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Amazon SAA-C03 Certification Exam is a popular certification exam for IT professionals who want to validate their skills in designing and deploying scalable, highly available, and fault-tolerant systems on Amazon Web Services (AWS) cloud platform. AWS Certified Solutions Architect - Associate certification is designed for those who have experience in AWS-based applications and have the ability to identify and define requirements for AWS-based applications, recommend AWS architectures and services, and deploy applications on AWS.
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NEW QUESTION # 179
A company runs a highly available web application on Amazon EC2 instances behind an Application Load Balancer The company uses Amazon CloudWatch metrics As the traffic to the web application Increases, some EC2 instances become overloaded with many outstanding requests The CloudWatch metrics show that the number of requests processed and the time to receive the responses from some EC2 instances are both higher compared to other EC2 instances The company does not want new requests to be forwarded to the EC2 instances that are already overloaded.
Which solution will meet these requirements?
Answer: D
Explanation:
The least outstanding requests (LOR) algorithm is a load balancing algorithm that distributes incoming requests to the target with the fewest outstanding requests. This helps to avoid overloading any single target and improves the overall performance and availability of the web application. The LOR algorithm can use the RequestCount and TargetResponseTime CloudWatch metrics to determine the number of outstanding requests and the response time of each target. These metrics measure the number of requests processed by each target and the time elapsed after the request leaves the load balancer until a response from the target is received by the load balancer, respectively. By using these metrics, the LOR algorithm can route new requests to the targets that are less busy and more responsive, and avoid sending requests to the targets that are already overloaded or slow. This solution meets the requirements of the company.
References:
* Application Load Balancer now supports Least Outstanding Requests algorithm for load balancing requests
* Target groups for your Application Load Balancers
* Elastic Load Balancing - Application Load Balancers
NEW QUESTION # 180
A company hosts an ecommerce application that stores all data in a single Amazon RDS for MySQL DB instance that is fully managed by AWS. The company needs to mitigate the risk of a single point of failure.
Which solution will meet these requirements with the LEAST implementation effort?
Answer: B
Explanation:
Enabling Multi-AZ deployment for an Amazon RDS DB instance is the simplest and most effective way to improve database availability and eliminate a single point of failure. Multi-AZ deployments provide automatic failover to a standby instance in case of a failure of the primary instance. This approach is managed by AWS and only requires a modification to the existing instance, with minimal manual intervention or downtime, thus providing the least implementation effort.
Reference Extract from AWS Documentation / Study Guide:
"With Multi-AZ deployments, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). In case of a failure of the primary DB Instance, Amazon RDS automatically fails over to the standby so that database operations can resume quickly." Source: AWS Certified Solutions Architect - Official Study Guide, RDS High Availability section.
NEW QUESTION # 181
A company is creating a prototype of an ecommerce website on AWS. The website consists of an Application Load Balancer, an Auto Scaling group of Amazon EC2 instances for web servers, and an Amazon RDS for MySQL DB instance that runs with the Single-AZ configuration.
The website is slow to respond during searches of the product catalog. The product catalog is a group of tables in the MySQL database that the company does not ate frequently. A solutions architect has determined that the CPU utilization on the DB instance is high when product catalog searches occur.
What should the solutions architect recommend to improve the performance of the website dunng searches of the product catalog?
Answer: C
Explanation:
* Requirement Analysis: The product catalog search is causing high CPU utilization on the MySQL DB instance, slowing down the website.
* ElastiCache Overview: Amazon ElastiCache for Redis can be used to cache frequently accessed data, reducing load on the database.
* Lazy Loading: This caching strategy loads data into the cache only when it is requested, improving response times for repeated queries.
* Implementation:
* Set up an ElastiCache for Redis cluster.
* Modify the application to check the cache before querying the database.
* Use lazy loading to populate the cache on cache misses.
* Conclusion: This approach reduces database load and improves website performance during product catalog searches.
References
* Amazon ElastiCache: ElastiCache Documentation
* Caching Strategies: ElastiCache Caching Strategies
NEW QUESTION # 182
A company wants to build a logging solution for its multiple AWS accounts. The company currently stores the logs from all accounts in a centralized account. The company has created an Amazon S3 bucket in the centralized account to store the VPC flow logs and AWS CloudTrail logs. All logs must be highly available for 30 days for frequent analysis, retained tor an additional 60 days tor backup purposes, and deleted 90 days after creation.
Which solution will meet these requirements MOST cost-effectively?
Answer: B
Explanation:
Understanding the Requirement: The company needs logs to be highly available for 30 days for frequent analysis, retained for an additional 60 days for backup, and deleted after 90 days.
Analysis of Options:
Transition to S3 Standard after 30 days: Keeps logs in the same high-availability storage, not cost-effective.
Transition to S3 Standard-IA, then Glacier Flexible Retrieval after 90 days: Adds unnecessary cost and complexity since objects need to be accessible for only 30 days and then retained for 60 days.
Transition to Glacier Flexible Retrieval after 30 days: Not suitable for frequent access required in the first 30 days.
Transition to S3 One Zone-IA after 30 days, then Glacier Flexible Retrieval: Provides cost-effective storage for infrequently accessed logs after the initial 30-day period, then moves to the cheapest long-term storage before deletion.
Best Solution:
Transition to S3 One Zone-IA after 30 days, then Glacier Flexible Retrieval: This solution meets the requirements for high availability, cost-effective storage for backup, and scheduled deletion with the least cost.
Reference:
Amazon S3 Storage Classes
Managing your storage lifecycle
NEW QUESTION # 183
A telemarketing company is designing its customer call center functionality on AWS. The company needs a solution that provides multiples speaker recognition and generates transcript files The company wants to query the transcript files to analyze the business patterns The transcript files must be stored for 7 years for auditing piloses.
Which solution will meet these requirements?
Answer: A
Explanation:
Amazon Transcribe now supports speaker labeling for streaming transcription. Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for you to convert speech-to-text. In live audio transcription, each stream of audio may contain multiple speakers. Now you can conveniently turn on the ability to label speakers, thus helping to identify who is saying what in the output transcript. https://aws.
amazon.com/about-aws/whats-new/2020/08/amazon-transcribe-supports-speaker-labeling-streaming- transcription/
NEW QUESTION # 184
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