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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design High-Performing Architectures | 24% | - Compute and storage optimization
|
| Topic 2: Design Cost-Optimized Architectures | 20% | - Cost management tools
|
| Topic 3: Design Resilient Architectures | 26% | - Highly available architecture
|
| Topic 4: Design Secure Architectures | 30% | - Secure workloads and applications
|
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NEW QUESTION # 960
A company has a business-critical application that runs on Amazon EC2 instances. The application stores data in an Amazon DynamoDB table. The company must be able to revert the table to any point within the last 24 hours.
Which solution meets these requirements with the LEAST operational overhead?
Answer: A
Explanation:
Point-in-time recovery (PITR) for DynamoDB is a feature that enables you to restore your table data to any point in time during the last 35 days. PITR helps protect your table from accidental write or delete operations, such as a test script writing to a production table or a user issuing a wrong command. PITR is easy to use, fully managed, fast, and scalable. You can enable PITR with a single click in the DynamoDB console or with a simple API call. You can restore a table to a new table using the console, the AWS CLI, or the DynamoDB API. PITR does not consume any provisioned table capacity and has no impact on the performance or availability of your production applications. PITR meets the requirements of the company with the least operational overhead, as it does not require any manual backup creation, scheduling, or maintenance. It also provides per-second granularity for restoring the table to any point within the last 24 hours.
Reference:
Point-in-time recovery for DynamoDB - Amazon DynamoDB
Amazon DynamoDB point-in-time recovery (PITR)
Enable Point-in-Time Recovery (PITR) for Dynamodb global tables
Restoring a DynamoDB table to a point in time - Amazon DynamoDB
Point-in-time recovery: How it works - Amazon DynamoDB
NEW QUESTION # 961
A company needs to run its external website on Amazon EC2 instances and on-premises virtualized servers. The AWS environment has a 1 GB AWS Direct Connect connection to the data center. The application has IP addresses that will not change. The on-premises and AWS servers are able to restart themselves while maintaining the same IP address if a failure occurs.
Some website users have to add their vendors to an allow list, so the solution must have a fixed IP address. The company needs a solution with the lowest operational overhead to handle this split traffic. What should a solutions architect do to meet these requirements?
Answer: D
Explanation:
A Network Load Balancer (NLB) supports IP address-based targets, which allows the use of both EC2 and on-premises endpoints. It also supports a static IP address or Elastic IP, which meets the requirement for a fixed IP address needed by some users.
NLB offers high performance, low latency, and minimal operational overhead. Application Load Balancer only supports instance or Lambda targets, not IP addresses outside the VPC. Route 53 Resolver is for DNS, and API Gateway is for HTTP-based APIs, not web applications.
NEW QUESTION # 962
A financial services company plans to launch a new application on AWS to handle sensitive financial transactions. The company will deploy the application on Amazon EC2 instances. The company will use Amazon RDS for MySQL as the database. The company's security policies mandate that data must be encrypted at rest and in transit.
Which solution will meet these requirements with the LEAST operational overhead?
Answer: A
Explanation:
This solution provides encryption at rest and in transit with the least operational overhead while adhering to the company's security policies.
Encryption at Rest: Amazon RDS for MySQL can be configured to encrypt data at rest by using AWS Key Management Service (KMS) managed keys. This encryption is applied automatically to all data stored on disk, including backups, read replicas, and snapshots. This solution requires minimal operational overhead because AWS manages the encryption and key management process.
Encryption in Transit: AWS Certificate Manager (ACM) allows you to provision, manage, and deploy SSL/TLS certificates seamlessly. These certificates can be used to encrypt data in transit by configuring the MySQL instance to use SSL/TLS for connections. This setup ensures that data is encrypted between the application and the database, protecting it from interception during transmission.
Why Not Other Options?:
Option B (IPsec tunnels): While IPsec tunnels encrypt data in transit, they are more complex to manage and require additional configuration and maintenance, leading to higher operational overhead.
Option C (Third-party application-level encryption): Implementing application-level encryption adds complexity, requires code changes, and increases operational overhead.
Option D (VPN for encryption): A VPN solution for encrypting data in transit is unnecessary and adds additional complexity without providing any benefit over SSL/TLS, which is simpler to implement and manage.
AWS Reference:
Amazon RDS Encryption - Information on how to configure and use encryption for Amazon RDS.
AWS Certificate Manager (ACM) - Details on using ACM to manage SSL/TLS certificates for securing data in transit.
NEW QUESTION # 963
An ecommerce company hosts an API that handles sales requests. The company hosts the API frontend on Amazon EC2 instances that run behind an Application Load Balancer (ALB). The company hosts the API backend on EC2 instances that perform the transactions. The backend tiers are loosely coupled by an Amazon Simple Queue Service (Amazon SQS) queue. The company anticipates a significant increase in request volume during a new product launch event.
The company wants to ensure that the API can handle increased loads successfully. Which solution will meet these requirements?
Answer: B
Explanation:
To handle increased loads effectively, it's essential to implement Auto Scaling for both frontend and backend tiers:
Frontend Auto Scaling Group: Scaling based on incoming network traffic ensures that the application can handle increased user requests.
Backend Auto Scaling Group: Scaling based on the Amazon SQS queue backlog ensures that the backend can process messages as they arrive, preventing delays.
This approach allows each tier to scale independently based on its specific load, ensuring optimal resource utilization and performance.
NEW QUESTION # 964
A company has an event-driven application that invokes AWS Lambda functions up to 800 times each minute with varying runtimes. The Lambda functions access data that is stored in an Amazon Aurora MySQL OB cluster. The company is noticing connection timeouts as user activity increases The database shows no signs of being overloaded. CPU. memory, and disk access metrics are all low.
Which solution will resolve this issue with the LEAST operational overhead?
Answer: D
Explanation:
1. database shows no signs of being overloaded. CPU, memory, and disk access metrics are all low==>A and C out. We cannot only add nodes instance or add read replica, because database workload is totally fine, very low. 2. "least operational overhead"==>B out, because b need to configure lambda. 3. ROS proxy: Shares infrequently used connections; High availability with failover; Drives increased efficiency==>proxy can leverage failover to redirect traffic from timeout rds instance to healthy rds instance. So D is right.
NEW QUESTION # 965
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