AWS Certified Solutions Architect Associate Practice Test (SAA-C03)

AWS Organizations enables you to centrally govern and manage your environment as you grow and scale your workloads on AWS. It allows you to group accounts into Organizational Units (OU), and apply Service Control Policies (SCPs) to manage services and permissions for those OUs. AWS Identity and Access Management (IAM) helps you securely control access to services and resources within a single account, not across multiple accounts. Amazon Cognito provides user authentication, authorization and management for web and mobile apps, hence, irrelevant for managing multiple AWS accounts. AWS CloudTrail tracks user activity and API usage for auditing purposes but does not manage access policies across organizational units.

Creating read replicas allows the primary database to offload read requests to the replicas, thereby improving the performance of the primary instance for write operations and providing faster read responses from the replicas. The deployment of read replicas in different Availability Zones (AZs) also increases high availability. The synchronization of read replicas is asynchronous, which helps in scaling-out read operations without impacting the write latency of the primary database. Increasing the instance size could improve performance but would not address the scalability or high availability. Multi-AZ deployment is for high availability and failover support, not for scaling read operations. Using a caching layer such as Amazon ElastiCache can indeed reduce database load, but it does not replace the need for read replicas when the goal is to scale read operations.

A security group acts as a virtual firewall for your instance to control inbound and outbound traffic. Security groups operate at the instance level, not the subnet level. Therefore, each instance in a subnet in your VPC can be assigned to a different set of security groups. Network Access Control Lists (NACLs) operate at the subnet level, so they are not the correct answer. Route tables direct network traffic, but do not control or filter traffic like a firewall. Subnet CIDRs are used for IP address allocation within a VPC and have no filtering capabilities.

The most efficient way to manage permissions for multiple users who share common job functions is by using groups. When a permissions update for a job function is needed, making a single change to the group policy will automatically propagate to all users in that group. Attaching permissions directly to each user is not scalable and makes it difficult to manage when there are changes in common access patterns. Utilizing a single role for all users would go against individualized access rights and does not support scalable permission updates. Service control policies apply to accounts within an AWS Organization and not to individual user accounts; hence, they are not suitable for managing individualized permissions within a single account.

Creating read replicas of the primary database instance allows for the distribution of the read query load, helping to maintain query performance during traffic peaks without a costly scaling of the primary instance. This technique improves read throughput at a lower cost compared to scaling up the primary instance or using a caching service for queries that cannot be cached. Implementing read replicas is more appropriate for balancing read traffic than using a caching service, which is mainly beneficial for frequently accessed immutable data, or leveraging an additional standby replica, which is more focused on high availability rather than read distribution.

Using an Application Load Balancer in conjunction with EC2 Auto Scaling across multiple Availability Zones is the most resilient option for maintaining service continuity and client session state. The ALB offers session stickiness, which is crucial for stateful applications to maintain user session information across requests, hence its suitability for an eCommerce workload. Auto Scaling ensures that upon an EC2 instance failure, a new instance is provisioned automatically to replace the failed one, preserving the desired capacity and performance levels. Directly deploying the application on S3 with Amazon CloudFront for static resources does not cater to the stateful nature of the application. While RDS Multi-AZ does serve as a resilient database solution, it does not facilitate high availability for the application layer itself. Utilizing Elastic IP addresses does not inherently provide failover for instance failures and lacks the capability to automatically reroute traffic to healthy instances.

Amazon Elastic File System (EFS) is optimized for use cases where a shared file system is required. It supports NFS protocol, and multiple compute instances can simultaneously access the same file system, making it the correct choice for the described scenario. Alternative solutions like Amazon S3 and Amazon EBS do not offer file-level storage with concurrent access. S3 offers object storage with eventual consistency, which is not suitable for file systems requiring consistent and concurrent access, while EBS is a block-level storage that's only attachable to one instance at a time, ruling out simultaneous access.

