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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Design solutions for organizational complexity | 26% | |
| Topic 2: Accelerate workload migration and modernization | 20% | |
| Topic 3: Design for new solutions | 29% | |
| Topic 4: Continuous improvement for existing solutions | 25% |
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NEW QUESTION # 659
A live-events company is designing a scaling solution for its ticket application on AWS. The application has high peaks of utilization during sale events. Each sale event is a one-time event that is scheduled. The application runs on Amazon EC2 instances that are in an Auto Scaling group.
The application uses PostgreSQL for the database layer.
The company needs a scaling solution to maximize availability during the sale events.
Which solution will meet these requirements?
Answer: D
Explanation:
The correct answer is D)
D) This solution meets the requirements because it uses a scheduled scaling policy for the EC2 instances, which can adjust the capacity according to the known sale events. It also uses Amazon Aurora PostgreSQL Multi-AZ DB cluster, which provides high availability and durability for the database. It uses Amazon EventBridge rules and AWS Lambda functions to create a larger Aurora Replica before a sale event and fail over to it, which can improve the performance and handle the increased traffic. It also uses another EventBridge rule and Lambda function to scale down the Aurora Replica after the sale event, which can save costs123 A) This solution is incorrect because it uses predictive scaling policy for the EC2 instances, which is not suitable for one-time events that are scheduled. Predictive scaling is based on historical data and machine learning, which may not accurately forecast the demand for sale events. It also uses Amazon Aurora PostgreSQL Serverless v2 Multi-AZ DB instance, which does not support read replicas. The use of AWS Step Functions state machine and Lambda functions to pre-warm the database is unnecessary and adds complexity45 B) This solution is incorrect because it uses Amazon RDS for PostgreSQL Multi-AZ DB instance with automatically scaling read replicas, which may not provide enough performance improvement for the sale events. The use of EventBridge rules and Lambda functions to create a larger read replica and fail over to it is risky and may cause downtime or data loss. The use of another EventBridge rule and Lambda function to scale down the read replica is also risky and may cause inconsistency or data loss67 C) This solution is incorrect because it uses predictive scaling policy for the EC2 instances, which is not suitable for one-time events that are scheduled. Predictive scaling is based on historical data and machine learning, which may not accurately forecast the demand for sale events. The use of AWS Step Functions state machine and Lambda functions to pre-warm the database is unnecessary and adds complexity45 Reference:
1: Scheduled scaling for Amazon EC2 Auto Scaling 2: Amazon Aurora PostgreSQL features 3: Amazon EventBridge rules 4: Predictive scaling for Amazon EC2 Auto Scaling 5: Amazon Aurora Serverless v2 6: Multi-AZ DB instance deployments - Amazon Relational Database Service 7: Working with PostgreSQL read replicas - Amazon Relational Database Service
NEW QUESTION # 660
A company is hosting a single-page web application in the AWS Cloud. The company is using Amazon CloudFront to reach its goal audience. The CloudFront distribution has an Amazon S3 bucket that is configured as its origin. The static files for the web application are stored in this S3 bucket. The company has used a simple routing policy to configure an Amazon Route S3 A record. The record points to the CloudFront distribution. The company wants to use a canary deployment release strategy for new versions of the application.
What should a solutions architect recommend to meet these requirements?
Answer: B
NEW QUESTION # 661
A company is deploying a new web-based application and needs a storage solution for the Linux application servers. The company wants to create a single location for updates to application data for all instances. The active dataset will be up to 100 GB in size. A solutions architect has determined that peak operations will occur for 3 hours daily and will require a total of 225 MiBps of read throughput.
The solutions architect must design a Multi-AZ solution that makes a copy of the data available in another AWS Region for disaster recovery (DR). The DR copy has an RPO of less than 1 hour.
Which solution will meet these requirements?
Answer: C
Explanation:
Explanation
The company should deploy a new Amazon Elastic File System (Amazon EFS) Multi-AZ file system. The company should configure the file system for 75 MiBps of provisioned throughput. The company should implement replication to a file system in the DR Region. This solution will meet the requirements because Amazon EFS is a serverless, fully elastic file storage service that lets you share file data without provisioning or managing storage capacity and performance. Amazon EFS is built to scale on demand to petabytes without disrupting applications, growing and shrinking automatically as you add and remove files1. By deploying a new Amazon EFS Multi-AZ file system, the company can create a single location for updates to application data for all instances. A Multi-AZ file system replicates data across multiple Availability Zones (AZs) within a Region, providing high availability and durability2. By configuring the file system for 75 MiBps of provisioned throughput, the company can ensure that it meets the peak operations requirement of 225 MiBps of read throughput. Provisioned throughput is a feature that enables you to specify a level of throughput that the file system can drive independent of the file system's size or burst credit balance3. By implementing replication to a file system in the DR Region, the company can make a copy of the data available in another AWS Region for disaster recovery. Replication is a feature that enables you to replicate data from one EFS file system to another EFS file system across AWS Regions. The replication process has an RPO of less than 1 hour.
