UNPARALLELED AMAZON CERTIFICATION SAA-C03 EXAM DUMPS - PASS4GUIDE FREE DOWNLOAD

Unparalleled Amazon Certification SAA-C03 Exam Dumps - Pass4guide Free Download

Unparalleled Amazon Certification SAA-C03 Exam Dumps - Pass4guide Free Download

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Amazon SAA-C03 (Amazon AWS Certified Solutions Architect - Associate (SAA-C03)) certification exam is a highly sought-after credential for IT professionals who want to demonstrate their expertise in designing and deploying scalable, fault-tolerant, and highly available systems on Amazon Web Services (AWS) platform. Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam certification exam is designed to test candidates' knowledge of AWS services, architectural principles, and best practices for building secure and reliable applications on the cloud.

Amazon SAA-C03 (Amazon AWS Certified Solutions Architect - Associate) certification exam is designed for IT professionals who want to demonstrate their expertise in designing and deploying scalable, highly available, and fault-tolerant systems on the Amazon Web Services (AWS) platform. The SAA-C03 Exam is the latest version of the AWS Certified Solutions Architect - Associate certification and it covers the latest AWS services and best practices. SAA-C03 exam is intended for professionals who have at least one year of experience in designing and deploying AWS-based applications.

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Amazon SAA-C03 Exam is updated to reflect the latest AWS services and features, making it a reliable measure of candidates' knowledge and skills in AWS. SAA-C03 exam covers a broad range of topics, including AWS core services, security, database, and networking. Successful candidates are expected to be able to design and deploy scalable, cost-effective solutions that meet the specific needs of their clients or organizations.

Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam Sample Questions (Q918-Q923):

NEW QUESTION # 918
A company has an existing VPC which is quite unutilized for the past few months. The Business Manager instructed the Solutions Architect to integrate the company's on-premises data center and its VPC. The architect explained the list of tasks that he'll be doing and discussed the Virtual Private Network (VPN) connection. The Business Manager is not tech-savvy but he is interested to know what a VPN is and its benefits.
What is one of the major advantages of having a VPN in AWS?

  • A. It provides a cost-effective, hybrid connection from your VPC to your on-premises data centers which bypasses the public Internet.
  • B. It enables you to establish a private and dedicated network connection between your network and your VPC
  • C. It allows you to connect your AWS cloud resources to your on-premises data center using secure and private sessions with IP Security (IPSec) or Transport Layer Security (TLS) tunnels.
  • D. It provides a networking connection between two VPCs which enables you to route traffic between them using private IPv4 addresses or IPv6 addresses.

Answer: C

Explanation:
Amazon VPC offers you the flexibility to fully manage both sides of your Amazon VPC connectivity by creating a VPN connection between your remote network and a software VPN appliance running in your Amazon VPC network. This option is recommended if you must manage both ends of the VPN connection either for compliance purposes or for leveraging gateway devices that are not currently supported by Amazon VPC's VPN solution.
You can connect your Amazon VPC to remote networks and users using the following VPN connectivity options:
AWS Site-to-Site VPN - creates an IPsec VPN connection between your VPC and your remote network.
On the AWS side of the Site-to-Site VPN connection, a virtual private gateway or transit gateway provides two VPN endpoints (tunnels) for automatic failover.
AWS Client VPN - a managed client-based VPN service that provides secure TLS VPN connections between your AWS resources and on-premises networks.
AWS VPN CloudHub - capable of wiring multiple AWS Site-to-Site VPN connections together on a virtual private gateway. This is useful if you want to enable communication between different remote networks that uses a Site-to-Site VPN connection.
Third-party software VPN appliance - You can create a VPN connection to your remote network by using an Amazon EC2 instance in your VPC that's running a third party software VPN appliance.

