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Amazon SAP-C02 Exam Syllabus Topics:

SectionWeightObjectives
Continuous Improvement for Existing Solutions23%- Performance optimization
  • 1. CDN implementation
  • 2. Database optimization
  • 3. Caching strategies (CloudFront, ElastiCache)
- Reviewing existing architectures
  • 1. Security pillar
  • 2. Reliability pillar
  • 3. Performance efficiency pillar
  • 4. Operational excellence pillar
  • 5. AWS Well-Architected Framework
  • 6. Cost optimization pillar
- Modernization strategies
  • 1. Re-architecting monolithic applications
  • 2. Serverless transformation
  • 3. Containerization
- Security hardening
  • 1. Encryption strategies
  • 2. Security monitoring
  • 3. Identity and access management
- Operational excellence improvements
  • 1. Infrastructure as Code (CloudFormation, Terraform)
  • 2. Monitoring and logging (CloudWatch)
  • 3. CI/CD pipelines
Migration Planning15%- Validation and testing post-migration
- Data migration considerations
  • 1. Large-scale data transfer
  • 2. Snow family devices
- Migration tools and services
  • 1. AWS Server Migration Service
  • 2. AWS Migration Hub
  • 3. AWS Transfer Family
  • 4. AWS Application Migration Service
  • 5. AWS DataSync
- Migration strategies
  • 1. Refactoring
  • 2. Repurchasing
  • 3. Rehosting (lift-and-shift)
  • 4. Replatforming
  • 5. Hybrid migration
Design for Organizational Complexity12.5%- Networks
  • 1. AWS Transit Gateway
  • 2. AWS Direct Connect
  • 3. VPN connections
  • 4. Hybrid DNS architecture
- Cross-account strategies and AWS organizations
  • 1. AWS Control Tower
  • 2. Organizational Units (OUs)
  • 3. Service Control Policies (SCPs)
- Multi-account AWS environments
Cost Control18.5%- Rightsizing recommendations
- Reserved capacity planning
  • 1. Capacity Reservations
  • 2. Reserved Instances
  • 3. Savings Plans
- Cost optimization strategies
  • 1. AWS Budgets
  • 2. AWS Cost Explorer
  • 3. Cost categories
  • 4. Cost allocation tags
- Resource efficiency
  • 1. Auto Scaling
  • 2. Managed services
  • 3. Serverless optimization
- Monitoring and controlling costs
  • 1. Budget alerts
  • 2. Anomaly detection
Design for New Solutions31%- Database migration
  • 1. Database types and selection
  • 2. AWS DMS (Database Migration Service)
  • 3. Schema Conversion Tool (SCT)
- High availability and fault tolerance
  • 1. Backup and restore
  • 2. Multi-AZ deployments
  • 3. Disaster recovery strategies
- Cost optimization at design phase
  • 1. Reserved Instances and Savings Plans
  • 2. Right-sizing resources
  • 3. Spot instances
- Multi-tier architecture
  • 1. Data tier considerations
  • 2. Web tier design
  • 3. Application tier
- Network design
  • 1. Subnet planning
  • 2. Network segmentation
  • 3. VPC architecture
  • 4. Security groups and NACLs
- Cloud Adoption Readiness
  • 1. 6 Rs of migration
  • 2. Migration strategy assessment
- Microservices patterns
  • 1. Event-driven architecture
  • 2. Containers and ECS/EKS
  • 3. Serverless architectures (Lambda)

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Amazon AWS Certified Solutions Architect - Professional (SAP-C02) Sample Questions (Q787-Q792):

NEW QUESTION # 787
A company has an application that stores data in a single Amazon S3 bucket. The company must keep all data for 1 year. The company's security team is concerned that an attacker could gain access to the AWS account through leaked long-term credentials.
Which solution will ensure that existing and future objects in the S3 bucket are protected?

Answer: C

Explanation:
https://docs.aws.amazon.com/AmazonS3/latest/userguide/security-best-practices.html


NEW QUESTION # 788
A company has application services that have been containerized and deployed on multiple Amazon EC2 instances with public IPs. An Apache Kafka cluster has been deployed to the EC2 instances. A PostgreSQL database has been migrated to Amazon RDS for PostgreSQL. The company expects a significant increase of orders on its platform when a new version of its flagship product is released.
What changes to the current architecture will reduce operational overhead and support the product release?

