Exam AWS Certified Solutions Architect - Associate SAA-C03 topic 1 question 183 discussion

A - is correct, because Dynamodb on-demand scales write and read capacity B - Aurora auto scaling scales only read replicas

please is this dump enough to pass the exam?

I also initially thought Aurora is better suited since it gives auto scaling as well as auto scaling. However, it doesn't auto scale for writer instances. there is a note in Aurora doc: "Aurora Auto Scaling doesn't apply to the workload on the writer DB instance. Aurora Auto Scaling helps with the workload only on the reader instances." https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Integrating.AutoScaling.html Hence the right answer is A. But man, how devious! a small detail can derail you from making the right choice!

Dynamodb - No need to provision, patch, or manage servers.

Dynamo DB Push Scaling

https://aws.amazon.com/blogs/database/how-to-determine-if-amazon-dynamodb-is-appropriate-for-your-needs-and-then-plan-your-migration/#:~:text=Are%20working%20with%20an%20online%20transaction%20processing%20(OLTP)%20workload.%20High%2Dperformance%20reads%20and%20writes%20are%20easy%20to%20manage%20with%20DynamoDB%2C%20and%20you%20can%20expect%20performance%20that%20is%20effectively%20constant%20across%20widely%20varying%20loads.

C,D are out due to EC2 scaling which is not ideal for static content scaling. A and B are logical choices. B uses Aurora which is more for relational database and comes with the baggage and limitations of RDBMS scaling. DynamDB (no SQL) is easier to scale for both read and write. A is simply better than be for an ordering website so that is the better option. Note that B would have been good if A wasn't a choice.

dynamodb is serverless

Hi all! The answer is A and NOT B on this one as the company is building an ordering website (OLTP). DynamoDB's high performance read and writes are perfect for an OLTP use case. https://aws.amazon.com/blogs/database/how-to-determine-if-amazon-dynamodb-is-appropriate-for-your-needs-and-then-plan-your-migration/

S3 is discarded since the question says: A company is building a new dynamic ordering website,

minimize server maintenance and patching, highly available, scale read and write = serverless = Amazon S3, Amazon API Gateway, AWS Lambda, Amazon DynamoDB

Key phrase in the Question is must scale read and write capacity. Aurora is only for Read. Amazon DynamoDB has two read/write capacity modes for processing reads and writes on your tables: On-demand Provisioned (default, free-tier eligible) https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadWriteCapacityMode.html

Minimize maintenance & Patching = Serverless S3, DynamoDB are serverless

Minimize maintenance & Patching = Serverless services Serverless services with no sql database is perfect combination

B. This solution leverages serverless technologies like API Gateway and Lambda for hosting dynamic content, reducing server maintenance and patching. Aurora with Aurora Auto Scaling provides a highly available and scalable database solution. Hosting static content in S3 and configuring CloudFront for content delivery ensures high availability and efficient scaling. A. Using DynamoDB with on-demand capacity may provide scalability, but it does not offer the same level of flexibility and performance as Aurora. Additionally, it does not address the hosting of dynamic content using serverless technologies. C. Hosting all the website content on EC2 instances requires server maintenance and patching. While using ASG and an ALB helps with availability and scalability, it does not minimize server maintenance as requested. D. Hosting all the website content on EC2 instances introduces server maintenance and patching. Using Aurora with Aurora Auto Scaling is a good choice for the database, but it does not address the need to minimize server maintenance and patching for the overall infrastructure.

B isn't correct because of cooldown You can tune the responsiveness of a target-tracking scaling policy by adding cooldown periods that affect scaling your Aurora DB cluster in and out. A cooldown period blocks subsequent scale-in or scale-out requests until the period expires. These blocks slow the deletions of Aurora Replicas in your Aurora DB cluster for scale-in requests, and the creation of Aurora Replicas for scale-out requests.

Key word in question "storing ordering data" DynamoDB is perfect for storing ordering data (key-values)