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A company creates operations data and stores the data in an Amazon S3 bucket for the company's annual audit, an external consultant needs to access an annual report that is stored in the S3 bucket. The external consultant needs to access the report for 7 days.
The company must implement a solution to allow the external consultant access to only the report.
Which solution will meet these requirements with the MOST operational efficiency?
A. Generate a presigned URL that has the required access to the location of the report on the S3 bucket.
Share the presigned URL with the external consultant.
B. Create a new S3 bucket that is configured to host a public static website. Migrate the operations data to the new S3 bucket. Share the S3 website URL with the external consultant.
C. Create a new IAM user that has access to the report in the S3 bucket. Provide the access keys to the external consultant. Revoke the access keys after 7 days.
D. Enable public access to the S3 bucket for 7 days. Remove access to the S3 bucket when the external consultant completes the audit.
Answer: A
Explanation:
Apresigned URLallows temporary access to a specific object in an S3 bucket without needing to make the bucket public or creating and managing additional IAM users. The URL is time-limited, and permissions are granted only to the specific object (in this case, the annual report), making it a highly secure and operationally efficient solution.
With a presigned URL, the consultant can access the report for the specified duration (7 days), after which the URL will expire automatically, removing the need for manual intervention to revoke access.
AWS References:
Amazon S3 Presigned URLsexplain how to generate a presigned URL to grant temporary access to S3 objects.
Best Practices for S3 Securityemphasize using presigned URLs for sharing temporary access to S3 objects securely.
Why the other options are incorrect:
A). Public static website: This approach involves making the S3 bucket publicly accessible, which is unnecessary and insecure for sensitive data.
B). Enable public access: Granting public access to the entire bucket, even temporarily, is a security risk and violates best practices.
C). Create an IAM user: Creating an IAM user and managing credentials is unnecessary overhead and less secure compared to a presigned URL for this short-term need.
NEW QUESTION # 512
A company is designing a new web application that will run on Amazon EC2 Instances. The application will use Amazon DynamoDB for backend data storage. The application traffic will be unpredictable. T company expects that the application read and write throughput to the database will be moderate to high. The company needs to scale in response to application traffic.
Which DynamoDB table configuration will meet these requirements MOST cost-effectively?
A. Configure DynamoDB in on-demand mode by using the DynamoDB Standard Infrequent Access (DynamoDB Standard-IA) table class.
B. Configure DynamoDB with provisioned read and write by using the DynamoDB Standard Infrequent Access (DynamoDB Standard-IA) table class. Set DynamoDB auto scaling to a maximum defined capacity.
C. Configure DynamoDB with provisioned read and write by using the DynamoDB Standard table class.
Set DynamoDB auto scaling to a maximum defined capacity.
D. Configure DynamoDB in on-demand mode by using the DynamoDB Standard table class.
Answer: D
Explanation:
The most cost-effective DynamoDB table configuration for the web application is to configure DynamoDB in on-demand mode by using the DynamoDB Standard table class. This configuration will allow the company to scale in response to application traffic and pay only for the read and write requests that the application performs on the table.
On-demand mode is a flexible billing option that can handle thousands of requests per second without capacity planning. On-demand mode automatically adjusts the table's capacity based on the incoming traffic, and charges only for the read and write requests that are actually performed. On-demand mode is suitable for applications with unpredictable or variable workloads, or applications that prefer the ease of paying for only what they use1.
The DynamoDB Standard table class is the default and recommended table class for most workloads. The DynamoDB Standard table class offers lower throughput costs than the DynamoDB Standard-Infrequent Access (DynamoDB Standard-IA) table class, and is more cost-effective for tables where throughput is the dominant cost. The DynamoDB Standard table class also offers the same performance, durability, and availability as the DynamoDB Standard-IA table class2.
The other options are not correct because they are either not cost-effective or not suitable for the use case.
Configuring DynamoDB with provisioned read and write by using the DynamoDB Standard table class, and setting DynamoDB auto scaling to a maximum defined capacity is not correct because this configuration requires manual estimation and management of the table's capacity, which adds complexity and cost to the solution. Provisioned mode is a billing option that requires users to specify the amount of read and write capacity units for their tables, and charges for the reserved capacity regardless of usage. Provisioned mode is suitable for applications with predictable or stable workloads, or applications that require finer-grained control over their capacity settings1. Configuring DynamoDB with provisioned read and write by using the DynamoDB Standard-Infrequent Access (DynamoDB Standard-IA) table class, and setting DynamoDB auto scaling to a maximum defined capacity is not correct because this configuration is not cost-effective for tables with moderate to high throughput. The DynamoDB Standard-IA table class offers lower storage costs than the DynamoDB Standard table class, but higher throughput costs. The DynamoDB Standard-IA table class is optimized for tables where storage is the dominant cost, such as tables that store infrequently accessed data2.
Configuring DynamoDB in on-demand mode by using the DynamoDB Standard-Infrequent Access (DynamoDB Standard-IA) table class is not correct because this configuration is not cost-effective for tables with moderate to high throughput. As mentioned above, the DynamoDB Standard-IA table class has higher throughput costs than the DynamoDB Standard table class, which can offset the savings from lower storage costs.
References:
Table classes - Amazon DynamoDB
Read/write capacity mode - Amazon DynamoDB
NEW QUESTION # 513
There is a new compliance rule in your company that audits every Windows and Linux EC2 instances each month to view any performance issues. They have more than a hundred EC2 instances running in production, and each must have a logging function that collects various system details regarding that instance. The SysOps team will periodically review these logs and analyze their contents using AWS Analytics tools, and the result will need to be retained in an S3 bucket.
