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Amazon SAA-C03, also known as the Amazon AWS Certified Solutions Architect - Associate (SAA-C03) exam, is a certification exam offered by Amazon Web Services (AWS). SAA-C03 Exam is designed to assess the candidate's knowledge and skills in designing and deploying scalable, highly available, and fault-tolerant systems on the AWS platform. It is an associate-level certification exam that is intended for individuals with some experience in AWS and cloud computing.

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The Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam certification exam is ideal for professionals who are looking to advance their careers in the cloud computing industry. It is also suitable for those who want to validate their AWS skills and knowledge to potential employers. Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam certification provides a competitive edge in the job market, and it is recognized globally as a standard for AWS expertise. With the growing demand for cloud computing professionals, the Amazon SAA-C03 Certification Exam is an excellent opportunity for individuals to enhance their skills and further their career.

Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam Sample Questions (Q192-Q197):

NEW QUESTION # 192
An IAM user made several configuration changes to AWS resources m their company's account during a production deployment last week. A solutions architect learned that a couple of security group rules are not configured as desired. The solutions architect wants to confirm which IAM user was responsible for making changes.
Which service should the solutions architect use to find the desired information?

A. Amazon Inspector
B. Amazon GuardDuty
C. AWS CloudTrail
D. AWS Config

Answer: C

Explanation:
The best option is to use AWS CloudTrail to find the desired information. AWS CloudTrail is a service that enables governance, compliance, operational auditing, and risk auditing of AWS account activities. CloudTrail can be used to log all changes made to resources in an AWS account, including changes made by IAM users, EC2 instances, AWS management console, and other AWS services. By using CloudTrail, the solutions architect can identify the IAM user who made the configuration changes to the security group rules.
.

NEW QUESTION # 193
A company has deployed a database in Amazon RDS for MySQL. Due to increased transactions, the database support team is reporting slow reads against the DB instance and recommends adding a read replica.
Which combination of actions should a solutions architect take before implementing this change? (Choose two.)

A. Create a global table and specify the AWS Regions where the table will be available.
B. Enable automatic backups on the source instance by setting the backup retention period to a value other than 0.
C. Choose a failover priority for the source DB instance.
D. Enable binlog replication on the RDS primary node.
E. Allow long-running transactions to complete on the source DB instance.

Answer: B,E

Explanation:
"An active, long-running transaction can slow the process of creating the read replica. We recommend that you wait for long-running transactions to complete before creating a read replica. If you create multiple read replicas in parallel from the same source DB instance, Amazon RDS takes only one snapshot at the start of the first create action. When creating a read replica, there are a few things to consider. First, you must enable automatic backups on the source DB instance by setting the backup retention period to a value other than 0.
This requirement also applies to a read replica that is the source DB instance for another read replica"
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_ReadRepl.html

NEW QUESTION # 194
A company is building a serverless application to process orders from an e-commerce site. The application needs to handle bursts of traffic during peak usage hours and to maintain high availability.
The orders must be processed asynchronously in the order the application receives them.

A. Use an Amazon Simple Notification Service (Amazon SNS) topic to receive orders. Use an AWS Lambda function to process the orders.
B. Use an Amazon Simple Queue Service (Amazon SQS) FIFO queue to receive orders. Use an AWS Lambda function to process the orders.
C. Use an Amazon Simple Notification Service (Amazon SNS) topic to receive orders. Use AWS Batch jobs to process the orders.
D. Use an Amazon Simple Queue Service (Amazon SQS) standard queue to receive orders. Use AWS Batch jobs to process the orders.

