SAA-C03 Exam Dumps - AWS Certified Solutions Architect - Associate (SAA-C03)

https://aws.amazon.com/vpc/faqs/#:~:text=Can%20a%20subnet%20span%20Availability,within%20a%20single%20Availability%20Zone.

To maintain predictable database performance and ensure that the Lambda invocations do not overload the database with too many connections, a solutions architect should point the client driver at an RDS proxy endpoint and deploy the Lambda functions inside a VPC. An RDS proxy is a fully managed database proxy that allows applications to share connections to a database, improving database availability and scalability. By using an RDS proxy, the Lambda functions can reuse existing connections, rather than creating new ones for every invocation, reducing the connection overhead and latency. Deploying the Lambda functions inside a VPC allows them to access the private RDS DB instance securely and efficiently, without exposing it to the public internet. References:

Using Amazon RDS Proxy with AWS Lambda

Configuring a Lambda function to access resources in a VPC

Amazon CloudFront is a content delivery network (CDN) that securely delivers data, videos, applications, and APIs to customers globally with low latency and high transfer speeds. CloudFront supports signed URLs that provide authorized access to your content. This feature allows the company to control who can access their content and for how long, providing a secure and scalable solution for millions of users.

This option is the most efficient because it deploys the web tier and the application tier to a second Region, which provides high availability and redundancy for the application. It also uses an Amazon Aurora global database, which is a feature that allows a single Aurora database to span multiple AWS Regions1. It also deploys the database in the primary Region and the second Region, which provides low latency global reads and fast recovery from a Regional outage. It also uses Amazon Route 53 health checks with afailover routing policy to the second Region, which provides data protection by routing traffic to healthy endpoints in different Regions2. It also promotes the secondary to primaryas needed, which provides dataconsistency by allowing write operations in one of the Regions at a time3. This solution meets the requirement of expanding globally and ensuring that its application has minimal downtime. Option A is less efficient because it extends the Auto Scaling groups for the web tier and the application tier to deploy instances in Availability Zones in a second Region, which could incur higher costs and complexity than deploying them separately. It also uses an Aurora global database to deploy the database in the primary Region and the second Region, which is correct. However, it does not use Amazon Route 53 health checks with a failover routing policy to the second Region, which could result in traffic being routed to unhealthy endpoints. Option B is less efficient because it deploys the web tier and the application tier to a second Region, which is correct. It also adds an Aurora PostgreSQL cross-Region Aurora Replica in the second Region, which provides read scalability across Regions. However, it does not use an Aurora global database, which provides faster replication and recovery than cross-Region replicas. It also uses Amazon Route 53 health checks with a failover routing policy to the secondRegion, which is correct. However, it does not promote the secondary to primary as needed, which could result in data inconsistency or loss. Option C is less efficient because it deploys the web tier and the application tier to a second Region, which is correct. It also creates an Aurora PostgreSQL database in the second Region, which provides data redundancy across Regions. However, it does not use an Aurora global database or cross-Region replicas, which provide faster replication and recovery than creating separate databases. It also uses AWS Database Migration Service (AWS DMS) to replicate the primary database to the second Region, which provides data migration between different sources and targets. However, it does not use an Aurora global database or cross-Region replicas, which provide faster replication and recovery than using AWS DMS. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which is correct.

This option is the most efficient because it uses aMulti-AZ deployment for the DB instance, which provides enhanced availability and durability for RDS database instances by automatically replicating the data to a standby instance in a different AvailabilityZone1. It also provides a recovery point objective (RPO) of less than 1 second for all its production databases, as the standby instance is kept in sync with the primary instanceusing synchronous physical replication2. This solution meets the requirement of requiring a RPO of less than 1 second for all its production databases. Option B is less efficientbecause it uses auto scaling for the DB instance in one Availability Zone, which is a way to automatically adjust the compute capacity of your DB instance based on load or a schedule3. However, this does not provide a RPO of lessthan 1 second for all its production databases, as it does not replicate the data to another Availability Zone. Option C is less efficient because it uses read replicas in a separate Availability Zone, which are read-only copies of your primary database that can serve read traffic and support scaling. However, this does not provide a RPO of less than 1 second for all its production databases, as read replicas use asynchronous replication and can lag behind the primary database. Option D is less efficient because it uses AWS Database Migration Service (AWS DMS) change data capture (CDC) tasks, which are tasks that capture changes made to source data and apply them to target data. However, this does not provide a RPO of less than 1 second for all its production databases, as AWS DMS uses asynchronous replication and can lag behind the source database.

https://docs.aws.amazon.com/AmazonS3/latest/userguide/privatelink-interface-endpoints.html#types-of-vpc-endpoints-for-s3

https://docs.aws.amazon.com/vpc/latest/userguide/vpc-endpoints-s3.html

To improve the architecture of this application, the best solution would be to use Amazon Simple Queue Service (Amazon SQS) to buffer the requests and decouple the S3 bucket from the Lambda function. This will ensure that the documents are not lost and can be processed at a later time if the Lambda function is not available. This will ensure that the documents are not lost and can be processed at a later time if the Lambda function is not available. By using Amazon SQS, the architecture is decoupled and the Lambda function can process the documents in a scalable and fault-tolerant manner

https://aws.amazon.com/about-aws/whats-new/2018/04/announcing-s3-one-zone-infrequent-access-a-new-amazon-s3-storage-class/?nc1=h_ls