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

https://aws.amazon.com/blogs/big-data/manage-fine-grained-access-control-using-aws-lake-formation/

https://aws.amazon.com/blogs/aws/introducing-amazon-s3-object-lambda-use-your-cod e-to-process-data-as-it-is-being-retrieved-from-s3/

S3 Object Lambda is a new feature of Amazon S3 that enables customers to add their own code to process data retrieved from S3 before returning it to the application. By using S3 Object Lambda, the data can be processed and transformed in real-time, without the need to store multiple copies of the data in separate S3 buckets or DynamoDB tables.

In this case, the Pll can be removed from the data by the code added to S3 Object Lambda before returning the data to the two applications that do not need to process Pll. The one application that requires Pll can be pointed to the original S3 bucket where the Pll is still stored.

Using S3 Object Lambda is the simplest and most cost-effective solution, as it eliminates the need to maintain multiple copies of the same data in different buckets or tables, which can result in additional storage costs and operational overhead.

Amazon RDS Proxy is a service that provides a fully managed, highly available database proxy for Amazon RDS and Aurora databases. It allows you to pool and share database connections, reduce database load, and improve application scalability and availability.

By using Amazon RDS Proxy in front of your Aurora database, you can achieve the following benefits:

You can reduce the number of connections to your database and avoid errors that indicate that there are too many connections. Amazon RDS Proxy handles the connection management and multiplexing for you, so you can use fewer database connections and resources.

You can reduce the failover time by 20% when a read replica is promoted to primary writer. Amazon RDS Proxy automatically detects failures and routes traffic to the new primary instance without requiring changes to your application code or configuration. According to a benchmark test, using Amazon RDS Proxy reduced the failover time from 66 seconds to 53 seconds, which is a 20% improvement.

You can improve the security and compliance of your database access. Amazon RDS Proxy integrates with AWS Secrets Manager and AWS Identity and Access Management (IAM) to enable secure and granular authentication and authorization for your database connections.

Amazon S3 is an object storage service that offers industry-leading scalability, data availability, security, and performance. You can use Amazon S3 to host static content for your website, such as HTML files, images, videos, etc. Amazon Elastic Container Service (Amazon ECS) is a fully managed container orchestration service that allows you to run and scale containerized applications on AWS. AWS Fargate is a serverless compute engine for containers that works with both Amazon ECS and Amazon EKS. Fargate makes it easy for you to focus on building your applications by removing the need to provision and manage servers. You can use Amazon ECS with AWS Fargate for compute power for your containerized application logic tier. Amazon RDS is a managed relational database service that makes it easy to set up, operate, and scale a relational database in the cloud. You can use a managed Amazon RDS cluster for the database tier of your application. This solution will simplify deployment and reduce operational costs for your three-tier application. References: https://docs.aws.amazon.com/AmazonS3/latest/userguide/WebsiteHosting.html https://docs.aws.amazon.com/AmazonECS/latest/developerguide/Welcome.html https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Welcome.ht ml

To ingest, transform, and query real-time streaming data from multiple sources, Amazon Kinesis and Amazon MSK are suitable solutions. Amazon Kinesis Data Streams can stream the data from various sources and integrate with other AWS services. Amazon Kinesis Data Analytics can transform the data using SQL or Apache Flink. Amazon Kinesis Data Firehose can write the data to Amazon S3 or other destinations. Amazon Athena can query the transformed data from Amazon S3 using standard SQL. Amazon MSK can stream the data using Apache Kafka, which is a popular open-source platform for streaming data. AWS Glue can transform the data using Apache Spark or Python scripts and write the data to Amazon S3 or other destinations. Amazon Athena can also query the transformed data from Amazon S3 using standard SQL.

References:

What Is Amazon Kinesis Data Streams?

What Is Amazon Kinesis Data Analytics?

What Is Amazon Kinesis Data Firehose?

What Is Amazon Athena?

What Is Amazon MSK?

What Is AWS Glue?

AWS DataSync is a service that makes it easy to move large amounts of data between AWS storage services and on-premises storage systems. AWS DataSync can copy files from an S3 bucket to an EFS file system and another S3 bucket continuously, as well as overwrite only the files that have changed in the source. This solution will meet the requirements with the least operational overhead, as it does not require any code development or manual intervention.

References:

4 explains how to create AWS DataSync locations for different storage services.

5 describes how to create and configure AWS DataSync tasks for data transfer.

6 discusses the different transfer modes that AWS DataSync supports.

An egress-only internet gateway is a VPC component that allows outbound communication over IPv6 from instances in your VPC to the internet, and prevents the internet from initiating an IPv6 connection with your instances. This meets the company’s security policy and requirements. To use an egress-only internet gateway, you need to add a route in the subnet’s route table that routes IPv6 internet traffic (::/0) to the egress-only internet gateway.

Reference URLs:

1 https://docs.aws.amazon.com/vpc/latest/userguide/egress-only-internet-gateway.html

2 https://dev.to/aws-builders/what-is-an-egress-only-internet-gateways-in-aws-7gp

3 https://docs.aws.amazon.com/vpc/latest/userguide/route-table-options.html

Generally, for building a hierarchical relationship model, a graph database such as Amazon Neptune is a better choice. In some cases, however, DynamoDB is a better choice for hierarchical data modeling because of its flexibility, security, performance, and scale. https://docs.aws.amazon.com/prescriptive-guidance/latest/dynamodb-hierarchical-data-model/introduction.html