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Amazon AWS-Solutions-Associate Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Design Resilient Architectures	26%	- Implement appropriate caching strategies 1. Amazon CloudFront 2. Cache invalidation strategies 3. AWS Global Accelerator 4. Amazon ElastiCache - Design highly available architectures 1. Fault-tolerant design patterns 2. RTO and RPO considerations 3. Disaster recovery strategies 4. Amazon Route 53 routing policies - Design multi-tier architectures 1. Auto Scaling groups 2. Multi-AZ deployments 3. Highly available architecture patterns 4. Load balancing strategies
Topic 2: Design Cost-Optimized Architectures	20%	- Design cost-optimized compute solutions 1. Right-sizing resources 2. Auto Scaling cost optimization 3. Savings Plans 4. Reserved Instances vs On-Demand vs Spot - Design cost-optimized database solutions 1. Database caching strategies 2. DynamoDB on-demand vs provisioned 3. Amazon RDS, Aurora pricing 4. Cost-effective query patterns - Design cost-optimized storage solutions 1. Intelligent Tiering 2. S3 lifecycle policies 3. Cost-effective data storage patterns 4. Storage Gateway
Topic 3: Design Secure Architectures	30%	- Appropriate data security controls 1. AWS KMS, AWS CloudHSM 2. S3 bucket policies and access controls 3. Security posture management 4. Encryption at rest and in transit - Design secure application tiers 1. Public vs private subnets 2. Application security patterns 3. AWS PrivateLink, VPC endpoints 4. VPC architecture (subnets, ACLs, security groups) - Design secure access to AWS resources 1. IAM users, groups, roles, and policies 2. Least privilege principles 3. AWS STS and temporary credentials 4. IAM permissions boundaries
Topic 4: Design High-Performing Architectures	24%	- Design data transfer solutions 1. AWS DataSync, Snow Family 2. S3 Transfer Acceleration 3. Network optimization - Identify elastic and scalable compute solutions 1. EC2 Auto Scaling 2. Amazon ECS, EKS, Lambda 3. Serverless architectures 4. Container-based solutions - Design highly available and scalable storage solutions 1. Amazon S3 storage classes 2. Storage cost optimization 3. Amazon EFS, EBS, FSx 4. Data lifecycle management

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Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Sample Questions (Q345-Q350):

NEW QUESTION # 345
A company recently expanded globally and wants to make its application accessible to users in those geographic locations. The application is deploying on Amazon EC2 instances behind an Application Load balancer in an Auto Scaling group. The company needs the ability shift traffic from resources in one region to another.
What should a solutions architect recommend?

A. Configure an Amazon Route 53 multivalue answer routing policy
B. Configure an Amazon Route 53 geolocation routing policy
C. Configure an Amazon Route 53 latency routing policy
D. Configure an Amazon Route 53 geoproximity fouling policy.

Answer: B

NEW QUESTION # 346
What is the maximum write throughput I can provision for a single Dynamic DB table?

A. 10,000 write capacity units
B. Dynamic DB is designed to scale without limits, but if you go beyond 10,000 you have to contact AWS first.
C. 100,000 write capacity units
D. 1,000 write capacity units

Answer: B

Explanation:
Explanation/Reference:
Explanation:
https://aws.amazon.com/dynamodb/faqs/

NEW QUESTION # 347

Refer to the architecture diagram above of a batch processing solution using Simple Queue Service (SQS) to set up a message queue between EC2 instances which are used as batch processors Cloud Watch monitors the number of Job requests (queued messages) and an Auto Scaling group adds or deletes batch servers automatically based on parameters set in Cloud Watch alarms.
You can use this architecture to implement which of the following features in a cost effective and efficient manner?

