Amazon Web Services udemy selected Sap-c02 Aws Certified Professional Questions Answers by Zayne q42 vce pdf

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Exam Name:	AWS Certified Solutions Architect - Professional
Exam Code:	SAP-C02 Dumps
Vendor:	Amazon Web Services	Certification:	AWS Certified Professional
Questions:	625 Q&A's	Shared By:	zayne

Question 136

An AWS partner company is building a service in AWS Organizations using Its organization named org. This service requires the partner company to have access to AWS resources in a customer account, which is in a separate organization named org2 The company must establish least privilege security access using an API or command line tool to the customer account

What is the MOST secure way to allow org1 to access resources h org2?

Options:

The customer should provide the partner company with their AWS account access keys to log inand perform the required tasks

The customer should create an IAM user and assign the required permissions to the IAM user The customer should then provide the credentials to the partner company to log In and perform the required tasks.

The customer should create an IAM role and assign the required permissions to the IAM role. The partner company should then use the IAM rote's Amazon Resource Name (ARN) when requesting access to perform the required tasks

The customer should create an IAM rote and assign the required permissions to the IAM rote. The partner company should then use the IAM rote's Amazon Resource Name (ARN). Including the external ID in the IAM role's trust pokey, when requesting access to perform the required tasks

Discussion

Question 137

An online survey company runs its application in the AWS Cloud. The application is distributed and consists of microservices that run in an automatically scaled Amazon Elastic Container Service (Amazon ECS) cluster. The ECS cluster is a target for an Application Load Balancer (ALB). The ALB is a custom origin for an Amazon CloudFront distribution.

The company has a survey that contains sensitive data. The sensitive data must be encrypted when it moves through the application. The application's data-handling microservice is the only microservice that should be able to decrypt the data.

Which solution will meet these requirements?

Options:

Create a symmetric AWS Key Management Service (AWS KMS) key that is dedicated to the data-handling microservice. Create a field-level encryption profile and a configuration. Associate the KMS key and the configuration with the CloudFront cache behavior.

Create an RSA key pair that is dedicated to the data-handling microservice. Upload the public key to the CloudFront distribution. Create a field-level encryption profile and a configuration. Add the configuration to the CloudFront cache behavior.

Create a symmetric AWS Key Management Service (AWS KMS) key that is dedicated to the data-handling microservice. Create a Lambda@Edge function. Program the function to use the KMS key to encrypt the sensitive data.

Create an RSA key pair that is dedicated to the data-handling microservice. Create a Lambda@Edge function. Program the function to use the private key of the RSA key pair to encrypt the sensitive data.

Discussion

Question 138

A company uses an Amazon Redshift cluster to ingest data from various sources. The data is shared with other internal applications for analysis and reporting.

The cluster has eight ra3.4xlarge nodes. Data ingestion runs daily from midnight to 8 AM and takes 3 hours. The cluster has 85% average CPU utilization during ingestion. The cluster uses on-demand node pricing and is paused outside of the 8-hour daily ingestion window. Snapshots are enabled on the cluster.

The company wants to optimize this workload to reduce costs.

Which solution will meet these requirements?

Options:

Create a new Redshift cluster with eight ra3.4xlarge nodes in concurrency scaling mode by using the most recent snapshot from the existing cluster. Modify the internal applications to retrieve data from the new Redshift cluster. Shut down the existing Redshift cluster. Purchase eight 1-year All Upfront Redshift reserved nodes.

Create a new Redshift cluster with six ra3.16xlarge nodes by using the most recent snapshot from the existing cluster. Enable auto scaling. Modify the internal applications to retrieve data from the new Redshift cluster. Shut down the existing Redshift cluster.

Create a new Redshift Serverless endpoint with 64 Redshift Processing Units (RPUs) by using the most recent snapshot from the existing Redshift cluster. Update the internal applications to retrieve data from the new Redshift Serverless endpoint. Delete the existing Redshift cluster.

Configure Redshift Spectrum on the existing Redshift cluster. Set up IAM permissions to allow Redshift Spectrum to access Amazon S3. Unload data from the existing cluster to an S3 bucket. Update the internal applications to query the S3 data.

