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NEW QUESTION # 103
A company runs containers in a Kubernetes environment in the company's local data center. The company wants to use Amazon Elastic Kubernetes Service (Amazon EKS) and other AWS managed services Data must remain locally in the company's data center and cannot be stored in any remote site or cloud to maintain compliance Which solution will meet these requirements?
Answer: A
Explanation:
AWS Outposts is a fully managed service that delivers AWS infrastructure and services to virtually any on-premises or edge location for a consistent hybrid experience. AWS Outposts supports Amazon EKS, which is a managed service that makes it easy to run Kubernetes on AWS and on-premises. By installing an AWS Outposts rack in the company's data center, the company can run containers in a Kubernetes environment using Amazon EKS and other AWS managed services, while keeping the data locally in the company's data center and meeting the compliance requirements. AWS Outposts also provides a seamless connection to the local AWS Region for access to a broad range of AWS services.
Option A is not a valid solution because AWS Local Zones are not deployed in the company's data center, but in large metropolitan areas closer to end users. AWS Local Zones are owned, managed, and operated by AWS, and they provide low-latency access to the public internet and the local AWS Region. Option B is not a valid solution because AWS Snowmobile is a service that transports exabytes of data to AWS using a 45-foot long ruggedized shipping container pulled by a semi-trailer truck. AWS Snowmobile is not designed for running containers or AWS managed services on-premises, but for large-scale data migration. Option D is not a valid solution because AWS Snowball Edge Storage Optimized is a device that provides 80 TB of HDD or 210 TB of NVMe storage capacity for data transfer and edge computing. AWS Snowball Edge Storage Optimized does not support Amazon EKS or other AWS managed services, and it is not suitable for running containers in a Kubernetes environment.
Reference:
AWS Outposts - Amazon Web Services
Amazon EKS on AWS Outposts - Amazon EKS
AWS Local Zones - Amazon Web Services
AWS Snowmobile - Amazon Web Services
[AWS Snowball Edge Storage Optimized - Amazon Web Services]
NEW QUESTION # 104
[Design Secure Architectures]
A company plans to use an Amazon S3 bucket to archive backup dat
a. Regulations require the company to retain the backup data for 7 years.
During the retention period, the company must prevent users, including administrators, from deleting the data. The company can delete the data after 7 years.
Which solution will meet these requirements?
Answer: A
Explanation:
Comprehensive and Detailed Step-by-Step
The requirement is toprevent data deletion by any user, including administrators, for 7 years while allowing automatic deletion afterward.
S3 Object Lock in Compliance Mode (Correct Choice - C)
Compliance mode ensures that even the root user cannot delete or modify the objects during the retention period.
After 7 years, the S3 Lifecycle policy automatically deletes the objects.
This meets bothimmutability and automatic deletionrequirements.
Governance Mode (Option B - Incorrect)
Governance mode prevents deletion,but administrators can override it.
The requirement explicitly states thateven administrators must not be able to delete the data.
S3 Bucket Policy (Option A - Incorrect)
An S3 bucket policy candeny deletes, but policies can be modified at any time by administrators.
It does not enforce strict retention like Object Lock.
S3 Batch Operations Job (Option D - Incorrect)
A legal hold does not have an automatic expiration.
Legal holds must be manually removed, which is not efficient.
Why Option C is Correct:
S3 Object Lock in Compliance Mode prevents deletion by all users, including administrators.
The S3 Lifecycle policy deletes the data automatically after 7 years, reducing operational overhead.
Reference:
S3 Object Lock Compliance Mode
S3 Lifecycle Policies
NEW QUESTION # 105
A company requires all the data stored in the cloud to be encrypted at rest. To easily integrate this with other AWS services, they must have full control over the encryption of the created keys and also the ability to immediately remove the key material from AWS KMS. The solution should also be able to audit the key usage independently of AWS CloudTrail.
Which of the following options will meet this requirement?
Answer: C
Explanation:
The AWS Key Management Service (KMS) custom key store feature combines the controls provided by AWS CloudHSM with the integration and ease of use of AWS KMS. You can configure your own CloudHSM cluster and authorize AWS KMS to use it as a dedicated key store for your keys rather than the default AWS KMS key store. When you create keys in AWS KMS you can choose to generate the key material in your CloudHSM cluster. CMKs that are generated in your custom key store never leave the HSMs in the CloudHSM cluster in plaintext and all AWS KMS operations that use those keys are only performed in your HSMs.
AWS KMS can help you integrate with other AWS services to encrypt the data that you store in these services and control access to the keys that decrypt it. To immediately remove the key material from AWS KMS, you can use a custom key store. Take note that each custom key store is associated with an AWS CloudHSM cluster in your AWS account. Therefore, when you create an AWS KMS CMK in a custom key store, AWS KMS generates and stores the non-extractable key material for the CMK in an AWS CloudHSM cluster that you own and manage. This is also suitable if you want to be able to audit the usage of all your keys independently of AWS KMS or AWS CloudTrail.
