Topic 4: Exam Pool D
A company deployed a serverless application that uses Amazon DynamoDB as a database layer The application has experienced a large increase in users. The company wants to improve database response time from milliseconds to microseconds and to cache requests to the database. Which solution will meet these requirements with the LEAST operational overhead?
A. Use DynamoDB Accelerator (DAX).
B. Migrate the database to Amazon Redshift.
C. Migrate the database to Amazon RDS.
D. Use Amazon ElastiCache for Redis.
Explanation: DynamoDB Accelerator (DAX) is a fully managed, highly available caching service built for Amazon DynamoDB. DAX delivers up to a 10 times performance improvement—from milliseconds to microseconds—even at millions of requests per second. DAX does all the heavy lifting required to add in-memory acceleration to your DynamoDB tables, without requiring developers to manage cache invalidation, data population, or cluster management. Now you can focus on building great applications for your customers without worrying about performance at scale. You do not need to modify application logic because DAX is compatible with existing DynamoDB API calls. This solution will meet the requirements with the least operational overhead, as it does not require any code development or manual intervention.
A gaming company hosts a browser-based application on AWS. The users of the application consume a large number of videos and images that are stored in Amazon S3. This content is the same for all users.
The application has increased in popularity, and millions of users worldwide are accessing these media files. The company wants to provide the files to the users while reducing the load on the origin.
Which solution meets these requirements MOST cost-effectively?
A. Deploy an AWS Global Accelerator accelerator in front of the web servers.
B. Deploy an Amazon CloudFront web distribution in front of the S3 bucket.
C. Deploy an Amazon ElastiCache for Redis instance in front of the web servers.
D. Deploy an Amazon ElastiCache for Memcached instance in front of the web servers.
Explanation: ElastiCache, enhances the performance of web applications by quickly retrieving information from fully-managed in-memory data stores. It utilizes Memcached and Redis, and manages to considerably reduce the time your applications would, otherwise, take to read data from disk-based databases. Amazon CloudFront supports dynamic content from HTTP and WebSocket protocols, which are based on the Transmission Control Protocol (TCP) protocol. Common use cases include dynamic API calls, web pages and web applications, as well as an application's static files such as audio and images. It also supports on-demand media streaming over HTTP. AWS Global Accelerator supports both User Datagram Protocol (UDP) and TCP-based protocols. It is commonly used for non- HTTP use cases, such as gaming, IoT and voice over IP. It is also good for HTTP use cases that need static IP addresses or fast regional failover
A company has an ecommerce checkout workflow that writes an order to a database and calls a service to process the payment. Users are experiencing timeouts during the checkout process. When users resubmit the checkout form, multiple unique orders are created for the same desired transaction.
How should a solutions architect refactor this workflow to prevent the creation of multiple orders?
A. Configure the web application to send an order message to Amazon Kinesis Data Firehose. Set the payment service to retrieve the message from Kinesis Data Firehose and process the order.
B. Create a rule in AWS CloudTrail to invoke an AWS Lambda function based on the logged application path request Use Lambda to query the database, call the payment service, and pass in the order information.
C. Store the order in the database. Send a message that includes the order number to Amazon Simple Notification Service (Amazon SNS). Set the payment service to poll Amazon SNS. retrieve the message, and process the order.
D. Store the order in the database. Send a message that includes the order number to an Amazon Simple Queue Service (Amazon SQS) FIFO queue. Set the payment service to retrieve the message and process the order. Delete the message from the queue.
Explanation: This approach ensures that the order creation and payment processing steps are separate and atomic. By sending the order information to an SQS FIFO queue, the payment service can process the order one at a time and in the order they were received. If the payment service is unable to process an order, it can be retried later, preventing the creation of multiple orders. The deletion of the message from the queue after it is processed will prevent the same message from being processed multiple times.
A company is planning to use an Amazon DynamoDB table for data storage. The company is concerned about cost optimization. The table will not be used on most mornings. In the evenings, the read and write traffic will often be unpredictable. When traffic spikes occur, they will happen very quickly. What should a solutions architect recommend?
A. Create a DynamoDB table in on-demand capacity mode.
B. Create a DynamoDB table with a global secondary index
C. Create a DynamoDB table with provisioned capacity and auto scaling.
D. Create a DynamoDB table in provisioned capacity mode, and configure it as a global table
Explanation: Provisioned capacity is best if you have relatively predictable application traffic, run applications whose traffic is consistent, and ramps up or down gradually. Ondemand capacity mode is best when you have unknown workloads, unpredictable application traffic and also if you only want to pay exactly for what you use. The on-demand pricing model is ideal for bursty, new, or unpredictable workloads whose traffic can spike in seconds or minutes, and when under-provisioned capacity would impact the user experience.
