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Amazon SAA-C03 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Design Secure Architectures30%- Design secure access to AWS resources
  • 1. Identity federation
  • 2. Multi-factor authentication (MFA)
  • 3. AWS Organizations and SCPs
  • 4. IAM policies and roles
- Determine appropriate data security controls
  • 1. Data encryption strategies
  • 2. Data classification
  • 3. Amazon Macie and GuardDuty
  • 4. Data backup and recovery
- Design secure workloads and applications
  • 1. AWS KMS and CloudHSM
  • 2. Security groups and NACLs
  • 3. Encryption at rest and in transit
  • 4. AWS WAF and Shield
Topic 2: Design Resilient Architectures26%- Design scalable and loosely coupled architectures
  • 1. Amazon API Gateway
  • 2. Elastic Load Balancing
  • 3. Amazon SQS and SNS
  • 4. Amazon EventBridge
  • 5. Auto Scaling groups
- Design highly available and/or fault-tolerant architectures
  • 1. Amazon Route 53 routing policies
  • 2. Multi-Region architectures
  • 3. AWS Global Accelerator
  • 4. Multi-AZ deployments
  • 5. Disaster recovery strategies (backup/restore, pilot light, warm standby, multi-site)
Topic 3: Design Cost-Optimized Architectures20%- Design cost-optimized storage solutions
  • 1. EFS cost optimization
  • 2. EBS volume type selection
  • 3. S3 Intelligent-Tiering
  • 4. S3 storage classes and lifecycle policies
- Design cost-optimized compute solutions
  • 1. Right-sizing instances
  • 2. Auto Scaling for cost optimization
  • 3. AWS Lambda pricing model
  • 4. EC2 purchasing options (On-Demand, Reserved, Spot, Savings Plans)
- Design cost-optimized database solutions
  • 1. Aurora Serverless
  • 2. ElastiCache for caching
  • 3. RDS Reserved Instances
  • 4. DynamoDB capacity modes (On-demand vs Provisioned)
- Design cost-optimized network architectures
  • 1. Data transfer costs
  • 2. VPC endpoints to reduce NAT costs
  • 3. AWS Direct Connect for cost optimization
  • 4. CloudFront to reduce origin load
Topic 4: Design High-Performing Architectures24%- Determine high-performing database solutions
  • 1. Amazon ElastiCache (Redis/Memcached)
  • 2. Amazon Redshift
  • 3. Amazon DynamoDB
  • 4. Amazon RDS and Aurora
- Design high-performing and elastic compute solutions
  • 1. Amazon EC2 instance types and families
  • 2. Amazon ECS and EKS
  • 3. AWS Lambda
  • 4. AWS Elastic Beanstalk
- Determine high-performing data ingestion and transformation solutions
  • 1. AWS Data Pipeline
  • 2. Amazon Kinesis
  • 3. AWS Glue
  • 4. Amazon MSK
- Determine high-performing and/or scalable network architectures
  • 1. AWS Direct Connect
  • 2. Amazon CloudFront
  • 3. Amazon Route 53
  • 4. AWS Global Accelerator
  • 5. VPC endpoints
- Determine high-performing and/or scalable storage solutions
  • 1. Amazon EBS volume types
  • 2. Amazon EFS
  • 3. Amazon FSx
  • 4. Instance Store
  • 5. Amazon S3 storage classes and lifecycle policies

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Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q544-Q549):

NEW QUESTION # 544
A company needs to connect its on-premises data center network to a new VPC. The data center network has a 100 Mbps symmetrical internet connection. An application that is running on premises will transfer multiple gigabytes of data each day. The application will use an Amazon Data Firehose delivery stream for processing.
What should a solutions architect recommend for maximum performance?

Answer: D

Explanation:
AWS Direct Connect provides a dedicated network connection from on-premises to AWS, offering greater bandwidth and more consistent performance than internet-based connections or VPN. AWS PrivateLink enables secure, private connectivity to supported AWS services such as Kinesis Data Firehose over Direct Connect, bypassing the public internet and providing the highest throughput and lowest latency possible. This is the recommended solution for consistently transferring large volumes of data with maximum reliability and performance.
Reference Extract from AWS Documentation / Study Guide:
"AWS Direct Connect and AWS PrivateLink provide private, high-throughput connectivity between on- premises and AWS services, bypassing the public internet and ensuring maximum performance for large data transfers." Source: AWS Certified Solutions Architect - Official Study Guide, Hybrid Networking section.


