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

Amazon RDS Custom for Oracle: This service allows you to bring your own Oracle Database licenses and provides the flexibility to customize the database settings, making it suitable for applications that require privileged access and third-party database features.

BYOL (Bring Your Own License):

RDS Custom supports the BYOL model, allowing you to use your existing Oracle licenses and comply with licensing requirements.

This helps in leveraging existing investments and reducing migration costs.

Customization and Third-Party Features:

RDS Custom allows for deeper customization of the database environment compared to standard RDS instances.

This makes it possible to support the third-party features that your application relies on without significant changes.

Migration Process:

Use native Oracle tools like Data Pump or RMAN to migrate the database to RDS Custom.

Customize the database settings post-migration to ensure compatibility with third-party features.

References:

Amazon RDS Custom for Oracle

Migrating to Amazon RDS Custom

Understanding the Requirement: The company wants to maximize cost savings for their application over the next three years, with the flexibility to change the instance family and sizes within the next six months based on application popularity and usage.

Analysis of Options:

Compute Savings Plan: This plan offers the most flexibility, allowing the company to change instance families, sizes, and regions. It applies to EC2, AWS Fargate, and AWS Lambda, offering significant cost savings with this flexibility.

EC2 Instance Savings Plan: This plan is less flexible than the Compute Savings Plan, as it only applies to EC2 instances and allows changes within a specific instance family.

Zonal Reserved Instances: These provide a discount on EC2 instances but are tied to a specific availability zone and instance type, offering the least flexibility.

Standard Reserved Instances: These offer discounts on EC2 instances but with more restrictions compared to Savings Plans, particularly when changing instance types and families.

Best Option for Flexibility and Savings:

The Compute Savings Plan is the most cost-effective solution because it allows the company to maintain flexibility while still achieving significant cost savings. This is critical for adapting to changing application demands without being locked into specific instance types or families.

References:

AWS Savings Plans

EC2 Instance Types

The issue described in the question, where incoming traffic seems to favor one EC2 instance, is often caused by session affinity (also known as sticky sessions) being enabled on the Application Load Balancer (ALB). When session affinity is enabled, the ALB routes requests from the same client to the same EC2 instance. This can cause an imbalance in traffic distribution, leading to performance bottlenecks on certain instances while others remain underutilized.

To resolve this issue, disabling session affinity ensures that the ALB distributes incoming traffic evenly across all EC2 instances, allowing better load distribution and reducing latency. The ALB will rely on its round-robin or least outstanding requests algorithm (depending on the configuration) to distribute traffic more evenly across instances.

Option B (Network Load Balancer): The NLB is designed for Layer 4 (TCP) traffic and low latency use cases, but it is not needed here as the problem is with load balancing logic at the application layer (Layer 7). The ALB is more appropriate for HTTP/HTTPS traffic.

Option C (Increase EC2 Instances): Adding more EC2 instances does not solve the root issue of uneven traffic distribution.

Option D (Health Check Frequency): Adjusting health check frequency won't address the imbalance caused by session affinity.

AWS References:

Application Load Balancer Sticky Sessions

Joining the FSx for Windows File Server file system to the on-premises Active Directory will allow the company to use the existing Active Directory groups to restrict access to the file shares, folders, and files after the move to AWS. This option allows the company to continue using their existing access controls and management structure, making the transition to AWS more seamless.

In a typical development environment, dev and test databases are mostly utilized for 8 hours a day and sit idle when not in use. However, the databases are billed for the compute and storage costs during this idle time. To reduce the overall cost, Amazon RDS allows instances to be stopped temporarily. While the instance is stopped, you’re charged for storage and backups, but not for the DB instance hours. Please note that a stopped instance will automatically be started after 7 days. This post presents a solution using AWS Lambda and Amazon EventBridge that allows you to schedule a Lambda function to stop and start the idle databases with specific tags to save on compute costs. The second post presents a solution that accomplishes stop and start of the idle Amazon RDS databases using AWS Systems Manager.

This solution satisfies the requirements in the following ways:

• AWS Backup will automatically take full backups of the DynamoDB table on the schedule defined in the backup plan (the first of each month).

• The lifecycle policy can transition backups to cold storage after 6 months, meeting that requirement.

• Setting a 7-year retention period in the backup plan will ensure each backup is retained for 7 years as required.

• AWS Backup manages the backup jobs and lifecycle policies, requiring no custom scripting or management.

AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. Lambda scales automatically based on the incoming requests, but it may take some time to initialize new instances of your function if there is a sudden increase in demand. This may result in high latency or cold starts for your application. To avoid this, you can use provisioned concurrency, which ensures that your function is initialized and ready to respond at any time. You can also set up a scheduled scaling policy that increases the provisioned concurrency before employees begin to use the application each day, and decreases it when the demand is low. References: https://docs.aws.amazon.com/lambda/latest/dg/configuration-concurrency.html

This option is the most efficient because it uses a Multi-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 Availability Zone1. 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 instance using 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 efficient because 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 less than 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.