A company's near-real-time streaming application is running on AWS. As the data is ingested, a job runs on the data and takes 30 minutes to complete. The workload frequently experiences high latency due to large amounts of incoming data.
A solutions architect needs to design a scalable and serverless solution to enhance performance.
Which combination of steps should the solutions architect take? (Choose two.)
A. Use Amazon Kinesis Data Firehose to ingest the data. B. Use AWS Lambda with AWS Step Functions to process the data. C. Use AWS Database Migration Service (AWS DMS) to ingest the data. D. Use Amazon EC2 instances in an Auto Scaling group to process the data. E. Use AWS Fargate with Amazon Elastic Container Service (Amazon ECS) to process the data.
A. Use Amazon Kinesis Data Firehose to ingest the data. E. Use AWS Fargate with Amazon Elastic Container Service (Amazon ECS) to process the data.
Question 452:
A company has a batch processing application that runs every day. The process typically takes an average 3 hours to complete. The application can handle interruptions and can resume the process after a restart.
Currently, the company runs the application on Amazon EC2 On-Demand Instances. The company wants to optimize costs while maintaining the same performance level.
Which solution will meet these requirements MOST cost-effectively?
A. Purchase a 1-year EC2 Instance Savings Plan for the appropriate instance family and size to meet the requirements of the application. B. Use EC2 On-Demand Capacity Reservations based on the appropriate instance family and size to meet the requirements of the application. Run the EC2 instances in an Auto Scaling group. C. Determine the appropriate instance family and size to meet the requirements of the application. Convert the application to run on AWS Batch with EC2 On-Demand Instances. Purchase a 1-year Compute Savings Plan. D. Determine the appropriate instance family and size to meet the requirements of the application. Convert the application to run on AWS Batch with EC2 Spot Instances.
D. Determine the appropriate instance family and size to meet the requirements of the application. Convert the application to run on AWS Batch with EC2 Spot Instances.
Explanation
Since the workload is interruptible and can resume after restarts, Amazon EC2 Spot Instances are the most cost-effective option, offering savings of up to 90% compared to On-Demand. Running the batch workload on AWS Batch with Spot Instances allows automatic job queue management, interruption handling, and scheduling.
Option A and C reduce cost but still rely on reserved or committed pricing for On-Demand capacity.
Option B (Capacity Reservations) increases cost instead of reducing it. Therefore, the most cost-optimized solution is D -- AWS Batch with EC2 Spot Instances.
References:
AWS Batch User Guide -- Using Spot Instances with AWS Batch?AWS Well-Architected Framework -- Cost Optimization Pillar
Question 453:
An ecommerce company is redesigning a product catalog system to handle millions of products and provide fast access to product information. The system needs to store structured product data such as product name, price, description, and category. The system also needs to store unstructured data such as high-resolution product videos and user manuals. The architecture must be highly available and must be able to handle sudden spikes in traffic during large-scale sales events.
Which solution will meet these requirements?
A. Use an Amazon RDS Multi-AZ deployment to store product information. Store product videos and user manuals in Amazon S3. B. Use Amazon DynamoDB to store product information. Store product videos and user manuals in Amazon S3. C. Store all product information, including product videos and user manuals, in Amazon DynamoDB. D. Deploy an Amazon DocumentDB (with MongoDB compatibility) cluster to store all product information, product videos, and user manuals.
B. Use Amazon DynamoDB to store product information. Store product videos and user manuals in Amazon S3.
Explanation
Amazon DynamoDB provides single-digit millisecond performance at any scale and is fully managed to handle millions of catalog records. It is ideal for structured catalog data such as product metadata and scales seamlessly during high-traffic events like sales. Amazon S3 is optimized for storing unstructured large objects such as videos and manuals, with virtually unlimited scalability and high durability.
Option A (RDS) would not handle massive scale or traffic spikes as efficiently.
Option C overloads DynamoDB by forcing it to store large binary data, which is not its purpose.
Option D (DocumentDB) is suitable for JSON-like documents but not optimal for storing large media files and would add operational complexity.
Therefore, option B represents the best separation of structured and unstructured data storage.
