SAA-C03 - AWS CERTIFIED SOLUTIONS ARCHITECT - ASSOCIATE–EFFICIENT PDF GUIDE

SAA-C03 - AWS Certified Solutions Architect - Associate–Efficient PDF Guide

SAA-C03 - AWS Certified Solutions Architect - Associate–Efficient PDF Guide

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Amazon SAA-C03 certification is an industry-recognized credential for IT professionals who want to prove their expertise in designing and deploying scalable, highly available, and fault-tolerant systems on the Amazon Web Services (AWS) cloud platform. AWS Certified Solutions Architect - Associate certification is designed for individuals who have experience with AWS and are capable of identifying and defining requirements for AWS-based applications, services, and systems.

The SAA-C03 Exam is designed to assess the candidate's understanding of AWS services and how they can be used to design and deploy applications in a cloud environment. SAA-C03 exam consists of 65 multiple-choice and multiple-response questions that must be answered within 130 minutes. The passing score for SAA-C03 exam is 720 out of a possible 1000 points.

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Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q513-Q518):

NEW QUESTION # 513
[Design Secure Architectures]
A company has a web application in the AWS Cloud and wants to collect transaction data in real time. The company wants to prevent data duplication and does not want to manage infrastructure. The company wants to perform additional processing on the data after the data is collected.
Which solution will meet these requirements?

  • A. Configure an Amazon Simple Queue Service (Amazon SOS) FIFO queue. Configure an AWS Lambda function with an event source mapping for the FIFO queue to process the data.
  • B. Configure an Amazon Simple Queue Service (Amazon SQS) FIFO queue Use an AWS Batch job to remove duplicate data from the queue Configure an AWSLambda function to process the data.
  • C. Use Amazon Kinesis Data Streams to send the Incoming transaction data to an AWS Batch job that removes duplicate data. Launch an Amazon EC2 instance that runs a custom script lo process the data.
  • D. Set up an AWS Step Functions state machine to send incoming transaction data to an AWS Lambda function to remove duplicate data. Launch an Amazon EC2 instance that runs a custom script to process the data.

Answer: A

Explanation:
Understanding the Requirement: The company needs to collect transaction data in real time, avoid data duplication, and perform additional processing without managing infrastructure.
Analysis of Options:
SQS FIFO Queue with Lambda: Ensures data is processed in order and prevents duplication.Lambda handles processing without the need to manage servers.
SQS FIFO Queue with AWS Batch: While this ensures no duplicates, it introduces additional complexity and management overhead with AWS Batch.
Kinesis Data Streams with AWS Batch and EC2: Involves more components and infrastructure management, which is against the requirement of not wanting to manage infrastructure.
Step Functions with Lambda and EC2: Involves setting up multiple services and still requires managing EC2 instances, increasing complexity.
Best Solution:
SQS FIFO Queue with Lambda: This combination ensures real-time data processing, prevents duplication, and minimizes infrastructure management, meeting all requirements efficiently.
Reference:
Amazon SQS FIFO Queues
AWS Lambda and SQS Integration


NEW QUESTION # 514
[Design Resilient Architectures]
A company recently launched a new application for its customers. The application runs on multiple Amazon EC2 instances across two Availability Zones. End users use TCP to communicate with the application.
The application must be highly available and must automatically scale as the number of users increases.
Which combination of steps will meet these requirements MOST cost-effectively? (Select TWO.)

  • A. Manually add more EC2 instances for the application.
  • B. Add a Network Load Balancer in front of the EC2 instances.
  • C. Configure an Auto Scaling group for the EC2 instances.
  • D. Add an Application Load Balancer in front of the EC2 instances.
  • E. Add a Gateway Load Balancer in front of the EC2 instances.

Answer: B,C

Explanation:
For an application requiring TCP communication and high availability:
Network Load Balancer (NLB)is the best choice for load balancing TCP traffic because it is designed for handling high-throughput, low-latency connections.
Auto Scaling groupensures that the application can automatically scale based on demand, adding or removing EC2 instances as needed, which is crucial for handling user growth.
Option C (Application Load Balancer): ALB is primarily for HTTP/HTTPS traffic, not ideal for TCP.
Option D (Manual scaling): Manually adding instances does not provide the automation or scalability required.
Option E (Gateway Load Balancer): GLB is used for third-party virtual appliances, not for direct application load balancing.
AWS Reference:
Network Load Balancer
Auto Scaling Group


NEW QUESTION # 515
[Design High-Performing Architectures]
A company runs analytics software on Amazon EC2 instances The software accepts job requests from users to process data that has been uploaded to Amazon S3 Users report that some submitted data is not being processed Amazon CloudWatch reveals that the EC2 instances have a consistent CPU utilization at or near 100% The company wants to improve system performance and scale the system based on user load.
What should a solutions architect do to meet these requirements?

  • A. Create an S3 VPC endpoint for Amazon S3 Update the software to reference the endpoint
  • B. Stop the EC2 instances. Modify the instance type to one with a more powerful CPU and more memory. Restart the instances.
  • C. Create a copy of the instance Place all instances behind an Application Load Balancer
  • D. Route incoming requests to Amazon Simple Queue Service (Amazon SQS) Configure an EC2 Auto Scaling group based on queue size Update the software to read from the queue.

