A developer is building an application that stores objects in an Amazon S3 bucket. The bucket does not have versioning enabled. The objects are accessed rarely after 1 week. However, the objects must be immediately available at all times. The developer wants to optimize storage costs for the S3 bucket.
Which solution will meet this requirement?
Comprehensive Detailed and Lengthy Step-by-Step Explanation with All AWS Developer Reference:
1. Understanding the Use Case:
The goal is to store objects in an S3 bucket while optimizing storage costs. The key conditions are:
Objects are accessed infrequently after 1 week.
Objects must remain immediately accessible at all times.
2. AWS S3 Storage Classes Overview:
Amazon S3 offers various storage classes, each optimized for specific use cases:
S3 Standard: Best for frequently accessed data with low latency and high throughput needs.
S3 Standard-Infrequent Access (S3 Standard-IA): Optimized for infrequently accessed data but requires the same availability and immediate access as Standard storage. It provides lower storage costs but incurs retrieval charges.
S3 Glacier Flexible Retrieval (formerly S3 Glacier): Designed for archival data with retrieval latency ranging from minutes to hours. This does not meet the requirement for 'immediate access.'
S3 Glacier Deep Archive: Lowest-cost storage, suitable for rarely accessed data with retrieval times of hours.
3. Explanation of the Options:
Option A:
'Create an S3 Lifecycle rule to expire objects after 7 days.'
Expiring objects after 7 days deletes them permanently, which does not fulfill the requirement of retaining the objects for later infrequent access.
Option B:
'Create an S3 Lifecycle rule to transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 7 days.'
This is the correct solution. S3 Standard-IA is ideal for objects accessed infrequently but still need to be available immediately. Transitioning objects to this storage class reduces storage costs while maintaining availability and low latency.
Option C:
'Create an S3 Lifecycle rule to transition objects to S3 Glacier Flexible Retrieval after 7 days.'
S3 Glacier Flexible Retrieval is a low-cost archival solution. However, it does not provide immediate access as retrieval requires minutes to hours. This option does not meet the requirement.
Option D:
'Create an S3 Lifecycle rule to delete objects that have delete markers.'
This option is irrelevant to the given use case, as it addresses versioning cleanup, which is not enabled in the described S3 bucket.
4. Implementation Steps for Option B:
To transition objects to S3 Standard-IA after 7 days:
Navigate to the S3 Console:
Sign in to the AWS Management Console and open the S3 service.
Select the Target Bucket:
Choose the bucket where the objects are stored.
Set Up a Lifecycle Rule:
Go to the Management tab.
Under Lifecycle Rules, click Create lifecycle rule.
Define the Rule Name and Scope:
Provide a descriptive name for the rule.
Specify whether the rule applies to the entire bucket or a subset of objects (using a prefix or tag filter).
Configure Transitions:
Choose Add transition.
Specify that objects should transition to S3 Standard-IA after 7 days.
Review and Save the Rule:
Review the rule configuration and click Save.
5. Cost Optimization Benefits:
Transitioning to S3 Standard-IA results in cost savings as it offers:
Lower storage costs compared to S3 Standard.
Immediate access to objects when required.
However, remember that there is a retrieval cost associated with S3 Standard-IA, so it is best suited for data with low retrieval frequency.
A banking company is building an application for users to create accounts, view balances, and review recent transactions. The company integrated an Amazon API Gateway REST API with AWS Lambda functions. The company wants to deploy a new version of a Lambda function that gives customers the ability to view their balances. The new version of the function displays customer transaction insights. The company wants to test the new version with a small group of users before deciding whether to make the feature available for all users. Which solution will meet these requirements with the LEAST disruption to users?
API Gateway's canary deployments allow gradual traffic shifting to a new version of a function, minimizing disruption while testing.
Why Option A is Correct:
Gradual Rollout: Reduces risk by incrementally increasing traffic.
Rollback Support: Canary deployments make it easy to revert to the previous version.
Why Not Other Options:
Option B: Redeploying the stage disrupts all users.
Option C & D: Managing new stages and weighted routing introduces unnecessary complexity.
A developer is receiving an intermittent ProvisionedThroughputExceededException error from an application that is based on Amazon DynamoDB. According to the Amazon CloudWatch metrics for the table, the application is not exceeding the provisioned throughput. What could be the cause of the issue?
DynamoDB distributes throughput across partitions based on the hash key. A hot partition (caused by high usage of a specific hash key) can result in a ProvisionedThroughputExceededException, even if overall usage is below the provisioned capacity.
Why Option B is Correct:
Partition-Level Limits: Each partition has a limit of 3,000 read capacity units or 1,000 write capacity units per second.
Hot Partition: Excessive use of a single hash key can overwhelm its partition.
Why Not Other Options:
Option A: DynamoDB storage size does not affect throughput.
Option C: Provisioned scaling operations are unrelated to throughput errors.
Option D: Sort keys do not impact partition-level throughput.
A developer is using AWS CodeDeploy to launch an application onto Amazon EC2 instances. The application deployment fails during testing. The developer notices an IAM_ROLE_PERMISSIONS error code in Amazon CloudWatch logs.
What should the developer do to resolve the error?
In a move toward using microservices, a company's management team has asked all development teams to build their services so that API requests depend only on that service's data store. One team is building a Payments service which has its own database; the service needs data that originates in the Accounts database. Both are using Amazon DynamoDB.
What approach will result in the simplest, decoupled, and reliable method to get near-real time updates from the Accounts database?
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