With a VPN connection, you can connect to an Amazon VPC in the cloud the same way you connect to your branches while establishing secure and private sessions with IP Security (IPSec) or Transport Layer Security (TLS) tunnels.
Hence, the correct answer is the option that says: It allows you to connect your AWS cloud resources to your on-premises data center using secure and private sessions with IP Security (IPSec) or Transport Layer Security (TLS) tunnels since one of the main advantages of having a VPN connection is that you will be able to connect your Amazon VPC to other remote networks securely.
The option that says: It provides a cost-effective, hybrid connection from your VPC to your on-premises data centers which bypasses the public Internet is incorrect. Although it is true that a VPN provides a cost-effective, hybrid connection from your VPC to your on-premises data centers, it certainly does not bypass the public Internet. A VPN connection actually goes through the public Internet, unlike the AWS Direct Connect connection which has a direct and dedicated connection to your on-premises network.
The option that says: It provides a networking connection between two VPCs which enables you to route traffic between them using private IPv4 addresses or IPv6 addresses is incorrect because this actually describes VPC Peering and not a VPN connection.
The option that says: It enables you to establish a private and dedicated network connection between your network and your VPC is incorrect because this is the advantage of an AWS Direct Connect connection and not a VPN.
References:
http://docs.aws.amazon.com/AmazonVPC/latest/UserGuide/vpn-connections.html
https://docs.aws.amazon.com/whitepapers/latest/aws-vpc-connectivity-options/software-vpn-network-to- amazon.html Amazon VPC Overview:
https://www.youtube.com/watch?v=oIDHKeNxvQQ
Check out this Amazon VPC Cheat Sheet:
https://tutorialsdojo.com/amazon-vpc/
Tutorials Dojo's AWS Certified Solutions Architect Associate Exam Study Guide:
https://tutorialsdojo.com/aws-certified-solutions-architect-associate/


NEW QUESTION # 919
A company is migrating a legacy application from an on-premises data center to AWS. The application relies on hundreds of cron Jobs that run between 1 and 20 minutes on different recurring schedules throughout the day.
The company wants a solution to schedule and run the cron jobs on AWS with minimal refactoring. The solution must support running the cron jobs in response to an event in the future.
Which solution will meet these requirements?

  • A. Create a container image for the cron jobs. Create a workflow in AWS Step Functions that uses a Wait state to run the cron jobs at a specified time. Use the RunTask action to run the cron job tasks on AWS Fargate.
  • B. Create a container image for the cron jobs. Use AWS Batch on Amazon Elastic Container Service (Amazon ECS) with a scheduling policy to run the cron jobs.
  • C. Create a container image for the cron jobs. Use Amazon EventBridge Scheduler to create a recurring schedule. Run the cron job tasks as AWS Lambda functions.
  • D. Create a container image for the cron jobs. Use Amazon EventBridge Scheduler to create a recurring schedule Run the cron job tasks on AWS Fargate.

Answer: D

Explanation:
This solution is the most suitable for running cron jobs on AWS with minimal refactoring, while also supporting the possibility of running jobs in response to future events.
* Container Image for Cron Jobs: By containerizing the cron jobs, you can package the environment and dependencies required to run the jobs, ensuring consistency and ease of deployment across different environments.
* Amazon EventBridge Scheduler: EventBridge Scheduler allows you to create a recurring schedule that can trigger tasks (like running your cron jobs) at specific times or intervals. It provides fine-grained control over scheduling and integrates seamlessly with AWS services.
* AWS Fargate: Fargate is a serverless compute engine for containers that removes the need to manage EC2 instances. It allows you to run containers without worrying about the underlying infrastructure.
Fargate is ideal for running jobs that can vary in duration, like cron jobs, as it scales automatically based on the task's requirements.
* Why Not Other Options?:
* Option A (Lambda): While AWS Lambda could handle short-running cron jobs, it has limitations in terms of execution duration (maximum of 15 minutes) and might not be suitable for jobs that run up to 20 minutes.
* Option B (AWS Batch on ECS): AWS Batch is more suitable for batch processing and workloads that require complex job dependencies or orchestration, which might be more than what is needed for simple cron jobs.
* Option D (Step Functions with Wait State): While Step Functions provide orchestration capabilities, this approach would introduce unnecessary complexity and overhead compared to the straightforward scheduling with EventBridge and running on Fargate.
AWS References:
* Amazon EventBridge Scheduler - Details on how to schedule tasks using Amazon EventBridge Scheduler.
* AWS Fargate - Information on how to run containers in a serverless manner using AWS Fargate.


