Create Amazon S3 gateway endpoint in the VPC and add a VPC endpoint policy. This VPC endpoint policy will have a statement that allows S3 access only via access points owned by the organization.

Converting VPC flow logs to store in Apache Parquet format and specifying hourly partitions significantly improves query performance and reduces storage space usage. Apache Parquet is a columnar storage file format optimized for analytical queries, allowing Athena to scan less data and improve query performance.
Partitioning logs by hour further enhances query efficiency by limiting the amount of data scanned during queries, addressing the issue of degrading performance over time due to the growing volume of ingested logs.
AWS Documentation on VPC Flow Logs and Amazon Athena provides insights into configuring VPC flow logs in Apache Parquet format and using Athena for querying log data. This approach is recommended for efficient log analysis and storage optimization.

an AWS Lambda function in the backup region to promote the read replica and modify the Auto Scaling group values, and then configuring Route 53 with a health check that monitors the web application and sends an Amazon SNS notification to the Lambda function when the health check status is unhealthy. Finally, the application's Route 53 record should be updated with a failover policy that routes traffic to the ALB in the backup region when a health check failure occurs. This approach provides automatic failover to the backup region when a health check failure occurs, reducing the RTO to less than 15 minutes. Additionally, this approach is cost-effective as it does not require an active-active strategy.

The company should use Amazon Aurora global database and Amazon DynamoDB global table to deploy the data tier components across two Regions. Amazon Aurora global database is a feature that allows a single Aurora database to span multiple AWS Regions, enabling low-latency global reads and fast recovery from Region-wide outages1. Amazon DynamoDB global table is a feature that allows a single DynamoDB table to span multiple AWS Regions, enabling low-latency global reads and writes and fast recovery from Region-wide outages2.
References:
https://aws.amazon.com/rds/aurora/global-database/
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/globaltables_HowItWorks.html
https://aws.amazon.com/route53/application-recovery-controller/

This solution will meet the requirements of making the application highly available with the least development time. Creating a new AMI that is configured with SSM Agent will enable the company to use AWS Systems Manager to manage and patch the EC2 instances automatically, reducing downtime and human errors. Using a launch template for an Auto Scaling group will allow the company to launch multiple instances of the same configuration and scale them up or down based on demand. Using smaller instances in the Auto Scaling group will reduce the cost and improve the performance of the application tier. Creating an Application Load Balancer to distribute traffic across the instances in the Auto Scaling group will increase the availability and fault tolerance of the application tier. Migrating the database to Amazon Aurora MySQL will provide a fully managed, compatible, and scalable relational database service that can handle high throughput and concurrent connections.