Answer: D

Explanation:
This option is the best solution because it allows the company to decouple the analytics software from the user requests and scale the EC2 instances dynamically based on the demand. By using Amazon SQS, the company can create a queue that stores the user requests and acts as a buffer between the users and the analytics software. This way, the software can process the requests at its own pace without losing any data or overloading the EC2 instances. By using EC2 Auto Scaling, the company cancreate an Auto Scaling group that launches or terminates EC2 instances automatically based on the size of the queue. This way, the company can ensure that there are enough instances to handle the load and optimize the cost and performance of the system. By updating the software to read from the queue, the company can enable the analytics software to consume the requests from the queue and process the data from Amazon S3.
A . Create a copy of the instance Place all instances behind an Application Load Balancer. This option is not optimal because it does not address the root cause of the problem, which is the high CPU utilization of the EC2 instances. An Application Load Balancer can distribute the incoming traffic across multiple instances, but it cannot scale the instances based on the load or reduce the processing time of the analytics software. Moreover, this option can incur additional costs for the load balancer and the extra instances.
B . Create an S3 VPC endpoint for Amazon S3 Update the software to reference the endpoint. This option is not effective because it does not solve the issue of the high CPU utilization of the EC2 instances. An S3 VPC endpoint can enable the EC2 instances to access Amazon S3 without going through the internet, which can improve the network performance and security. However, it cannot reduce the processing time of the analytics software or scale the instances based on the load.
C . Stop the EC2 instances. Modify the instance type to one with a more powerful CPU and more memory. Restart the instances. This option is not scalable because it does not account for the variability of the user load. Changing the instance type to a more powerful one can improve the performance of the analytics software, but it cannot adjust the number of instances based on the demand. Moreover, this option can increase the cost of the system and cause downtime during the instance modification.
Reference:
1 Using Amazon SQS queues with Amazon EC2 Auto Scaling - Amazon EC2 Auto Scaling
2 Tutorial: Set up a scaled and load-balanced application - Amazon EC2 Auto Scaling
3 Amazon EC2 Auto Scaling FAQs


NEW QUESTION # 516
[Design Secure Architectures]
A company has an AWS Direct Connect connection from its on-premises location to an AWS account The AWS account has 30 different VPCs in the same AWS Region The VPCs use private virtual interfaces (VIFs) Each VPC has a CIDR block that does not overlap with other networks under the company's control The company wants to centrally manage the networking architecture while still allowing each VPC to communicate with all other VPCs and on-premises networks Which solution will meet these requirements with the LEAST amount of operational overhead?

  • A. Create a transit gateway and associate the Direct Connect connection with a new transit VIF Turn on the transit gateway's route propagation feature
  • B. Create AWS Site-to-Site VPN connections from on premises to each VPC Ensure that both VPN tunnels are UP for each connection Turn on the route propagation feature
  • C. Create a Direct Connect gateway Recreate the private VIFs to use the new gateway Associate each VPC by creating new virtual private gateways
  • D. Create a transit VPC Connect the Direct Connect connection to the transit VPC Create a peenng connection between all other VPCs in the Region Update the route tables

Answer: A

Explanation:
This solution meets the following requirements:
It is operationally efficient, as it only requires one transit gateway and one transit VIF to connect the Direct Connect connection to all the VPCs in the same AWS Region. The transit gateway acts as a regional network hub that simplifies the network management and reduces the number of VIFs and gateways needed.
It is scalable, as it can support up to 5000 attachments per transit gateway, which can include VPCs, VPNs, Direct Connect gateways, and peering connections. The transit gateway can also be connected to other transit gateways in different Regions or accounts using peering connections, enabling cross-Region and cross-account connectivity.
It is flexible, as it allows each VPC to communicate with all other VPCs and on-premises networks using dynamic routing protocols such as Border Gateway Protocol (BGP). The transit gateway's route propagation feature automatically propagates the routes from the attached VPCs and VPNs to the transit gateway route table, eliminating the need to manually update the route tables.
Reference:
Transit Gateways - Amazon Virtual Private Cloud
Working with transit gateways - AWS Direct Connect
Amazon VPC-to-Amazon VPC connectivity options - Amazon Virtual Private Cloud Connectivity Options


NEW QUESTION # 517
[Design Operationally Excellent Architectures]
An insurance company runs an application on premises to process contracts. The application processes jobs that are comprised of many tasks. The individual tasks run for up to 5 minutes. Some jobs can take up to 24 hours in total to finish. If a task fails, the task must be reprocessed.
The company wants to migrate the application to AWS. The company will use Amazon S3 as part of the solution. The company wants to configure jobs to start automatically when a contract is uploaded to an S3 bucket.
Which solution will meet these requirements?

  • A. Use an AWS Batch job to handle the overall contract processing job. Configure the S3 bucket to send an event notification to initiate the Batch job.
  • B. Use an S3 event notification to notify an Amazon Simple Queue Service (Amazon SQS) queue when a contract is uploaded. Configure an AWS Lambda function to read messages from the queue and to run the contract processing job.
  • C. Use AWS Lambda functions to process individual tasks. Create a primary Lambda function to handle the overall job processing by calling individual Lambda functions in sequence. Configure the S3 bucket to send an event notification to invoke the primary Lambda function to begin processing.
  • D. Use a state machine in AWS Step Functions to handle the overall contract processing job. Configure the S3 bucket to send an event notification to Amazon EventBridge. Create a rule in Amazon EventBridge to target the state machine.

Answer: D

Explanation:
AWS Step Functions supports long-running workflows and error retries, making it ideal for a job composed of many tasks. Integration with EventBridge allows automatic triggering from S3 events. This setup is resilient and supports up to 1-year execution duration.
Reference:


NEW QUESTION # 518
......

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