NEW QUESTION # 920
A company has an event-driven application that invokes AWS Lambda functions up to 800 times each minute with varying runtimes. The Lambda functions access data that is stored in an Amazon Aurora MySQL OB cluster. The company is noticing connection timeouts as user activity increases The database shows no signs of being overloaded. CPU. memory, and disk access metrics are all low.
Which solution will resolve this issue with the LEAST operational overhead?

  • A. Use Amazon ROS Proxy to create a proxy. Set the DB cluster as the target database Configure the Lambda functions lo connect to the proxy rather than to the DB cluster.
  • B. Set up Amazon ElastiCache tor Redls to cache commonly read items from the database. Configure the Lambda functions to connect to ElastiCache for reads.
  • C. Adjust the size of the Aurora MySQL nodes to handle more connections. Configure retry logic in the Lambda functions for attempts to connect to the database
  • D. Add an Aurora Replica as a reader node. Configure the Lambda functions to connect to the reader endpoint of the OB cluster rather than lo the writer endpoint.

Answer: A


NEW QUESTION # 921
A company is preparing a new data platform that will ingest real-time streaming data from multiple sources.
The company needs to transform the data before writing the data to Amazon S3. The company needs the ability to use SQL to query the transformed data.
Which solutions will meet these requirements? (Choose two.)

  • A. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use AWS Glue to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.
  • B. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use Amazon Kinesis Data Analytics to transform the data and to write the data to Amazon S3. Use the Amazon RDS query editor to query the transformed data from Amazon S3.
  • C. Use AWS Database Migration Service (AWS DMS) to ingest the data. Use Amazon EMR to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.
  • D. Use Amazon Kinesis Data Streams to stream the data. Use AWS Glue to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use the Amazon RDS query editor to query the transformed data from Amazon S3.
  • E. Use Amazon Kinesis Data Streams to stream the data. Use Amazon Kinesis Data Analytics to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.

Answer: A,E

Explanation:
To ingest, transform, and query real-time streaming data from multiple sources, Amazon Kinesis and Amazon MSK are suitable solutions. Amazon Kinesis Data Streams can stream the data from various sources and integrate with other AWS services. Amazon Kinesis Data Analytics can transform the data using SQL or Apache Flink. Amazon Kinesis Data Firehose can write the data to Amazon S3 or other destinations. Amazon Athena can query the transformed data from Amazon S3 using standard SQL. Amazon MSK can stream the data using Apache Kafka, which is a popular open-source platform for streaming data. AWS Glue can transform the data using Apache Spark or Python scripts and write the data to Amazon S3 or other destinations. Amazon Athena can also query the transformed data from Amazon S3 using standard SQL.
References:
What Is Amazon Kinesis Data Streams?
What Is Amazon Kinesis Data Analytics?
What Is Amazon Kinesis Data Firehose?
What Is Amazon Athena?
What Is Amazon MSK?
What Is AWS Glue?


NEW QUESTION # 922
A company is building a solution that will report Amazon EC2 Auto Scaling events across all the applications in an AWS account. The company needs to use a serverless solution to store the EC2 Auto Scaling status data in Amazon S3. The company then will use the data in Amazon S3 to provide near-real-time updates in a dashboard. The solution must not affect the speed of EC2 instance launches.
How should the company move the data to Amazon S3 to meet these requirements?

  • A. Use an Amazon CloudWatch metric stream to send the EC2 Auto Scaling status data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.
  • B. Use a bootstrap script during the launch of an EC2 instance to install Amazon Kinesis Agent. Configure Kinesis Agent to collect the EC2 Auto Scaling status data and send the data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.
  • C. Launch an Amazon EMR cluster to collect the EC2 Auto Scaling status data and send the data to Amazon Kinesis Data Firehose. Store the data in Amazon S3.
  • D. Create an Amazon EventBridge rule to invoke an AWS Lambda function on a schedule. Configure the Lambda function to send the EC2 Auto Scaling status data directly to Amazon S3.

Answer: A

Explanation:
Explanation
You can use metric streams to continually stream CloudWatch metrics to a destination of your choice, with near-real-time delivery and low latency. One of the use cases is Data Lake: create a metric stream and direct it to an Amazon Kinesis Data Firehose delivery stream that delivers your CloudWatch metrics to a data lake such as Amazon S3.
https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Metric-Streams.html


NEW QUESTION # 923
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