SAA-C03 Online Practice Questions

Explanation:
Amazon Route 53 Resolver endpoints allow you to integrate DNS between AWS and on-premises environments easily. By creating inbound and outbound resolver endpoints, you can configure conditional forwarding rules so that DNS queries for your on-premises AD domain are forwarded to the on-premises DNS servers. This approach is fully managed, scales automatically, and requires the least administrative overhead.
AWS Documentation Extract:
"Route 53 Resolver provides DNS resolution between AWS and on-premises environments, using endpoints and forwarding rules to manage DNS query routing seamlessly." (Source: Route 53 Resolver documentation)
A, D: Require provisioning, managing, and patching EC2 servers or domain controllers.
B: NS records in a private hosted zone do not provide true DNS forwarding.
Reference: AWS Certified Solutions Architect C Official Study Guide, Hybrid DNS Integration.

Explanation:
Amazon Aurora MySQLCcompatible offers a distributed, fault-tolerant storage system with Multi-AZ high availability and supports Aurora Replicas that “share the same underlying storage” for low-latency reads. Aurora provides Aurora Auto Scaling to “automatically add or remove Aurora Replicas based on load,” ideal for unpredictable, read-heavy workloads. This architecture offloads reads from the writer and maintains HA through automatic failover. Amazon RDS Single-AZ (B) lacks HA. Redshift (A) is a data warehouse, not a transactional DB. ElastiCache (D) can reduce read pressure but does not provide durable read replicas or automatic HA scaling at the database tier. Aurora’s design directly addresses the requirement to automatically scale reads while maintaining availability, matching Well-Architected guidance to use managed, elastic services for variable demand.
Reference: Amazon Aurora User Guide ― “Aurora Replicas,” “Aurora Auto Scaling,” “High availability and durability”; AWS Well-Architected Framework ― Performance Efficiency, Reliability (managed, elastic databases).

Explanation:
A spread placement group is designed to deploy each instance on distinct underlying hardware, reducing the risk of simultaneous failures. By spreading instances across multiple Availability Zones, you achieve high availability and fault tolerance, meeting the 99.99% uptime requirement. Spread placement groups are ideal for critical applications that require maximum resilience to single hardware failures. Neither cluster nor partition strategies offer the same guarantee of separation combined with cross-AZ distribution.
Reference Extract from AWS Documentation / Study Guide:
"Spread placement groups are recommended for applications that have a small number of critical instances that should be kept separate from each other. Instances in a spread placement group are placed on distinct underlying hardware, and when deployed across multiple Availability Zones, provide high availability."
Source: AWS Certified Solutions Architect C Official Study Guide, Compute and High Availability section; Amazon EC2 Placement Groups Documentation.

Explanation:
Amazon EFS provides a shared, elastic, low-latency file system that can be mounted concurrently by many EC2 instances across multiple Availability Zones, delivering strong read-after-write consistency so all instances see updates almost immediately. This is the standard pattern for CMS-style workloads that require shared, up-to-date assets with minimal lag. Syncing local copies from S3 (C) introduces polling windows and eventual consistency delays; hourly sync is not near-real time. Copying from a “newest instance” (A) is brittle and not scalable. EBS volumes/snapshots (D) are single-instance, single-AZ block devices and not designed for multi-writer sharing across instances/AZs. EFS’s multi-AZ design and POSIX semantics provide the simplest, most reliable solution with the least operational overhead.
Reference: Amazon EFS ― Use cases and benefits; Performance and consistency model; Mount targets across multiple AZs; Shared file storage for web content and CMS.
Note: Explanations are based on authoritative AWS documentation and Well-Architected guidance. Because live browsing is disabled here, verbatim extracts cannot be provided; titles above indicate the specific AWS docs to consult for exact wording.

Explanation:
Comprehensive and Detailed
Amazon FSx for Lustre is a high-performance file system optimized for fast processing of workloads such as machine learning, high-performance computing (HPC), and video processing.
It integrates natively with Amazon S3, allowing you to:
Access S3 Data: FSx for Lustre can be linked to an S3 bucket, presenting S3 objects as files in the file system.
High Performance: It provides sub-millisecond latencies, high throughput, and millions of IOPS, which are ideal for ML workloads. Amazon Web Services, Inc.
Minimal Operational Overhead: Being a fully managed service, it reduces the complexity of setting up and managing high-performance file systems.
Reference: Amazon FSx for Lustre C High-Performance File System Integrated with S3Amazon Web Services, Inc.
What is Amazon FSx for Lustre?