A. Reduce the overall lime for executing jobs through parallel processing by allowing a busy EC2 instance that receives a message to pass it to the next instance in a daisy-chain setup.
B. Handle high priority jobs before lower priority jobs by assigning a priority metadata field to SQS messages.
C. Coordinate number of EC2 instances with number of job requests automatically thus Improving cost effectiveness.
D. Implement message passing between EC2 instances within a batch by exchanging messages through SQS.
E. Implement fault tolerance against EC2 instance failure since messages would remain in SQS and worn can continue with recovery of EC2 instances implement fault tolerance against SQS failure by backing up messages to S3.

Answer: C

Explanation:
Explanation/Reference:
Explanation:
There are cases where a large number of batch jobs may need processing, and where the jobs may need to be re-prioritized.
For example, one such case is one where there are differences between different levels of services for unpaid users versus subscriber users (such as the time until publication) in services enabling, for example, presentation files to be uploaded for publication from a web browser. When the user uploads a presentation file, the conversion processes, for example, for publication are performed as batch processes on the system side, and the file is published after the conversion. Is it then necessary to be able to assign the level of priority to the batch processes for each type of subscriber?
Explanation of the Cloud Solution/Pattern
A queue is used in controlling batch jobs. The queue need only be provided with priority numbers. Job requests are controlled by the queue, and the job requests in the queue are processed by a batch server.
In Cloud computing, a highly reliable queue is provided as a service, which you can use to structure a highly reliable batch system with ease. You may prepare multiple queues depending on priority levels, with job requests put into the queues depending on their priority levels, to apply prioritization to batch processes. The performance (number) of batch servers corresponding to a queue must be in accordance with the priority level thereof.
Implementation
In AWS, the queue service is the Simple Queue Service (SQS). Multiple SQS queues may be prepared to prepare queues for individual priority levels (with a priority queue and a secondary queue). Moreover, you may also use the message Delayed Send function to delay process execution.
Use SQS to prepare multiple queues for the individual priority levels.
Place those processes to be executed immediately (job requests) in the high priority queue.
Prepare numbers of batch servers, for processing the job requests of the queues, depending on the priority levels.
Queues have a message "Delayed Send" function. You can use this to delay the time for starting a process.
Configuration

Benefits
You can increase or decrease the number of servers for processing jobs to change automatically the processing speeds of the priority queues and secondary queues.
You can handle performance and service requirements through merely increasing or decreasing the number of EC2 instances used in job processing.
Even if an EC2 were to fail, the messages (jobs) would remain in the queue service, enabling processing to be continued immediately upon recovery of the EC2 instance, producing a system that is robust to failure.
Cautions
Depending on the balance between the number of EC2 instances for performing the processes and the number of messages that are queued, there may be cases where processing in the secondary queue may be completed first, so you need to monitor the processing speeds in the primary queue and the secondary queue.

NEW QUESTION # 348
What does elasticity mean to AWS?

A. The ability to scale computing resources up easily, with minimal friction and down with latency.
B. The ability to scale computing resources up and down easily, with minimal friction.
C. The ability to recover from business continuity events with minimal friction.
D. The ability to provision cloud computing resources in expectation of future demand.

Answer: B

NEW QUESTION # 349
Question:
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.
Options:

A. Place the frontend EC2 instances into an Auto Scaling group. Create an Auto Scaling policy to launch new instances to handle the incoming network traffic.
B. Place the frontend EC2 instances into an Auto Scaling group. Add an Amazon ElastiCache cluster in front of the ALB to reduce the amount of traffic the API needs to handle.
C. Double the number of frontend and backend EC2 instances to handle the increased traffic during the product launch event. Create a dead-letter queue to retain unprocessed sales requests when the demand exceeds the system capacity.
D. Place the frontend and backend EC2 instances into separate Auto Scaling groups. Create a policy for the frontend Auto Scaling group to launch instances based on incoming network traffic. Create a policy for the backend Auto Scaling group to launch instances based on the SQS queue backlog.

Answer: D

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.
References:
Tutorial: Set up a scaled and load-balanced application
Scaling policy based on Amazon SQSAWS Documentation

NEW QUESTION # 350
......

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