Discussion

Answer:

Explanation:

The current Redshift configuration uses eight ra3.4xlarge nodes with on-demand pricing and is paused outside an 8-hour daily window. The ingestion workload runs only 3 hours per day and has about 85% CPU utilization during ingestion, which indicates that the existing node size and count are adequate for performance. The main opportunity is cost optimization for a workload that is time-bound and does not require a continuously running provisioned cluster.

Amazon Redshift Serverless is designed for such intermittent or variable workloads. With Redshift Serverless, you configure compute capacity in terms of Redshift Processing Units (RPUs) and pay per use based on the RPU-hours consumed when queries and data ingestion jobs are actually running. When there is no activity, there is no compute charge. Redshift Serverless can also be created from an existing provisioned Redshift snapshot, allowing an easy migration path from a node-based cluster to a serverless endpoint without re-ingesting or manually moving data.

Option C creates a new Redshift Serverless endpoint with 64 RPUs from the most recent snapshot. This takes advantage of snapshots that already exist on the current cluster. The internal applications are then updated to read from the new serverless endpoint, and the existing cluster is deleted to stop incurring node-based charges. For a workload that runs only a few hours per day, moving to serverless compute is usually more cost-effective than maintaining a provisioned cluster, even if that cluster is paused outside the ingestion window, because serverless eliminates the need to manage cluster sizing and pausing and optimizes billing around actual usage.

Option A proposes staying on provisioned RA3 nodes and additionally purchasing 1-year Reserved Nodes. Reserved Nodes apply discount to node hours whether or not the cluster is paused or fully utilized, and they are designed to be cost-effective for steady, predictable, long-running workloads. For an 8-hour-per-day workload, especially with only 3 hours of intensive ingestion, Reserved Nodes are likely to be less cost-optimal than an on-demand, usage-based serverless model. Also, concurrency scaling is primarily for handling bursty query concurrency, not for cost reduction of a regular ingestion workload.

Option B replaces the existing eight ra3.4xlarge nodes with six ra3.16xlarge nodes and enables auto scaling. ra3.16xlarge provides significantly more capacity per node and is generally more expensive. The original workload already runs at acceptable utilization (about 85% during ingestion), so scaling up to larger nodes is not necessary for performance. Adding auto scaling on top of this likely increases costs and complexity without a clear benefit for a predictable, time-bound daily ingestion pattern.

Option D uses Redshift Spectrum and unloads data from the cluster to Amazon S3 for querying. Redshift Spectrum allows querying data stored in S3 using external tables from within a Redshift cluster, and is charged per amount of data scanned. However, the option still depends on maintaining a Redshift cluster and does not fundamentally optimize the compute cost of the ingestion workload. It also changes query patterns and data access architecture for the internal applications and may increase query cost if large volumes of S3 data are scanned by Spectrum.

Therefore, using Redshift Serverless created from the existing snapshot and paying only for compute usage during ingestion and queries, as described in option C, is the best way to optimize cost for this specific workload pattern.

[References:AWS documentation for Amazon Redshift Serverless concepts such as RPU-based pricing, using snapshots from provisioned clusters to create serverless workgroups, and cost optimization guidance for intermittent and spiky analytics workloads.AWS guidance on reserved node usage and suitability for steady-state provisioned Redshift clusters.AWS descriptions of Amazon Redshift Spectrum and its pricing and use cases for querying data directly in Amazon S3.]

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Question 139

A company needs to implement a patching process for its servers. The on-premises servers and Amazon EC2 instances use a variety of tools to perform patching. Management requires a single report showing the patch status of all the servers and instances.

Which set of actions should a solutions architect take to meet these requirements?

Options:

Use AWS Systems Manager to manage patches on the on-premises servers and EC2 instances. Use Systems Manager to generate patch compliance reports.

Use AWS OpsWorks to manage patches on the on-premises servers and EC2 instances. Use Amazon OuickSight integration with OpsWorks to generate patch compliance reports.

Use an Amazon EventBridge (Amazon CloudWatch Events) rule to apply patches by scheduling an AWS Systems Manager patch remediation job. Use Amazon Inspector to generate patch compliance reports.

Use AWS OpsWorks to manage patches on the on-premises servers and EC2 instances. Use AWS X-Ray to post the patch status to AWS Systems Manager OpsCenter to generate patch compliance reports.