A company is running several business applications in three separate VPCs within me us- east-1 Region. The applications must be able to communicate between VPCs. The applications also must be able to consistently send hundreds to gigabytes of data each day to a latency-sensitive application that runs in a single on-premises data center.
A solutions architect needs to design a network connectivity solution that maximizes cost- effectiveness
Which solution moots those requirements?
A. Configure three AWS Site-to-Site VPN connections from the data center to AWS Establish connectivity by configuring one VPN connection for each VPC
B. Launch a third-party virtual network appliance in each VPC Establish an iPsec VPN tunnel between the Data center and each virtual appliance
C. Set up three AWS Direct Connect connections from the data center to a Direct Connect gateway in us-east-1 Establish connectivity by configuring each VPC to use one of the Direct Connect connections
D. Set up one AWS Direct Connect connection from the data center to AWS. Create a transit gateway, and attach each VPC to the transit gateway. Establish connectivity between the Direct Connect connection and the transit gateway.
A serverless application uses Amazon API Gateway. AWS Lambda, and Amazon DynamoDB. The Lambda function needs permissions to read and write to the DynamoDB table. Which solution will give the Lambda function access to the DynamoDB table MOST securely?
A. Create an 1AM user with programmatic access to the Lambda function. Attach a policy to the user that allows read and write access to the DynamoDB table. Store the access_key_id and secret_access_key parameters as part of the Lambda environment variables. Ensure that other AWS users do not have read and write access to the Lambda function configuration
B. Create an 1AM role that includes Lambda as a trusted service. Attach a policy to the role that allows read and write access to the DynamoDB table. Update the configuration of the Lambda function to use the new role as the execution role.
C. Create an 1AM user with programmatic access to the Lambda function. Attach a policy to the user that allows read and write access to the DynamoDB table. Store the access_key_id and secret_access_key parameters in AWS Systems Manager Parameter Store as secure string parameters. Update the Lambda function code to retrieve the secure string parameters before connecting to the DynamoDB table.
D. Create an 1AM role that includes DynamoDB as a trusted service. Attach a policy to the role that allows read and write access from the Lambda function. Update the code of the Lambda function to attach to the new role as an execution role.
Explanation: Option B suggests creating an IAM role that includes Lambda as a trusted service, meaning the role is specifically designed for Lambda functions. The role should have a policy attached to it that grants the required read and write access to the DynamoDB table.
A company has a nightly batch processing routine that analyzes report files that an onpremises file system receives daily through SFTP. The company wants to move the solution to the AWS Cloud. The solution must be highly available and resilient. The solution also must minimize operational effort. Which solution meets these requirements?
A. Deploy AWS Transfer for SFTP and an Amazon Elastic File System (Amazon EFS) file system for storage. Use an Amazon EC2 instance in an Auto Scaling group with a scheduled scaling policy to run the batch operation.
B. Deploy an Amazon EC2 instance that runs Linux and an SFTP service. Use an Amazon Elastic Block Store {Amazon EBS) volume for storage. Use an Auto Scaling group with the minimum number of instances and desired number of instances set to 1.
C. Deploy an Amazon EC2 instance that runs Linux and an SFTP service. Use an Amazon Elastic File System (Amazon EFS) file system for storage. Use an Auto Scaling group with the minimum number of instances and desired number of instances set to 1.
D. Deploy AWS Transfer for SFTP and an Amazon S3 bucket for storage. Modify the application to pull the batch files from Amazon S3 to an Amazon EC2 instance for processing. Use an EC2 instance in an Auto Scaling group with a scheduled scaling policy to run the batch operation.
Explanation: The solution that meets the requirements of high availability, performance, security, and static IP addresses is to use Amazon CloudFront, Application Load Balancers (ALBs), Amazon Route 53, and AWS WAF. This solution allows the company to distribute its HTTP-based application globally using CloudFront, which is a content delivery network (CDN) service that caches content at edge locations and provides static IP addresses for each edge location. The company can also use Route 53 latency-based routing to route requests to the closest ALB in each Region, which balances the load across the EC2 instances. The company can also deploy AWS WAF on the CloudFront distribution to protect the application against common web exploits by creating rules that allow, block, or count web requests based on conditions that are defined. The other solutions do not meet all the requirements because they either use Network Load Balancers (NLBs), which do not support HTTP-based applications, or they do not use CloudFront, which provides better performance and security than AWS Global Accelerator.
A reporting team receives files each day in an Amazon S3 bucket. The reporting team manually reviews and copies the files from this initial S3 bucket to an analysis S3 bucket each day at the same time to use with Amazon QuickSight. Additional teams are starting to send more files in larger sizes to the initial S3 bucket.
The reporting team wants to move the files automatically analysis S3 bucket as the files enter the initial S3 bucket. The reporting team also wants to use AWS Lambda functions to run pattern-matching code on the copied data. In addition, the reporting team wants to send the data files to a pipeline in Amazon SageMaker Pipelines.