References:
DynamoDB Developer Guide -- Millisecond performance at scale?Amazon S3 User Guide -- Storage for unstructured data?AWS Well-Architected Framework -- Performance Efficiency Pillar
Question 454:
A company wants a flexible compute solution that includes Amazon EC2 instances and AWS Fargate. The company does not want to commit to multi-year contracts.
Which purchasing option will meet these requirements MOST cost-effectively?
A. Purchase a 1-year EC2 Instance Savings Plan with the All Upfront option. B. Purchase a 1-year Compute Savings Plan with the No Upfront option. C. Purchase a 1-year Compute Savings Plan with the Partial Upfront option. D. Purchase a 1-year Compute Savings Plan with the All Upfront option.
B. Purchase a 1-year Compute Savings Plan with the No Upfront option.
Explanation
To optimize costs for both Amazon EC2 and AWS Fargate, the best option is a Compute Savings Plan because it offers flexibility across instance families, Regions, and compute options including EC2, AWS Fargate, and AWS Lambda.
Unlike EC2 Instance Savings Plans, which apply only to specific instance families, Compute Savings Plans apply across multiple services.
Since the company does not want to commit to multi-year contracts or large upfront payments, the 1-year No Upfront Compute Savings Plan provides the greatest flexibility with no upfront capital commitment, while still offering cost savings over On-Demand pricing.
This option also aligns with cost-optimization best practices by allowing for scalability and service mix flexibility.
References:
AWS Compute Savings Plans
AWS Pricing Models
Question 455:
A company has a production Amazon RDS for MySQL database. The company needs to create a new application that will read frequently changing data from the database with minimal impact on the database's overall performance. The application will rarely perform the same query more than once.
What should a solutions architect do to meet these requirements?
A. Set up an Amazon ElastiCache cluster. Query the results in the cluster. B. Set up an Application Load Balancer (ALB). Query the results in the ALB. C. Set up a read replica for the database. Query the read replica. D. Set up querying of database snapshots. Query the database snapshots.
C. Set up a read replica for the database. Query the read replica.
Explanation
Amazon RDS read replicas provide a way to offload read traffic from the primary database, allowing read-intensive applications to query the replica without impacting the performance of the production (write) database. This is especially effective for workloads that involve frequently changing data but do not benefit from caching, since queries are rarely repeated.
Reference Extract from AWS Documentation /
Study Guide:
" Read replicas allow you to elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads. "
A company runs a self-managed Microsoft SQL Server on Amazon EC2 instances and Amazon Elastic Block Store (Amazon EBS). Daily snapshots are taken of the EBS volumes. Recently, all the company's EBS snapshots were accidentally deleted while running a snapshot cleaning script that deletes all expired EBS snapshots. A solutions architect needs to update the architecture to prevent data loss without retaining EBS snapshots indefinitely.
Which solution will meet these requirements with the LEAST development effort?
A. Change the IAM policy of the user to deny EBS snapshot deletion. B. Copy the EBS snapshots to another AWS Region after completing the snapshots daily. C. Create a 7-day EBS snapshot retention rule in Recycle Bin and apply the rule for all snapshots. D. Copy EBS snapshots to Amazon S3 Standard-Infrequent Access (S3 Standard-IA).
C. Create a 7-day EBS snapshot retention rule in Recycle Bin and apply the rule for all snapshots.
Question 457:
A company wants to move its application to a serverless solution. The serverless solution needs to analyze existing data and new data by using SQL. The company stores the data in an Amazon S3 bucket. The data must be encrypted at rest and replicated to a different AWS Region.
Which solution will meet these requirements with the LEAST operational overhead?
A. Create a new S3 bucket that uses server-side encryption with AWS KMS multi-Region keys (SSE-KMS). Configure Cross-Region Replication (CRR). Load the data into the new S3 bucket. Use Amazon Athena to query the data. B. Create a new S3 bucket that uses server-side encryption with Amazon S3 managed keys (SSE-S3). Configure Cross-Region Replication (CRR). Load the data into the new S3 bucket. Use Amazon RDS to query the data. C. Configure Cross-Region Replication (CRR) on the existing S3 bucket. Use server-side encryption with Amazon S3 managed keys (SSE-S3). Use Amazon Athena to query the data. D. Configure S3 Cross-Region Replication (CRR) on the existing S3 bucket. Use server-side encryption with AWS KMS multi-Region keys (SSE-KMS). Use Amazon RDS to query the data.
