LATEST AMAZON AWS-SOLUTIONS-ASSOCIATE QUESTIONS IN THREE DIFFERENT FORMATS

Latest Amazon AWS-Solutions-Associate Questions in Three Different Formats

Latest Amazon AWS-Solutions-Associate Questions in Three Different Formats

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The AWS Certified Solutions Architect - Associate (SAA-C02) exam is a certification that validates an individual's skills and expertise in designing and deploying scalable, highly available, and fault-tolerant systems on Amazon Web Services (AWS) cloud platform. AWS-Solutions-Associate Exam is intended for professionals who work as solutions architects, system administrators, or developers and want to demonstrate their proficiency in AWS services and solutions.

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The AWS-Solutions-Associate certification exam is a challenging exam that requires a solid understanding of AWS services and architecture. To prepare for AWS-Solutions-Associate exam, candidates can take advantage of various resources, including AWS documentation, online courses, practice exams, and study guides. With proper preparation and dedication, passing AWS-Solutions-Associate Exam can be a great accomplishment that can help propel your career to new heights.

Amazon AWS Certified Solutions Architect - Associate (SAA-C02) Sample Questions (Q109-Q114):

NEW QUESTION # 109
An online company wants to conduct real-time sentiment analysis about its products from its social media channels using SQL.
Which of the following solutions has the LOWEST cost and operational burden?

  • A. Configure the input stream using Amazon Kinesis Data Streams. Use Amazon Kinesis Data Analytics to write SQL queries against the stream.
  • B. Configure the input stream using Amazon Kinesis Data Streams. Use Amazon Kinesis Data Firehose to send data to an Amazon Redshift cluster, and then query directly against Amazon Redshift
  • C. Set up streaming data ingestion application on Amazon EC2 and send the output to Amazon S3 using Kinesis Data Firehose. Use Athena to analyze the data.
  • D. Set up a streaming data ingestion application on Amazon EC2 and connect it to a Hadoop cluster for data processing. Send the output to Amazon S3 and use Amazon Athena to analyze the data.

Answer: A

Explanation:
Explanation
Input - The streaming source for your application. You can select either a Kinesis data stream or a Kinesis Data Firehose data delivery stream as the streaming source. In the input configuration, you map the streaming source to an in-application input stream. The in-application stream is like a continuously updating table upon which you can perform the SELECT and INSERT SQL operations. In your application code, you can create additional in-application streams to store intermediate query result
https://aws.amazon.com/blogs/big-data/writing-sql-on-streaming-data-with-amazon-kinesis-analytics-part-1/


NEW QUESTION # 110
Your company runs a customer facing event registration site This site is built with a 3-tier architecture with web and application tier servers and a MySQL database The application requires 6 web tier servers and 6 application tier servers for normal operation, but can run on a minimum of 65% server capacity and a single MySQL database. When deploying this application in a region with three availability zones (AZs) which architecture provides high availability?

  • A. A web tier deployed across 2 AZs with 3 EC2 (Elastic Compute Cloud) instances in each AZ inside an Auto Scaling Group behind an ELB (elastic load balancer) and an application tier deployed across 2 AZs with 3 EC2 instances m each AZ inside an Auto Scaling Group behind an ELS and a Multi-AZ RDS (Relational Database Service) deployment.
  • B. A web tier deployed across 2 AZs with 3 EC2 (Elastic Compute Cloud) instances in each AZ inside an Auto Scaling Group behind an ELB (elastic load balancer), and an application tier deployed across 2 AZs with 3 EC2 instances in each AZ inside an Auto Scaling Group behind an ELB, and one RDS (Relational Database Service) instance deployed with read replicas in the other AZ.
  • C. A web tier deployed across 3 AZs with 2 EC2 (Elastic Compute Cloud) instances in each AZ inside an Auto Scaling Group behind an ELB (elastic load balancer) and an application tier deployed across 3 AZs with 2 EC2 instances in each AZ inside an Auto Scaling Group behind an ELB and one RDS (Relational Database Service) Instance deployed with read replicas in the two other AZs.
  • D. A web tier deployed across 3 AZs with 2 EC2 (Elastic Compute Cloud) instances in each AZ Inside an Auto Scaling Group behind an ELB (elastic load balancer). And an application tier deployed across 3 AZs with 2 EC2 instances in each AZ inside an Auto Scaling Group behind an ELB. And a Multi-AZ RDS (Relational Database services) deployment.

