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1). What are the key factors to consider when choosing between S3 Standard, S3 Infrequent Access (IA), and Glacier storage classes for a specific use case??
A) Data access frequency, object size, and cost sensitivity.
B) Data durability, availability, and performance requirements.
C) Data encryption, compression, and retention policies.
D) Data replication, consistency, and scalability.
2). Explain the concept of S3 lifecycle management policies and how to optimize storage costs using them.?
A) Automatically transitioning objects between storage classes based on age or access patterns.
B) Deleting objects after a specified retention period.
C) Compressing objects to reduce storage costs.
D) Encrypting objects to protect data.
3). Describe the best practices for implementing data versioning in S3 to balance durability and cost-efficiency.?
A) Enabling versioning for all objects.
B) Disabling versioning for frequently accessed objects.
C) Using lifecycle policies to manage object versions.
D) All of the above.
4). What are the key considerations for designing a highly available and scalable S3-based architecture for a big data application??
A) Data partitioning, replication, and fault tolerance.
B) High throughput, low latency, and consistent hashing.
C) Data compression, encryption, and access control.
D) All of the above.
5). Explain the difference between S3 eventual consistency and strong consistency, and provide use cases for each.?
A) Eventual consistency for read-after-write consistency, strong consistency for immediate consistency.
B) Eventual consistency for high performance, strong consistency for high accuracy.
C) Eventual consistency for large datasets, strong consistency for small datasets.
D) Eventual consistency for cold storage, strong consistency for hot storage.
6). Describe the challenges of using S3 for large-scale object storage and how to address them.?
A) Data management, performance optimization, and cost control.
B) Data security, compliance, and disaster recovery.
C) Data migration, integration, and transformation.
D) All of the above.
7). How can you optimize S3 performance for serving dynamic web content??
A) Using CloudFront as a CDN.
B) Enabling S3 CORS.
C) Leveraging ETags for caching.
D) All of the above.
8). Explain the concept of S3 Intelligent-Tiering storage class and its use cases.?
A) Automatically transitions objects between access patterns.
B) Provides the lowest cost storage option.
C) Is suitable for all types of data.
D) Offers the highest performance.
9). Describe the best practices for implementing data encryption at rest and in transit for sensitive data in S3.?
A) Using S3 Server-Side Encryption (SSE) with KMS.
B) Using client-side encryption with AWS KMS.
C) Combining SSE-S3 and SSE-KMS for maximum security.
D) All of the above.
10). How can you optimize S3 storage costs for a large-scale data lake with varying data access patterns??
A) Using lifecycle management policies.
B) Implementing data tiering strategies.
C) Leveraging compression and deduplication.
D) All of the above.
11). What are the key considerations for migrating large datasets to S3 from on-premises storage or other cloud storage providers??
A) Data format, size, and transfer speed.
B) Data validation, consistency, and security.
C) Cost optimization and performance tuning.
D) All of the above.
12). How can you implement data governance and compliance for data stored in S3??
A) Using S3 access controls, encryption, and versioning.
B) Integrating with AWS Identity and Access Management (IAM).
C) Leveraging AWS CloudTrail for auditing and monitoring.
D) All of the above.
13). Explain the concept of S3 Inventory and its use cases.?
A) Creates an inventory of objects in an S3 bucket.
B) Optimizes object storage costs.
C) Encrypts objects at rest.
D) Accelerates object retrieval.
14). How can you optimize S3 performance for serving large video files??
A) Using S3 Transfer Acceleration.
B) Enabling S3 CORS.
C) Leveraging CloudFront with origin shields.
D) All of the above.
15). Describe the challenges of using S3 for real-time data processing and how to address them.?
A) High latency, low throughput, and data consistency issues.
B) Using S3 as a data lake for batch processing.
C) Integrating S3 with real-time data processing services like Kinesis.
D) All of the above.
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