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Amazon SAA-C03 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Design Resilient Architectures	26%	- Design scalable and loosely coupled architectures 1. Amazon API Gateway 2. Amazon SQS and SNS 3. Elastic Load Balancing 4. Auto Scaling groups 5. Amazon EventBridge - Design highly available and/or fault-tolerant architectures 1. AWS Global Accelerator 2. Multi-Region architectures 3. Amazon Route 53 routing policies 4. Multi-AZ deployments 5. Disaster recovery strategies (backup/restore, pilot light, warm standby, multi-site)
Topic 2: Design Secure Architectures	30%	- Design secure access to AWS resources 1. AWS Organizations and SCPs 2. Multi-factor authentication (MFA) 3. Identity federation 4. IAM policies and roles - Determine appropriate data security controls 1. Amazon Macie and GuardDuty 2. Data encryption strategies 3. Data backup and recovery 4. Data classification - Design secure workloads and applications 1. Encryption at rest and in transit 2. AWS KMS and CloudHSM 3. Security groups and NACLs 4. AWS WAF and Shield
Topic 3: Design High-Performing Architectures	24%	- Determine high-performing and/or scalable network architectures 1. AWS Direct Connect 2. VPC endpoints 3. AWS Global Accelerator 4. Amazon CloudFront 5. Amazon Route 53 - Design high-performing and elastic compute solutions 1. AWS Lambda 2. Amazon ECS and EKS 3. Amazon EC2 instance types and families 4. AWS Elastic Beanstalk - Determine high-performing database solutions 1. Amazon ElastiCache (Redis/Memcached) 2. Amazon RDS and Aurora 3. Amazon DynamoDB 4. Amazon Redshift - Determine high-performing data ingestion and transformation solutions 1. Amazon MSK 2. AWS Data Pipeline 3. AWS Glue 4. Amazon Kinesis - Determine high-performing and/or scalable storage solutions 1. Instance Store 2. Amazon EBS volume types 3. Amazon FSx 4. Amazon EFS 5. Amazon S3 storage classes and lifecycle policies
Topic 4: Design Cost-Optimized Architectures	20%	- Design cost-optimized compute solutions 1. EC2 purchasing options (On-Demand, Reserved, Spot, Savings Plans) 2. AWS Lambda pricing model 3. Right-sizing instances 4. Auto Scaling for cost optimization - Design cost-optimized database solutions 1. Aurora Serverless 2. ElastiCache for caching 3. DynamoDB capacity modes (On-demand vs Provisioned) 4. RDS Reserved Instances - Design cost-optimized network architectures 1. CloudFront to reduce origin load 2. Data transfer costs 3. VPC endpoints to reduce NAT costs 4. AWS Direct Connect for cost optimization - Design cost-optimized storage solutions 1. EBS volume type selection 2. S3 storage classes and lifecycle policies 3. EFS cost optimization 4. S3 Intelligent-Tiering

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Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q400-Q405):

NEW QUESTION # 400
A company is preparing a new data platform that will ingest real-time streaming data from multiple sources. The company needs to transform the data before writing the data to Amazon S3. The company needs the ability to use SQL to query the transformed data.
Which solutions will meet these requirements? (Choose two.)

A. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use Amazon Kinesis Data Analytics to transform the data and to write the data to Amazon S3. Use the Amazon RDS query editor to query the transformed data from Amazon S3.
B. Use Amazon Kinesis Data Streams to stream the data. Use Amazon Kinesis Data Analytics to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.
C. Use Amazon Managed Streaming for Apache Kafka (Amazon MSK) to stream the data. Use AWS Glue to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.
D. Use Amazon Kinesis Data Streams to stream the data. Use AWS Glue to transform the data. Use Amazon Kinesis Data Firehose to write the data to Amazon S3. Use the Amazon RDS query editor to query the transformed data from Amazon S3.
E. Use AWS Database Migration Service (AWS DMS) to ingest the data. Use Amazon EMR to transform the data and to write the data to Amazon S3. Use Amazon Athena to query the transformed data from Amazon S3.

Answer: B,C

Explanation:
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.
Reference:
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?

NEW QUESTION # 401
A medical company wants to perform transformations on a large amount of clinical trial data that comes from several customers. The company must extract the data from a relational databasethatcontains the customer data. Then the company will transform the data by using a series of complex rules. The company will load the data to Amazon S3 when the transformations are complete.
* All data must be encrypted where it is processed before the company stores the data in Amazon S3.
* All data must be encrypted by using customer-specific keys.
Which solution will meet these requirements with the LEAST amount of operational effort?

A. Create one AWS Glue job for each customer Attach a security configuration to each job that uses client-side encryption with AWS KMS managed keys (CSE-KMS) to encrypt the data.
B. Create one AWS Glue job for each customer Attach a security configuration to each job that uses server-side encryption with Amazon S3 managed keys (SSE-S3) to encrypt the data.
C. Create one Amazon EMR cluster for each customer Attach a security configuration to each cluster that uses client-side encryption with a custom client-side root key (CSE-Custom) to encrypt the data.
D. Create one Amazon EMR cluster for each customer Attach a security configuration to each cluster that uses server-side encryption with AWS KMS keys (SSE-KMS) to encrypt the data.