C. Configure Cross-Region Replication (CRR) on the existing S3 bucket. Use server-side encryption with Amazon S3 managed keys (SSE-S3). Use Amazon Athena to query the data.
Question 458:
A company's application is receiving data from multiple data sources. The size of the data varies and is expected to increase over time. The current maximum size is 700 KB. The data volume and data size continue to grow as more data sources are added. The company decides to use Amazon DynamoDB as the primary database for the application. A solutions architect needs to identify a solution that handles the large data sizes.
Which solution will meet these requirements in the MOST operationally efficient way?
A. Create an AWS Lambda function to filter the data that exceeds DynamoDB item size limits. Store the larger data in an Amazon DocumentDB (with MongoDB compatibility) database. B. Store the large data as objects in an Amazon S3 bucket. In a DynamoDB table, create an item that has an attribute that points to the S3 URL of the data. C. Split all incoming large data into a collection of items that have the same partition key. Write the data to a DynamoDB table in a single operation by using the BatchWriteItem API operation. D. Create an AWS Lambda function that uses gzip compression to compress the large objects as they are written to a DynamoDB table.
B. Store the large data as objects in an Amazon S3 bucket. In a DynamoDB table, create an item that has an attribute that points to the S3 URL of the data.
Question 459:
A company deployed an application in two AWS Regions. If the application becomes unavailable in one Region, the application must fail over to the second Region. The failover process must avoid stale DNS client caches. The company wants to use one endpoint to access both copies of the application.
Which solution will meet these requirements?
A. Use an Amazon CloudFront distribution that has multiple origins. Correlate each origin with the application in each Region. B. Use an Amazon Route 53 weighted routing policy that uses equal weights to route client requests to the second Region if the application becomes unavailable in the original Region. C. Use AWS Global Accelerator, and assign a static anycast IP address to the application endpoint. D. Use an Amazon Route 53 IP-based routing policy to route requests to the second Region if the application becomes unavailable in the original Region.
C. Use AWS Global Accelerator, and assign a static anycast IP address to the application endpoint.
Explanation
AWS Global Accelerator provides static anycast IP addresses that are announced from AWS edge locations. Traffic sent to these IPs is routed over the AWS global network to the nearest healthy endpoint (for example, an ALB or NLB) in any Region. Because clients connect to static IPs instead of DNS names that change, failover does not depend on DNS TTLs or client cache expiry, which avoids stale DNS entries.
You can register endpoints in multiple Regions and let Global Accelerator automatically fail over when health checks fail, all behind a single global endpoint.
CloudFront (Option A) is primarily for HTTP/HTTPS content caching and still uses DNS; it is not intended as a generic multi-Region failover solution for arbitrary applications.
Route 53 (Options B and D) relies on DNS; clients can cache DNS responses and may keep sending traffic to an unhealthy Region until TTLs expire, which does not meet the "avoid stale DNS client caches" requirement.
Question 460:
A research company uses on-premises devices to generate data for analysis. The company wants to use the AWS Cloud to analyze the data. The devices generate .csv files and support writing the data to an SMB file share. Company analysts must be able to use SQL commands to query the data. The analysts will run queries periodically throughout the day.
Which combination of steps will meet these requirements MOST cost-effectively? (Choose three.)
A. Deploy an AWS Storage Gateway on premises in Amazon S3 File Gateway mode. B. Deploy an AWS Storage Gateway on premises in Amazon FSx File Gateway made. C. Set up an AWS Glue crawler to create a table based on the data that is in Amazon S3. D. Set up an Amazon EMR cluster with EMR File System (EMRFS) to query the data that is in Amazon S3. Provide access to analysts. E. Set up an Amazon Redshift cluster to query the data that is in Amazon S3. Provide access to analysts. F. Setup Amazon Athena to query the data that is in Amazon S3. Provide access to analysts.
A. Deploy an AWS Storage Gateway on premises in Amazon S3 File Gateway mode. C. Set up an AWS Glue crawler to create a table based on the data that is in Amazon S3. F. Setup Amazon Athena to query the data that is in Amazon S3. Provide access to analysts.
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