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| Section | Weight | Objectives |
|---|---|---|
| Design Resilient Architectures | 26% | - Design scalable and loosely coupled architectures
|
| Design Cost-Optimized Architectures | 20% | - Design cost-optimized database solutions
|
| Design High-Performing Architectures | 24% | - Design high-performing and elastic compute solutions
|
| Design Secure Architectures | 30% | - Determine appropriate data security controls
|
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질문 # 885
A global company hosts its web application on Amazon EC2 instances behind an Application Load Balancer ALB. The web application has static data and dynamic data. The company stores its static data in an Amazon S3 bucket. The company wants to improve performance and reduce latency for the static data and dynamic data. The company is using its own domain name registered with Amazon Route 53.
What should a solutions architect do to meet these requirements?
정답：C
설명：
Amazon CloudFront can usemultiple originsin one distribution, including anAmazon S3 bucketfor static content and anApplication Load Balancerfor dynamic content. That lets the company reduce latency globally for both content types while keeping a single front door for users. AWS documentation specifically notes that CloudFront supports both S3 origins and load balancer origins, and a single distribution can include multiple origins. Route 53 can then alias the company's domain to the CloudFront distribution. The Global Accelerator options are unnecessary here because CloudFront already addresses the performance need for both static and dynamic web delivery in this architecture.
질문 # 886
A company runs an on-premises application on a Kubernetes cluster. The company recently added millions of new customers. The company's existing on-premises infrastructure is unable to handle the large number of new customers. The company needs to migrate the on-premises application to the AWS Cloud.
The company will migrate to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. The company does not want to manage the underlying compute infrastructure for the new architecture on AWS.
Which solution will meet these requirements with the LEAST operational overhead?
정답：D
설명：
AWS Fargate is a serverless compute engine for containers that works with Amazon EKS. With Fargate, you do not need to provision or manage EC2 instances or clusters. You simply define and deploy your pods, and Fargate automatically launches the required compute resources. This results in the lowest operational overhead because AWS manages the infrastructure. Fargate profiles allow you to specify which pods run on Fargate.
AWS Documentation Extract:
"AWS Fargate is a serverless, pay-as-you-go compute engine that lets you focus on building applications without managing servers. With Amazon EKS and Fargate, you only need to define your application's pods; Fargate provisions and manages the required compute resources for you." (Source: Amazon EKS documentation, AWS Fargate integration) Other options:
A: Self-managed nodes require you to manage EC2 instances.
B: Managed node groups reduce some overhead, but you are still responsible for patching and managing the EC2 instances.
D: Managed node groups with Karpenter automate scaling but do not remove the need to manage underlying instances.
Reference: AWS Certified Solutions Architect - Official Study Guide, EKS and Fargate Section.
질문 # 887
A company needs to retain application logs files for a critical application for 10 years. The application team regularly accesses logs from the past month for troubleshooting, but logs older than 1 month are rarely accessed. The application generates more than 10 TB of logs per month.
Which storage option meets these requirements MOST cost-effectively?
정답：C
설명：
Explanation
You need S3 to be able to archive the logs after one month. Cannot do that with CloudWatch Logs.
질문 # 888
A company has an OLTP (Online Transactional Processing) application that is hosted in an Amazon ECS cluster using the Fargate launch type. It has an Amazon RDS database that stores data of its production website. The Data Analytics team needs to run queries against the database to track and audit all user transactions. These query operations against the production database must not impact application performance in any way.
Which of the following is the MOST suitable and cost-effective solution that you should implement?
정답：A
설명：
Amazon RDS Read Replicas provide enhanced performance and durability for database (DB) instances.
This feature makes it easy to elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads.
You can create one or more replicas of a given source DB Instance and serve high-volume application read traffic from multiple copies of your data, thereby increasing aggregate read throughput. Read replicas can also be promoted when needed to become standalone DB instances. Read replicas are available in Amazon RDS for MySQL, MariaDB, Oracle and PostgreSQL, as well as Amazon Aurora.
You can reduce the load on your source DB instance by routing read queries from your applications to the read replica. These replicas allow you to elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads.
Because read replicas can be promoted to master status, they are useful as part of a sharding implementation. To shard your database, add a read replica and promote it to master status, then, from each of the resulting DB Instances, delete the data that belongs to the other shard.
Hence, the correct answer is: Set up a new Amazon RDS Read Replica of the production database.
Direct the Data Analytics team to query the production data from the replica.
The option that says: Set up a new Amazon Redshift database cluster. Migrate the product database into Redshift and allow the Data Analytics team to fetch data from it is incorrect because Redshift is primarily used for OLAP (Online Analytical Processing) applications and not for OLTP.
The option that says: Set up a Multi-AZ deployments configuration of your production database in RDS.
Direct the Data Analytics team to query the production data from the standby instance is incorrect because you can't directly connect to the standby instance. This is only used in the event of a database failover when your primary instance encountered an outage.
The option that says: Upgrade the instance type of the RDS database to a large instance is incorrect because this entails a significant amount of cost. Moreover, the production database could still be affected by the queries done by the Data Analytics team. A better solution for this scenario is to use a Read Replica instead.
References:
https://aws.amazon.com/caching/database-caching/
https://aws.amazon.com/rds/details/read-replicas/
https://aws.amazon.com/elasticache/
Check out this Amazon RDS Cheat Sheet:
https://tutorialsdojo.com/amazon-relational-database-service-amazon-rds/
질문 # 889
A solutions architect needs to optimize storage costs. The solutions architect must identify any Amazon S3 buckets that are no longer being accessed or are rarely accessed.
Which solution will accomplish this goal with the LEAST operational overhead?
정답：D
설명：
Amazon S3 Storage Lens with advanced activity metrics is the most operationally efficient answer because AWS documentation explicitly says you can use S3 Storage Lens advanced metrics to identify "cold" buckets, meaning buckets whose objects are no longer accessed or are accessed only rarely. That is exactly the requirement in the question. This avoids building a custom analytics workflow on top of CloudTrail or CloudWatch metrics. The standard S3 console does not provide the same purpose-built fleet-level analysis for cold-bucket identification. Athena and CloudTrail can be used for access analysis, but they require more setup, data handling, and query maintenance. S3 Storage Lens is the native managed feature for this storage- optimization scenario. (AWS Documentation)
질문 # 890
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