In this scenario, what is the most efficient way to collect and analyze logs from the instances with minimal effort?
A. Install the AWS Systems Manager Agent (SSM Agent) in each instance which will automatically collect and push data to CloudWatch Logs. Analyze the log data with CloudWatch Logs Insights.
B. Install the unified CloudWatch Logs agent in each instance which will automatically collect and push data to CloudWatch Logs. Analyze the log data with CloudWatch Logs Insights.
C. Install AWS Inspector Agent in each instance which will collect and push data to CloudWatch Logs periodically. Set up a CloudWatch dashboard to properly analyze the log data of all instances.
D. Install AWS SDK in each instance and create a custom daemon script that would collect and push data to CloudWatch Logs periodically. Enable CloudWatch detailed monitoring and use CloudWatch Logs Insights to analyze the log data of all instances.
Answer: B
Explanation:
To collect logs from your Amazon EC2 instances and on-premises servers into CloudWatch Logs, AWS offers both a new unified CloudWatch agent, and an older CloudWatch Logs agent. It is recommended to use the unified CloudWatch agent which has the following advantages:
- You can collect both logs and advanced metrics with the installation and configuration of just one agent.
- The unified agent enables the collection of logs from servers running Windows Server.
- If you are using the agent to collect CloudWatch metrics, the unified agent also enables the collection of additional system metrics, for in-guest visibility.
- The unified agent provides better performance.
CloudWatch Logs Insights enables you to interactively search and analyze your log data in Amazon CloudWatch Logs. You can perform queries to help you quickly and effectively respond to operational issues. If an issue occurs, you can use CloudWatch Logs Insights to identify potential causes and validate deployed fixes.
CloudWatch Logs Insights includes a purpose-built query language with a few simple but powerful commands. CloudWatch Logs Insights provides sample queries, command descriptions, query autocompletion, and log field discovery to help you get started quickly. Sample queries are included for several types of AWS service logs.
The option that says: Install AWS SDK in each instance and create a custom daemon script that would collect and push data to CloudWatch Logs periodically. Enable CloudWatch detailed monitoring and use CloudWatch Logs Insights to analyze the log data of all instances is incorrect. Although this is a valid solution, this entails a lot of effort to implement as you have to allocate time to install the AWS SDK to each instance and develop a custom monitoring solution. Remember that the question is specifically looking for a solution that can be implemented with minimal effort. In addition, it is unnecessary and not cost-efficient to enable detailed monitoring in CloudWatch in order to meet the requirements of this scenario since this can be done using CloudWatch Logs.
The option that says: Install the AWS Systems Manager Agent (SSM Agent) in each instance which will automatically collect and push data to CloudWatch Logs. Analyze the log data with CloudWatch Logs Insights is incorrect. Although this is also a valid solution, it is more efficient to use CloudWatch agent than an SSM agent. Manually connecting to an instance to view log files and troubleshoot an issue with SSM Agent is time-consuming hence, for more efficient instance monitoring, you can use the CloudWatch Agent instead to send the log data to Amazon CloudWatch Logs.
The option that says: Install AWS Inspector Agent in each instance which will collect and push data to CloudWatch Logs periodically. Set up a CloudWatch dashboard to properly analyze the log data of all instances is incorrect because AWS Inspector is simply a security assessments service which only helps you in checking for unintended network accessibility of your EC2 instances and for vulnerabilities on those EC2 instances. Furthermore, setting up an Amazon CloudWatch dashboard is not suitable since its primarily used for scenarios where you have to monitor your resources in a single view, even those resources that are spread across different AWS Regions. It is better to use CloudWatch Logs Insights instead since it enables you to interactively search and analyze your log data. References: https://docs.aws.amazon.com/Amaz ... CloudWatchLogs.html https://docs.aws.amazon.com/syst ... ring-ssm-agent.html https://docs.aws.amazon.com/Amaz ... alyzingLogData.html Amazon CloudWatch Overview: https://www.youtube.com/watch?v=q0DmxfyGkeU
Check out this Amazon CloudWatch Cheat Sheet: https://tutorialsdojo.com/amazon-cloudwatch/
CloudWatch Agent vs SSM Agent vs Custom Daemon Scripts: https://tutorialsdojo.com/cloudw ... tom-daemon-scripts/
NEW QUESTION # 514
A company has 5 TB of datasets. The datasets consist of 1 million user profiles and 10 million connections.
The user profiles have connections as many-to-many relationships. The company needs a performance- efficient way to find mutual connections up to five levels.
Which solution will meet these requirements?
A. Use Amazon RDS to store the datasets with multiple tables. Perform SQL JOIN queries to find connections.
B. Use Amazon Neptune to store the datasets with edges and vertices. Query the data to find connections.
C. Use an Amazon S3 bucket to store the datasets. Use Amazon Athena to perform SQL JOIN queries to find connections.
D. Use an Amazon S3 bucket to store the datasets. Use Amazon QuickSight to visualize connections.
Answer: B
Explanation:
Amazon Neptune is a fully managed graph database service optimized for storing and navigating complex many-to-many relationships like social graphs or network topologies.
It supports Gremlin and openCypher queries that allow efficient traversal of connections even multiple levels deep. SQL JOINs (Athena or RDS) are inefficient for deep relationship queries due to exponential complexity.
QuickSight is used for data visualization, not graph traversal.
NEW QUESTION # 515
A solutions architect has created two IAM policies: Policy1 and Policy2. Both policies are attached to an IAM group.
A cloud engineer is added as an IAM user to the IAM group. Which action will the cloud engineer be able to perform?
NEW QUESTION # 516
......
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