Setting up a trust relationship between the centralized directory service and cloud-based resources with specific roles dedicated for each environment is the most secure and scalable solution. This maintains a single identity for users while leveraging existing authentication mechanisms and enables appropriate, limited access to development, staging, or production resources. Direct attachment of policies to identities is less secure and scalable. Amazon Cognito is better suited for consumer application user pools and identity management. Using one cloud identity with multiple credentials is not a best practice due to security and management complexity.

Amazon Elastic File System (Amazon EFS) is the most appropriate storage service for this scenario. EFS provides a scalable, fully managed Network File System (NFS) for use with AWS Cloud services and on-premises resources. It supports standard file system semantics such as file locking and hierarchical directories, which are essential for applications that require shared file storage. EFS is designed for low-latency access to data and scales automatically as files are added and removed, making it both scalable and cost-effective. Amazon Simple Storage Service (Amazon S3) is object storage and does not support file system semantics like file locking or hierarchical directories. Amazon Elastic Block Store (Amazon EBS) provides block storage for EC2 instances and does not offer shared storage across multiple instances unless using EBS Multi-Attach, which has limitations and may not suit shared file system needs. Amazon S3 Glacier is intended for archival storage and is not suitable for frequently accessed data requiring low-latency access.

The option involving Wavelength is aimed primarily at applications that necessitate ultra-low latency for mobile devices and is not particularly suited for IoT sensor data. The concept of Local Zones is more about improving end user experience by reducing latency for interactive applications and is not primarily intended for local data processing scenarios. Snowball Edge is typically used for edge storage and batch data transfer rather than continuous, real-time edge processing. The correct choice, IoT Greengrass, is designed to allow connected devices to run local compute, message, data caching, and synchronization tasks. This includes executing functions, processing data streams, and only transmitting essential or processed data to the cloud, which aligns perfectly with the need to preprocess and reduce datasets at the source to save on transmission costs.

Relying solely on Average CPU Utilization might not be sufficient to guarantee the high availability of an application during peak times. Auto-scaling decisions should be based on a broader set of metrics that reflect different aspects of system performance and user experience to avoid potential bottlenecks or resource constraints. These can include metrics like network I/O, disk I/O, memory usage, request latency, error rates, and throughput. A combination of these metrics can more accurately trigger scaling actions that maintain the application's high availability during demand surges.

Creating a secondary site in another region within the same country with Amazon Route 53 managing traffic between regions ensures that the application stays online even if the primary region fails. Amazon Route 53 can detect if a region is down and route traffic to another available region that also resides within the country, thus maintaining compliance and high availability. This approach contributes to a fault-tolerant architecture by preventing a single region's failure from causing application downtime. Using multiple Availability Zones alone is not sufficient because it doesn't protect against a whole region failure. Adding read replicas in other Availability Zones does not address region-level disaster recovery if the read replicas are all within the same region. Expanding to only one additional Availability Zone will not prevent downtime if that zone is in the same region as the other two, as the requirement is to survive a full-region outage.

The service that manages customer encryption keys offers the capability to automate the rotation of the underlying encryption material used by a managed key, usually on an annual basis. This automation ensures that the material is updated regularly without the need to change the key identifier or associated metadata, thus adhering to strict security protocols. The operation does not demand manual intervention, nor does it rely on a reactive approach to potential key compromises. Moreover, a fixed five-year rotation period is not a feature currently supported by the service provider.

Cost Explorer with the implementation of categorization tags provides the capability to analyze and attribute expenses to specific resources and operational groups. By assigning relevant categorization tags to the resources used by each department, the Architect can filter and disassemble the expense data based on the organizational structure. These tags must be activated for cost allocation in the billing console before they can be used for granular visibility into expenditure associated with designated departments or teams.

Amazon S3 Glacier Deep Archive is designed for data that is accessed very infrequently but needs to be retained for a long-term period. It is the most cost-effective solution for archival storage, meeting compliance requirements and ensuring that records are preserved with minimum cost. Other options like Amazon S3 Standard or Amazon S3 One Zone-Infrequent Access are not optimized for long-term archival storage and would result in higher costs due to higher storage prices and the lack of infrequent access.