What should a solutions architect do to meet these requirements with the LEAST operational overhead?
A. Create a Lambda function to copy the files to the analysis S3 bucket. Create an S3 event notification for the analysis S3 bucket. Configure Lambda and SageMaker Pipelines as destinations of the event notification. Configure s30bjectCreated:Put as the event type.
B. Create a Lambda function to copy the files to the analysis S3 bucket. Configure the analysis S3 bucket to send event notifications to Amazon EventBridge (Amazon CloudWatch Events). Configure an ObjectCreated rule in EventBridge (CloudWatch Events). Configure Lambda and SageMaker Pipelines as targets for the rule.
C. Configure S3 replication between the S3 buckets. Create an S3 event notification for the analysis S3 bucket. Configure Lambda and SageMaker Pipelines as destinations of the event notification. Configure s30bjectCreated:Put as the event type.
D. Configure S3 replication between the S3 buckets. Configure the analysis S3 bucket to send event notifications to Amazon EventBridge (Amazon CloudWatch Events). Configure an ObjectCreated rule in EventBridge (CloudWatch Events). Configure Lambda and SageMaker Pipelines as targets for the rule.
Explanation:
This solution meets the requirements of moving the files automatically, running Lambda functions on the copied data, and sending the data files to SageMaker Pipelines with the least operational overhead. S3 replication can copy the files from the initial S3 bucket to the analysis S3 bucket as they arrive. The analysis S3 bucket can send event notifications to Amazon EventBridge (Amazon CloudWatch Events) when an object is created.
EventBridge can trigger Lambda and SageMaker Pipelines as targets for the ObjectCreated rule. Lambda can run pattern-matching code on the copied data, and SageMaker Pipelines can execute a pipeline with the data files.
Option A is incorrect because creating a Lambda function to copy the files to the analysis S3 bucket is not necessary when S3 replication can do that automatically. It also adds operational overhead to manage the Lambda function. Option B is incorrect because creating a Lambda function to copy the files to the analysis S3 bucket is not necessary when S3 replication can do that automatically. It also adds operational overhead to manage the Lambda function. Option C is incorrect because using S3 event notification with multiple destinations can result in throttling or delivery failures if there are too many events.
A company offers a food delivery service that is growing rapidly. Because of the growth, the
company’s order processing system is experiencing scaling problems during peak traffic
hours. The current architecture includes the following:
A. Use Amazon CloudWatch metrics to monitor the CPU of each instance in the Auto Scaling groups. Configure each Auto Scaling group’s minimum capacity according to peak workload values.
B. Use Amazon CloudWatch metrics to monitor the CPU of each instance in the Auto Scaling groups. Configure a CloudWatch alarm to invoke an Amazon Simple Notification Service (Amazon SNS) topic that creates additional Auto Scaling groups on demand.
C. Provision two Amazon Simple Queue Service (Amazon SQS) queues: one for order collection and another for order fulfillment. Configure the EC2 instances to poll their respective queue. Scale the Auto Scaling groups based on notifications that the queues send.
D. Provision two Amazon Simple Queue Service (Amazon SQS) queues: one for order collection and another for order fulfillment. Configure the EC2 instances to poll their respective queue. Create a metric based on a backlog per instance calculation. Scale the Auto Scaling groups based on this metric.
Explanation: The number of instances in your Auto Scaling group can be driven by how long it takes to process a message and the acceptable amount of latency (queue delay). The solution is to use a backlog per instance metric with the target value being the acceptable backlog per instance to maintain.
A company wants to measure the effectiveness of its recent marketing campaigns. The company performs batch processing on csv files of sales data and stores the results in an Amazon S3 bucket once every hour. The S3 bi petabytes of objects. The company runs one-time queries in Amazon Athena to determine which products are most popular on a particular date for a particular region Queries sometimes fail or take longer than expected to finish.
Which actions should a solutions architect take to improve the query performance and reliability? (Select TWO.)
A. Reduce the S3 object sizes to less than 126 MB
B. Partition the data by date and region n Amazon S3
C. Store the files as large, single objects in Amazon S3.
D. Use Amazon Kinosis Data Analytics to run the Queries as pan of the batch processing operation
E. Use an AWS duo extract, transform, and load (ETL) process to convert the csv files into Apache Parquet format.
Explanation: This solution meets the requirements of measuring the effectiveness of marketing campaigns by performing batch processing on csv files of sales data and storing the results in an Amazon S3 bucket once every hour. An AWS duo ETL process can use services such as AWS Glue or AWS Data Pipeline to extract data from S3, transform it into a more efficient format such as Apache Parquet, and load it back into S3. Apache Parquet is a columnar storage format that can improve the query performance and reliability of Athena by reducing the amount of data scanned, improving compression ratio, and enabling predicate pushdown.
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