Answer: D

Explanation:
Amazon RDS Multi-AZ Deployments
Amazon RDS Multi-AZ deployments provide enhanced availability and durability for Database (DB) Instances, making them a natural fit for production database workloads. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Each AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. In case of an infrastructure failure (for example, instance hardware failure, storage failure, or network disruption), Amazon RDS performs an automatic failover to the standby, so that you can resume database operations as soon as the failover is complete. Since the endpoint for your DB Instance remains the same after a failover, your application can resume database operation without the need for manual administrative intervention.
Enhanced Durability
Multi-AZ deployments for the MySQL, Oracle, and PostgreSQL engines utilize synchronous physical replication to keep data on the standby up-to-date with the primary. Multi-AZ deployments for the SQL Server engine use synchronous logical replication to achieve the same result, employing SQL Server-native Mirroring technology. Both approaches safeguard your data in the event of a DB Instance failure or loss of an Availability Zone.
If a storage volume on your primary fails in a Multi-AZ deployment, Amazon RDS automatically initiates a failover to the up-to-date standby. Compare this to a Single-AZ deployment: in case of a Single-AZ database failure, a user-initiated point-in-time-restore operation will be required. This operation can take several hours to complete, and any data updates that occurred after the latest restorable time (typically within the last five minutes) will not be available.
Amazon Aurora employs a highly durable, SSD-backed virtualized storage layer purpose-built for database workloads. Amazon Aurora automatically replicates your volume six ways, across three Availability Zones. Amazon Aurora storage is fault-tolerant, transparently handling the loss of up to two copies of data without affecting database write availability and up to three copies without affecting read availability. Amazon Aurora storage is also self-healing. Data blocks and disks are continuously scanned for errors and replaced automatically.
Increased Availability
You also benefit from enhanced database availability when running Multi-AZ deployments. If an Availability Zone failure or DB Instance failure occurs, your availability impact is limited to the time automatic failover takes to complete: typically under one minute for Amazon Aurora and one to two minutes for other database engines (see the RDS FAQ for details).
The availability benefits of Multi-AZ deployments also extend to planned maintenance and backups. In the case of system upgrades like OS patching or DB Instance scaling, these operations are applied first on the standby, prior to the automatic failover. As a result, your availability impact is, again, only the time required for automatic failover to complete.
Unlike Single-AZ deployments, 1/0 activity is not suspended on your primary during backup for Multi-AZ deployments for the MySQL, Oracle, and PostgreSQL engines, because the backup is taken from the standby. However, note that you may still experience elevated latencies for a few minutes during backups for Multi-AZ deployments.
On instance failure in Amazon Aurora deployments, Amazon RDS uses RDS Multi-AZ technology to automate failover to one of up to 15 Amazon Aurora Replicas you have created in any of three Availability Zones. If no Amazon Aurora Replicas have been provisioned, in the case of a failure, Amazon RDS will attempt to create a new Amazon Aurora DB instance for you automatically.


NEW QUESTION # 111
How can a user track memory usage in an EC2 instance?

  • A. Call Amazon CloudWatch to retrieve the memory usage metric data that exists for the EC2 Instance
  • B. Use an instance type that supports memory usage reporting to a metric by default
  • C. Place en agent on the EC2 instance to push memory usage to an Amazon CloudWatch custom metric.
  • D. Assign an 1AM role to the EC2 instance with an 1AM policy granting access to the desired metric.

Answer: C


NEW QUESTION # 112
Can I move a Reserved Instance from one Region to another?

  • A. Only if they are moving into GovCloud
  • B. No
  • C. Only if they are moving to US East from another region
  • D. Yes

Answer: A


NEW QUESTION # 113
A company has thousands of files stored in an Amazon S3 bucket that has a welldefined access pattern. The files are accessed by an application multiple times a day for the first 30 days. Files are rarely accessed within the next 90 days. After that, the files are never accessed again. During the first 120 days, accessing these files should never take more than a few seconds.
Which lifecycle policy should be used for the S3 objects to minimize costs based on the access pattern?

  • A. Use Amazon S3 Standard-Infrequent Access (S3 Standard-IA) for the first 30 days. After that, move the data to the GLACIER storage class, where is will be deleted automatically.
  • B. Use Amazon S3 Standard storage for the first 30 days. Then move the files to Amazon S3 Standard-Infrequent Access (S3 Standard-IA) for the next 90 days. Allow the data to expire after that.
  • C. Use Amazon S3 Standard-Infrequent Access (S3 Standard-IA) storage for the first 30 days. Then move the files to the GLACIER storage class for the next 90 days. Allow the data to expire after that.
  • D. Use Amazon S3 Standard storage for first 30 days. Then move the files to the GLACIER storage class for the next 90 days. Allow the data to expire after that.

Answer: B


NEW QUESTION # 114
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