100% PASS SAA-C03 RELIABLE TEST SYLLABUS - REALISTIC AWS CERTIFIED SOLUTIONS ARCHITECT - ASSOCIATE DISCOUNT

100% Pass SAA-C03 Reliable Test Syllabus - Realistic AWS Certified Solutions Architect - Associate Discount

100% Pass SAA-C03 Reliable Test Syllabus - Realistic AWS Certified Solutions Architect - Associate Discount

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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.

Amazon SAA-C03 exam is a valuable certification for IT professionals who want to become certified in AWS solutions architecture. It covers a wide range of topics and is designed to test your knowledge of AWS services, best practices, and solutions architecture patterns. AWS Certified Solutions Architect - Associate certification can help you advance your career and increase your earning potential, and is recognized globally as a valuable credential.

To achieve the Amazon SAA-C03 Certification, candidates need to demonstrate their proficiency in various AWS services, such as EC2, S3, RDS, VPC, and Route 53, among others. Candidates are required to have at least one year of hands-on experience in designing and deploying scalable, highly available, and fault-tolerant systems on AWS. The SAA-C03 certification exam consists of 65 multiple-choice and multiple-response questions, and the candidates have 130 minutes to complete the exam. The passing score for the exam is 720 out of 1000 points. Earning the Amazon SAA-C03 certification not only validates the candidate’s expertise in AWS but also demonstrates their commitment to staying up-to-date with the latest trends and best practices in cloud computing.

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Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q871-Q876):

NEW QUESTION # 871
A company has implemented a self-managed DNS service on AWS. The solution consists of the following:
* Amazon EC2 instances in different AWS Regions
* Endpomts of a standard accelerator m AWS Global Accelerator
The company wants to protect the solution against DDoS attacks What should a solutions architect do to meet this requirement?

  • A. Create an AWS WAF web ACL that includes a rate-based rule Associate the web ACL with the EC2 instances
  • B. Subscribe to AWS Shield Advanced Add the accelerator as a resource to protect
  • C. Create an AWS WAF web ACL that includes a rate-based rule Associate the web ACL with the accelerator
  • D. Subscribe to AWS Shield Advanced Add the EC2 instances as resources to protect

Answer: B

Explanation:
AWS Shield is a managed service that provides protection against Distributed Denial of Service (DDoS) attacks for applications running on AWS. AWS Shield Standard is automatically enabled to all AWS customers at no additional cost. AWS Shield Advanced is an optional paid service. AWS Shield Advanced provides additional protections against more sophisticated and larger attacks for your applications running on Amazon Elastic Compute Cloud (EC2), Elastic Load Balancing (ELB), Amazon CloudFront, AWS Global Accelerator, and Route 53.
https://docs.aws.amazon.com/waf/latest/developerguide/ddos-event-mitigation-logic-gax.html


NEW QUESTION # 872
[Design Secure Architectures]
A solution architect is designing a company's disaster recovery (DR) architecture. The company has a MySQL database that runs on an Amazon EC2 instance in a private subnet with scheduled backup. The DR design to include multiple AWS Regions.
Which solution will meet these requiements with the LEAST operational overhead?

  • A. Store the schedule backup of the MySQL database in an Amazon S3 bucket that is configured for S3 Cross-Region Replication (CRR). Use the data backup to restore the database in the DR Region.
  • B. Migrate the MySQL database to Amazon RDS. Use a Multi-AZ deployment. Turn on read replication for the primary DB instance in the different Availability Zones.
  • C. Migrate the MySQL database to an Amazon Aurora global database. Host the primary DB cluster in the primary Region. Host the secondary DB cluster in the DR Region.
  • D. Migrate the MySQL database to multiple EC2 instances. Configure a standby EC2 instance in the DR Region Turn on replication.

Answer: C

Explanation:
Migrate MySQL database to an Amazon Aurora global database is the best solution because it requires minimal operational overhead. Aurora is a managed service that provides automatic failover, so standby instances do not need to be manually configured. The primary DB cluster can be hosted in the primary Region, and the secondary DB cluster can be hosted in the DR Region. This approach ensures that the data is always available and up-to-date in multiple Regions, without requiring significant manual intervention.


NEW QUESTION # 873
A company wants to create an application to store employee data in a hierarchical structured relationship. The company needs a minimum-latency response to high-traffic queries for the employee data and must protect any sensitive data. The company also needs to receive monthly email messages if any financial information is present in the employee data.
Which combination of steps should a solutions architect take to meet these requirements? (Select TWO.)

  • A. Configure Amazon Macie for the AWS account Integrate Macie with Amazon EventBridge to send monthly notifications through an Amazon Simple Notification Service (Amazon SNS) subscription.
  • B. Use Amazon Athena to analyze the employee data in Amazon S3. Integrate Athena with Amazon QuickSight to publish analysis dashboards and share the dashboards with users.
  • C. Use Amazon Redshift to store the employee data in hierarchies. Unload the data to Amazon S3 every month.
  • D. Use Amazon DynamoDB to store the employee data in hierarchies. Export the data to Amazon S3 every month.
  • E. Configure Amazon fvlacie for the AWS account. Integrate Macie with Amazon EventBridge to send monthly events to AWS Lambda.

Answer: A,D

Explanation:
Generally, for building a hierarchical relationship model, a graph database such as Amazon Neptune is a better choice. In some cases, however, DynamoDB is a better choice for hierarchical data modeling because of its flexibility, security, performance, and scale.
https://docs.aws.amazon.com/prescriptive-guidance/latest/dynamodb-hierarchical-data-model/introduction.html


NEW QUESTION # 874
[Design High-Performing Architectures]
How can trade data from DynamoDB be ingested into an S3 data lake for near real-time analysis?

  • A. Use DynamoDB Streams to invoke a Lambda function that writes to Data Firehose, which writes to S3.
  • B. Use DynamoDB Streams to invoke a Lambda function that writes to S3.
  • C. Enable Kinesis Data Streams on DynamoDB. Use Data Firehose to write to S3.
  • D. Enable Kinesis Data Streams on DynamoDB. Configure it to invoke a Lambda function that writes to S3.

Answer: B

Explanation:
Option Ais the simplest solution, using DynamoDB Streams and Lambda for real-time ingestion into S3.
Options B, C, and Dadd unnecessary complexity with Data Firehose or Kinesis.


NEW QUESTION # 875
A company has an application that places hundreds of .csv files into an Amazon S3 bucket every hour. The files are 1 GB in size. Each time a file is uploaded, the company needs to convert the file to Apache Parquet format and place the output file into an S3 bucket.
Which solution will meet these requirements with the LEAST operational overhead?

  • A. Create an Apache Spark job to read the .csv files, convert the files to Parquet format, and place the output files in an S3 bucket. Create an AWS Lambda function for each S3 PUT event to invoke the Spark job.
  • B. Create an AWS Glue table and an AWS Glue crawler for the S3 bucket where the application places the
    .csv files. Schedule an AWS Lambda function to periodically use Amazon Athena to query the AWS Glue table, convert the query results into Parquet format, and place the output files into an S3 bucket.
  • C. Create an AWS Glue extract, transform, and load (ETL) job to convert the .csv files to Parquet format and place the output files into an S3 bucket. Create an AWS Lambda function for each S3 PUT event to invoke the ETL job.
  • D. Create an AWS Lambda function to download the .csv files, convert the files to Parquet format, and place the output files in an S3 bucket. Invoke the Lambda function for each S3 PUT event.

Answer: C

Explanation:
https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/three-aws-glue-etl-job-types-for- converting-data-to-apache-parquet.html


NEW QUESTION # 876
......

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