Answer: B

Explanation:
* Key Requirements:
* Serverless architecture.
* Handle traffic bursts with high availability.
* Process orders asynchronously in the order they are received.
* Analysis of Options:
* Option A: Amazon SNS delivers messages to subscribers. However, SNS does not ensure ordering, making it unsuitable for FIFO (First In, First Out) requirements.
* Option B: Amazon SQS FIFO queues support ordering and ensure messages are delivered exactly once. AWS Lambda functions can be triggered by SQS to process messages asynchronously and efficiently. This satisfies all requirements.
* Option C: Amazon SQS standard queues do not guarantee message order and have "at-least- once" delivery, making them unsuitable for the FIFO requirement.
* Option D: Similar to Option A, SNS does not ensure message ordering, and using AWS Batch adds complexity without directly addressing the requirements.
* AWS References:
* Amazon SQS FIFO Queues
* AWS Lambda and SQS Integration

NEW QUESTION # 195
A company hosts a three-tier web application in the AWS Cloud. A Multi-AZ Amazon RDS for MySQL server forms the database layer. Amazon ElastiCache forms the cache layer. The company wants a caching strategy that adds or updates data in the cache when a customer adds an item to the database. The data in the cache must always match the data in the database.
Which solution will meet these requirements?

A. Implement the adding TTL caching strategy.
B. Implement the AWS AppConfig caching strategy.
C. Implement the write-through caching strategy.
D. Implement the lazy loading caching strategy

Answer: C

Explanation:
A write-through caching strategy adds or updates data in the cache whenever data is written to the database. This ensures that the data in the cache is always consistent with the data in the database. A write-through caching strategy also reduces the cache miss penalty, as data is always available in the cache when it is requested. However, a write-through caching strategy can increase the write latency, as data has to be written to both the cache and the database. A write-through caching strategy is suitable for applications that require high data consistency and low read latency.
A lazy loading caching strategy only loads data into the cache when it is requested, and updates the cache when there is a cache miss. This can result in stale data in the cache, as data is not updated in the cache when it is changed in the database. A lazy loading caching strategy is suitable for applications that can tolerate some data inconsistency and have a low cache miss rate.
An adding TTL caching strategy assigns a time-to-live (TTL) value to each data item in the cache, and removes the data from the cache when the TTL expires. This can help prevent stale data in the cache, as data is periodically refreshed from the database. However, an adding TTL caching strategy can also increase the cache miss rate, as data can be evicted from the cache before it is requested. An adding TTL caching strategy is suitable for applications that have a high cache hit rate and can tolerate some data inconsistency.
An AWS AppConfig caching strategy is not a valid option, as AWS AppConfig is a service that enables customers to quickly deploy validated configurations to applications of any size and scale. AWS AppConfig does not provide a caching layer for web applications.

NEW QUESTION # 196
A company runs container applications by using Amazon Elastic Kubernetes Service (Amazon EKS) and the Kubernetes Horizontal Pod Autoscaler. The workload is not consistent throughout the day. A solutions architect notices that the number of nodes does not automatically scale out when the existing nodes have reached maximum capacity in the cluster, which causes performance issues Which solution will resolve this issue with the LEAST administrative overhead?

A. Scale out the nodes by tracking the memory usage
B. Use the Kubernetes Cluster Autoscaler to manage the number of nodes in the cluster.
C. Use an Amazon EC2 Auto Scaling group to distribute the workload.
D. Use an AWS Lambda function to resize the EKS cluster automatically.

Answer: B

Explanation:
Explanation
The Kubernetes Cluster Autoscaler is a component that automatically adjusts the number of nodes in your cluster when pods fail or are rescheduled onto other nodes. It uses Auto Scaling groups to scale up or down the nodes according to the demand and capacity of your cluster1.
By using the Kubernetes Cluster Autoscaler in your Amazon EKS cluster, you can achieve the following benefits:
* You can improve the performance and availability of your container applications by ensuring that there are enough nodes to run your pods and that there are no idle nodes wasting resources.
* You can reduce the administrative overhead of managing your cluster size manually or using custom scripts. The Cluster Autoscaler handles the scaling decisions and actions for you based on the metrics and events from your cluster.
* You can leverage the integration of Amazon EKS and AWS Auto Scaling to optimize the cost and efficiency of your cluster. You can use features such as launch templates, mixed instances policies, and spot instances to customize your node configuration and save up to 90% on compute costs2

NEW QUESTION # 197
......

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SAA-C03 Valid Exam Cost | Test SAA-C03 Result

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Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam Sample Questions (Q192-Q197):

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