The other options are not correct because:
* Deploying a new Amazon FSx for Lustre file system would not provide a single location for updates to application data for all instances. Amazon FSx for Lustre is a fully managed service that provides cost-effective, high-performance storage for compute workloads. However, it does not support concurrent write access from multiple instances. Using AWS Backup to back up the file system to the DR Region would not provide real-time replication of data. AWS Backup is a service that enables you to centralize and automate data protection across AWS services. However, it does not support continuous data replication or cross-Region disaster recovery.
* Deploying a General Purpose SSD (gp3) Amazon Elastic Block Store (Amazon EBS) volume with 225 MiBps of throughput would not provide a single location for updates to application data for all instances. Amazon EBS is a service that provides persistent block storage volumes for use with Amazon EC2 instances. However, it does not support concurrent access from multiple instances, unless Multi-Attach is enabled. Enabling Multi-Attach for the EBS volume would not provide Multi-AZ resilience or cross-Region replication. Multi-Attach is a feature that enables you to attach an EBS volume to multiple EC2 instances within the same Availability Zone. Using AWS Elastic Disaster Recovery to replicate the EBS volume to the DR Region would not provide real-time replication of data.
* AWS Elastic Disaster Recovery (AWS DRS) is a service that enables you to orchestrate and automate disaster recovery workflows across AWS Regions. However, it does not support continuous data replication or sub-hour RPOs.
* Deploying an Amazon FSx for OpenZFS file system in both the production Region and the DR Region would not be as simple or cost-effective as using Amazon EFS. Amazon FSx for OpenZFS is a fully managed service that provides high-performance storage with strong data consistency and advanced data management features for Linux workloads. However, it requires more configuration and management than Amazon EFS, which is serverless and fully elastic. Creating an AWS DataSync scheduled task to replicate the data from the production file system to the DR file system every 10 minutes would not provide real-time replication of data. AWS DataSync is a service that enables you to transfer data between on-premises storage and AWS services, or between AWS services. However, it does not support continuous data replication or sub-minute RPOs.
References:
* https://aws.amazon.com/efs/
* https://docs.aws.amazon.com/efs/latest/ug/how-it-works.html#how-it-works-azs
* https://docs.aws.amazon.com/efs/latest/ug/performance.html#provisioned-throughput
* https://docs.aws.amazon.com/efs/latest/ug/replication.html
* https://aws.amazon.com/fsx/lustre/
* https://aws.amazon.com/backup/
* https://aws.amazon.com/ebs/
* https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-volumes-multi.html
NEW QUESTION # 662
A company's lease of a colocated storage facility will expire in 90 days. The company wants to move to AWS to avoid signing a contract extension. The company's environment consists of 200 virtual machines and a NAS with 40 TB of data. Most of the data is archival, yet instant access is required when data is requested.
Leadership wants to ensure minimal downtime during the migration. Each virtual machine has a number of customized configurations. The company's existing 1 Gbps network connection is mostly idle, especially after business hours.
Which combination of steps should the company take to migrate to AWS while minimizing downtime and operational impact? (Choose two.)
Answer: B,C
Explanation:
With 1Gbps of inactive speed means about 128MBs which will take about 4 days lets say only off hours so it will take about 8 days in total. Better to use Storage File GW no need to order and send a snowball for this.
NEW QUESTION # 663
A company has developed a mobile game. The backend for the game runs on several virtual machines located in an on-premises data center. The business logic is exposed using a REST API with multiple functions. Player session data is stored in central file storage. Backend services use different API keys for throttling and to distinguish between live and test traffic.
The load on the game backend varies throughout the day. During peak hours, the server capacity is not sufficient. There are also latency issues when fetching player session data. Management has asked a solutions architect to present a cloud architecture that can handle the game's varying load and provide low-latency data access. The API model should not be changed.
Which solution meets these requirements?
Answer: D
NEW QUESTION # 664
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