NEW QUESTION # 545
A company has a large amount of data in an Amazon DynamoDB table. A large batch of data is appended to the table once each day. The company wants a solution that will make all the existing and future data in DynamoDB available for analytics on a long-term basis. Which solution meets these requirements with the LEAST operational overhead?

Answer: D

Explanation:
* Incremental Exports: Exporting DynamoDB data directly to Amazon S3 provides an automated, serverless way to make data available for analytics without operational overhead.
* Analytics-Friendly Storage: Amazon S3 supports long-term analytics workloads and can integrate with tools like Athena or QuickSight.: DynamoDB Export to S3 Documentation


NEW QUESTION # 546
[Design High-Performing Architectures]
A company wants to rearchitect a large-scale web application to a serverless microservices architecture. The application uses Amazon EC2 instances and is written in Python.
The company selected one component of the web application to test as a microservice. The component supports hundreds of requests each second. The company wants to create and test the microservice on an AWS solution that supports Python. The solution must also scale automatically and require minimal infrastructure and minimal operational support.
Which solution will meet these requirements?

Answer: B

Explanation:
AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. You can use Lambda to create and test microservices that are written in Python or other supported languages. Lambda scales automatically to handle the number of requests per second. You only pay for the compute time you consume. Lambda also integrates with other AWS services, such as Amazon API Gateway, Amazon S3, Amazon DynamoDB, and Amazon SQS, to enable event-driven architectures. Lambda has minimal infrastructure andoperational overhead, as you do not need to manage servers, operating systems, patches, or scaling policies.
The other options are not serverless solutions and require more infrastructure and operational support. They also do not scale automatically to handle the number of requests per second. A Spot Fleet is a collection of EC2 instances that run on spare capacity at low prices. However, Spot Instances can be interrupted by AWS at any time, which can affect the availability and performance of your microservice. AWS Elastic Beanstalk is a service that automates the deployment and management of web applications on EC2 instances. However, you still need to provision, configure, and monitor the underlying EC2 instances and load balancers. Amazon EKS is a service that runs Kubernetes on AWS. However, you still need to create, configure, and manage the EC2 instances that form the Kubernetes cluster and nodes. You also need to install and update the Kubernetes software and tools.
Reference:
What is AWS Lambda?
Building Lambda functions with Python
Create a layer for a Lambda Python function
AWS Lambda - Function in Python
How do I call my AWS Lambda function from a local python script?


NEW QUESTION # 547
A financial service company has a two-tier consumer banking application. The frontend serves static web content. The backend consists of APIs. The company needs to migrate the frontendcomponent to AWS. The backend of the application will remain on premises. The company must protect the application from common web vulnerabilities and attacks.
Which solution will meet these requirements with the LEAST operational overhead?

Answer: C

Explanation:
Comprehensive Deploying the frontend as a CloudFront distribution with multiple origins provides an efficient and scalable solution. Using WAF rules with CloudFront protects against web vulnerabilities, while the multi-origin configuration allows traffic routing to the on-premises backend APIs. This approach minimizes operational overhead compared to managing EC2 instances.
Reference:
Amazon CloudFront Features
AWS WAF Integration with CloudFront


NEW QUESTION # 548
A company runs its application by using Amazon EC2 instances and AWS Lambda functions. The EC2 instances run in private subnets of a VPC. The Lambda functions need direct network access to the EC2 instances for the application to work.
The application will run for 1 year. The number of Lambda functions that the application uses will increase during the 1-year period. The company must minimize costs on all application resources.
Which solution will meet these requirements?

Answer: C

Explanation:
Compute Savings Plans apply to EC2, AWS Fargate, and AWS Lambda usage, maximizing coverage for mixed architectures while retaining flexibility across instance families, regions, OS, and tenancy. For private connectivity, Lambda functions must be configured with VPC access to attach ENIs in the target subnets, enabling direct network access to EC2 in private subnets (no public subnets are required for intra-VPC communication). EC2 Instance Savings Plans only discount EC2 usage and are tied to a specific instance family in a region, reducing flexibility and leaving Lambda costs undiscounted. Keeping Lambda in the service VPC prevents direct access to private EC2 without VPC configuration. Thus, a 1-year Compute Savings Plan plus connecting Lambda to the private subnets minimizes total cost and meets connectivity needs.
References: AWS Savings Plans - Compute Savings Plans applicability (EC2, Fargate, Lambda); AWS Lambda Developer Guide - Configuring Lambda to access VPC resources (ENIs, subnets, security groups).
Note: Explanations are derived from AWS documentation and Well-Architected guidance. Verbatim extracts are not included because live browsing is unavailable here; the referenced AWS documents contain the authoritative wording.


NEW QUESTION # 549
......

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