Since you control your AWS CloudHSM cluster, you have the option to manage the lifecycle of your CMKs independently of AWS KMS. There are four reasons why you might find a custom key store useful:
You might have keys that are explicitly required to be protected in a single-tenant HSM or in an HSM over which you have direct control.
You might have keys that are required to be stored in an HSM that has been validated to FIPS 140-2 level 3 overall (the HSMs used in the standard AWS KMS key store are either validated or in the process of being validated to level 2 with level 3 in multiple categories).
You might need the ability to immediately remove key material from AWS KMS and to prove you have done so by independent means.
You might have a requirement to be able to audit all use of your keys independently of AWS KMS or AWS CloudTrail.
Hence, the correct answer in this scenario is: Use AWS Key Management Service to create a CMK in a custom key store and store the non-extractable key material in AWS CloudHSM.
The option that says: Use AWS Key Management Service to create a CMK in a custom key store and store the non-extractable key material in Amazon S3 is incorrect because Amazon S3 is not a suitable storage service to use in storing encryption keys. You have to use AWS CloudHSM instead.
The options that say: Use AWS Key Management Service to create AWS-owned CMKs and store the non-extractable key material in AWS CloudHSM and Use AWS Key Management Service to create AWS- managed CMKs and store the non-extractable key material in AWS CloudHSM are both incorrect because the scenario requires you to have full control over the encryption of the created key. AWS- owned CMKs and AWS-managed CMKs are managed by AWS. Moreover, these options do not allow you to audit the key usage independently of AWS CloudTrail. References:
https://docs.aws.amazon.com/kms/latest/developerguide/custom-key-store-overview.html
https://aws.amazon.com/kms/faqs/
https://aws.amazon.com/blogs/security/are-kms-custom-key-stores-right-for-you/ Check out this AWS KMS Cheat Sheet:
https://tutorialsdojo.com/aws-key-management-service-aws-kms/
NEW QUESTION # 106
A company has an application that uses an Amazon DynamoDB table for storage. A solutions architect discovers that many requests to the table are not returning the latest data. The company's users have not reported any other issues with database performance. Latency is in an acceptable range.
Which design change should the solutions architect recommend?
Answer: A
Explanation:
The most suitable design change for the company's application is to request strongly consistent reads for the table. This change will ensure that the requests to the table return the latest data, reflecting the updates from all prior write operations.
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB supports two types of read consistency: eventually consistent reads and strongly consistent reads. By default, DynamoDB uses eventually consistent reads, unless users specify otherwise1.
Eventually consistent reads are reads that may not reflect the results of a recently completed write operation.
The response might not include the changes because of the latency of propagating the data to all replicas. If users repeat their read request after a short time, the response should return the updated data. Eventually consistent reads are suitable for applications that do not require up-to-date data or can tolerate eventual consistency1.
Strongly consistent reads are reads that return a result that reflects all writes that received a successful response prior to the read. Users can request a strongly consistent read by setting the ConsistentRead parameter to true in their read operations, such as GetItem, Query, or Scan. Strongly consistent reads are suitable for applications that require up-to-date data or cannot tolerate eventual consistency1.
The other options are not correct because they do not address the issue of read consistency or are not relevant for the use case. Adding read replicas to the table is not correct because this option is not supported by DynamoDB. Read replicas are copies of a primary database instance that can serve read-only traffic and improve availability and performance. Read replicas are available for some relational database services, such as Amazon RDS or Amazon Aurora, but not for DynamoDB2. Using a global secondary index (GSI) is not correct because this option is not related to read consistency. A GSI is an index that has a partition key and an optional sort key that are different from those on the base table. A GSI allows users to query the data in different ways, with eventual consistency3. Requesting eventually consistent reads for the table is not correct because this option is already the default behavior of DynamoDB and does not solve the problem of requests not returning the latest data.
References:
Read consistency - Amazon DynamoDB
Working with read replicas - Amazon Relational Database Service
Working with global secondary indexes - Amazon DynamoDB
NEW QUESTION # 107
An ecommerce company is migrating its on-premises workload to the AWS Cloud. The workload currently consists of a web application and a backend Microsoft SQL database for storage.
The company expects a high volume of customers during a promotional event. The new infrastructure in the AWS Cloud must be highly available and scalable.
Which solution will meet these requirements with the LEAST administrative overhead?
Answer: A
Explanation:
To ensure high availability and scalability, the web application should run in anAuto Scaling groupacross two Availability Zones behind anApplication Load Balancer (ALB). The database should be migrated toAmazon RDSwithMulti-AZ deployment, which ensures fault tolerance and automatic failover in case of an AZ failure.
This setup minimizes administrative overhead while meeting the company's requirements for high availability and scalability.
Option A: Read replicas are typically used for scaling read operations, and Multi-AZ provides better availability for a transactional database.
Option B: Replicating across AWS Regions adds unnecessary complexity for a single web application.
Option D: EC2 instances across three Availability Zones add unnecessary complexity for this scenario.
AWS References:
Auto Scaling Groups
Amazon RDS Multi-AZ
NEW QUESTION # 108
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