implement a target tracking action triggered at a lower CPU threshold, and decrease the cooldown period. D. Implement a scheduled action that sets the minimum and maximum capacity to 20 shortly before the office opens.
C. Implement a target tracking action triggered at a lower CPU threshold, and decrease the cooldown period.
Question 1309:
A company wants to use automatic machine learning (ML) to create and visualize forecasts of complex scenarios and trends.
Which solution will meet these requirements with the LEAST management overhead?
A. Use an AWS Glue ML job to transform the data and create forecasts. Use Amazon QuickSight to visualize the data. B. Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts. C. Use a prebuilt ML AMI from the AWS Marketplace to create forecasts. Use Amazon QuickSight to visualize the data. D. Use Amazon SageMaker AI inference pipelines to create and update forecasts. Use Amazon QuickSight to visualize the combined data.
B. Use Amazon QuickSight to visualize the data. Use ML-powered forecasting in QuickSight to create forecasts.
Explanation
Amazon QuickSight includes built-in ML-powered forecasting capabilities, allowing you to create, visualize, and interact with time series forecasts directly within the BI dashboard, with no ML experience or infrastructure management required.
This is the lowest management overhead solution.
References:
AWS Certified Solutions Architect?Official Study Guide, QuickSight and ML Forecasting.
Question 1310:
A company needs to implement a new data retention policy for regulatory compliance. As part of this policy, sensitive documents that are stored in an Amazon S3 bucket must be protected from deletion or modification for a fixed period of time.
Which solution will meet these requirements?
A. Activate S3 Object Lock on the required objects and enable governance mode. B. Activate S3 Object Lock on the required objects and enable compliance mode. C. Enable versioning on the S3 bucket. Set a lifecycle policy to delete the objects after a specified period. D. Configure an S3 Lifecycle policy to transition objects to S3 Glacier Flexible Retrieval for the retention duration.
B. Activate S3 Object Lock on the required objects and enable compliance mode.
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