Answer: A

Explanation:
AWS Glue jobs are designed for extract, transform, and load (ETL) operations, which are perfect for transforming clinical trial data. AWS Glue integrates with AWS Key Management Service (KMS), allowing for customer-specific encryption keys, fulfilling the encryption requirement with minimal operational effort. Client-side encryption with AWS KMS ensures that the data is encrypted before it is sent to S3, aligning with the security needs specified in the scenario.
Key aspects:
AWS Glue: This managed ETL service simplifies data transformation, reduces operational overhead, and integrates seamlessly with KMS.
CSE-KMS: Client-side encryption with KMS ensures that the data is encrypted with customer- specific keys before it is processed or stored in S3, offering robust security.
Minimal Operational Overhead: Compared to managing an EMR cluster, AWS Glue automates much of the process, making it a lower-effort solution.
AWS Documentation: According to the AWS Well-Architected Framework, encryption with AWS KMS offers strong security controls that meet the needs of industries requiring high levels of confidentiality.

NEW QUESTION # 402
A company website hosted on Amazon EC2 instances processes classified data stored in The application writes data to Amazon Elastic Block Store (Amazon EBS) volumes The company needs to ensure that all data that is written to the EBS volumes is encrypted at rest.
Which solution will meet this requirement?

A. Create an EC2 instance tag that has a key of Encrypt and a value of True Tag all instances that require encryption at the EBS level
B. Create an AWS Key Management Service (AWS KMS) key policy that enforces EBS encryption in the account Ensure that the key policy is active
C. Create an 1AM role that specifies EBS encryption Attach the role to the EC2 instances
D. Create the EBS volumes as encrypted volumes Attach the EBS volumes to the EC2 instances

Answer: D

Explanation:
The simplest and most effective way to ensure that all data that is written to the EBS volumes is encrypted at rest is to create the EBS volumes as encrypted volumes. You can do this by selecting the encryption option when you create a new EBS volume, or by copying an existing unencrypted volume to a new encrypted volume. You can also specify the AWS KMS key that you want to use for encryption, or use the default AWS-managed key. When you attach the encrypted EBS volumes to the EC2 instances, the data will be automatically encrypted and decrypted by the EC2 host. This solution does not require any additional IAM roles, tags, or policies.
Reference:
Amazon EBS encryption
Creating an encrypted EBS volume
Encrypting an unencrypted EBS volume

NEW QUESTION # 403
A company is developing a mobile game that streams score updates to a backend processor and then posts results on a leaderboard A solutions architect needs to design a solution that can handle large traffic spikes process the mobile game updates in order of receipt, and store the processed updates in a highly available database The company also wants to minimize the management overhead required to maintain the solution What should the solutions architect do to meet these requirements?

A. Push score updates to an Amazon Simple Queue Service (Amazon SQS) queue. Use a fleet of Amazon EC2 instances with Auto Scaling to process the updates in the SQS queue. Store the processed updates in an Amazon RDS Multi-AZ DB instance.
B. Push score updates to Amazon Kinesis Data Streams. Process the updates with a fleet of Amazon EC2 instances set up for Auto Scaling Store the processed updates in Amazon Redshift.
C. Push score updates to an Amazon Simple Notification Service (Amazon SNS) topic Subscribe an AWS Lambda function to the SNS topic to process the updates. Store the processed updates in a SQL database running on Amazon EC2.
D. Push score updates to Amazon Kinesis Data Streams Process the updates in Kinesis Data Streams with AWS Lambda Store the processed updates in Amazon DynamoDB.

Answer: D

Explanation:
Amazon Kinesis Data Streams is a scalable and reliable service that can ingest, buffer, and process streaming data in real-time. It can handle large traffic spikes and preserve the order of the incoming data records. AWS Lambda is a serverless compute service that can process the data streams from Kinesis Data Streams without requiring any infrastructure management. It can also scale automatically to match the throughput of the data stream. Amazon DynamoDB is a fully managed, highly available, and fast NoSQL database that can store the processed updates from Lambda. It can also handle high write throughput and provide consistent performance. By using these services, the solutions architect can design a solution that meets the requirements of the company with the least operational overhead.

NEW QUESTION # 404
A company is hosting a web application on AWS using a single Amazon EC2 instance that stores user-uploaded documents in an Amazon EBS volume. For better scalability and availability, the company duplicated the architecture and created a second EC2 instance and EBS volume in another Availability Zone placing both behind an Application Load Balancer After completing this change, users reported that, each time they refreshed the website, they could see one subset of their documents or the other, but never all of the documents at the same time.
What should a solutions architect propose to ensure users see all of their documents at once?

A. Copy the data so both EBS volumes contain all the documents.
B. Copy the data from both EBS volumes to Amazon EFS Modify the application to save new documents to Amazon EFS
C. Configure the Application Load Balancer to send the request to both servers Return each document from the correct server.
D. Configure the Application Load Balancer to direct a user to the server with the documents

Answer: B

Explanation:
Explanation
Amazon EFS provides file storage in the AWS Cloud. With Amazon EFS, you can create a file system, mount the file system on an Amazon EC2 instance, and then read and write data to and from your file system. You can mount an Amazon EFS file system in your VPC, through the Network File System versions 4.0 and
4.1 (NFSv4) protocol. We recommend using a current generation Linux NFSv4.1 client, such as those found in the latest Amazon Linux, Redhat, and Ubuntu AMIs, in conjunction with the Amazon EFS Mount Helper. For instructions, see Using the amazon-efs-utils Tools.
For a list of Amazon EC2 Linux Amazon Machine Images (AMIs) that support this protocol, see NFS Support. For some AMIs, you'll need to install an NFS client to mount your file system on your Amazon EC2 instance. For instructions, see Installing the NFS Client.
You can access your Amazon EFS file system concurrently from multiple NFS clients, so applications that scale beyond a single connection can access a file system. Amazon EC2 instances running in multiple Availability Zones within the same AWS Region can access the file system, so that many users can access and share a common data source.

NEW QUESTION # 405
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