Answer: B

Explanation:
The correct answer is D. Deploy the application on Amazon Elastic Kubernetes Service (Amazon EKS) with AWS Fargate and enable auto scaling behind an Application Load Balancer. Create additional read replicas for the DB instance. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.
Option D meets the requirements of the scenario because it allows you to reduce operational overhead and support the product release by using the following AWS services and features:
Amazon Elastic Kubernetes Service (Amazon EKS) is a fully managed service that allows you to run Kubernetes applications on AWS without needing to install, operate, or maintain your own Kubernetes control plane. You can use Amazon EKS to deploy your containerized application services on a Kubernetes cluster that is compatible with your existing tools and processes.
AWS Fargate is a serverless compute engine that eliminates the need to provision and manage servers for your containers. You can use AWS Fargate as the launch type for your Amazon EKS pods, which are the smallest deployable units of computing in Kubernetes. You can also enable auto scaling for your pods, which allows you to automatically adjust the number of pods based on the demand or custom metrics.
An Application Load Balancer (ALB) is a load balancer that distributes traffic across multiple targets in multiple Availability Zones using HTTP or HTTPS protocols. You can use an ALB to balance the load across your Amazon EKS pods and provide high availability and fault tolerance for your application.
Amazon RDS for PostgreSQL is a fully managed relational database service that supports the PostgreSQL open source database engine. You can create additional read replicas for your DB instance, which are copies of your primary DB instance that can handle read-only queries and improve performance. You can also useread replicas to scale out beyond the capacity of a single DB instance for read-heavy workloads.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that makes it easy to build and run applications that use Apache Kafka to process streaming data. Apache Kafka is an open source platform for building real-time data pipelines and streaming applications. You can use Amazon MSK to create and manage a Kafka cluster that is highly available, secure, and compatible with your existing Kafka applications. You can also configure your application services to use the Amazon MSK cluster as a source or destination of streaming data.
Amazon S3 is an object storage service that offers high durability, availability, and scalability. You can store static content such as images, videos, or documents in Amazon S3 buckets, which are containers for objects.
You can also serve static content directly from Amazon S3 using public URLs or presigned URLs.
Amazon CloudFront is a fast content delivery network (CDN) service that securely delivers data, videos, applications, and APIs to customers globally with low latency and high transfer speeds. You can use Amazon CloudFront to create a distribution that caches static content from your Amazon S3 bucket at edge locations closer to your users. This can improve the performance and user experience of your application.
Option A is incorrect because creating an EC2 Auto Scaling group behind an ALB would not reduce operational overhead as much as using AWS Fargate with Amazon EKS, as you would still need to manage EC2 instances for your containers. Creating additional read replicas for the DB instance would not provide high availability or fault tolerance in case of a failure of the primary DB instance, unlike deploying the DB instance in Multi-AZ mode. Creating Amazon Kinesis data streams would not be compatible with your existing Apache Kafka applications, unlike using Amazon MSK.
Option B is incorrect because creating an EC2 Auto Scaling group behind an ALB would not reduce operational overhead as much as using AWS Fargate with Amazon EKS, as you would still need to manage EC2 instances for your containers. Creating Amazon Kinesis data streams would not be compatible with your existing Apache Kafka applications, unlike using Amazon MSK. Storing and serving static content directly from Amazon S3 would not provide optimal performance and user experience, unlike using Amazon CloudFront.
Option C is incorrect because deploying the application on a Kubernetes cluster created on the EC2 instances behind an ALB would not reduce operational overhead as much as using AWS Fargate with Amazon EKS, as you would still need to manage EC2 instances and Kubernetes control plane for your containers. Using Amazon API Gateway to interact with the application would add an unnecessary layer of complexity and cost to your architecture, as you would need to create and maintain an API gateway that proxies requests to your ALB.


NEW QUESTION # 789
A company is planning to migrate its business-critical applications from an on-premises data center to AWS. The company has an on-premises installation of a Microsoft SQL Server Always On cluster. The company wants to migrate to an AWS managed database service. A solutions architect must design a heterogeneous database migration on AWS.
Which solution will meet these requirements?

Answer: C

Explanation:
AWS Schema Conversion Tool (SCT) can automatically convert the database schema from Microsoft SQL Server to Amazon RDS for MySQL. This allows for a smooth transition of the database schema without any manual intervention. AWS DMS can then be used to migrate the data from the on-premises databases to the newly created Amazon RDS for MySQL instance.
This service can perform a one-time migration of the data or can set up ongoing replication of data changes to keep the on-premises and AWS databases in sync.
https://aws.amazon.com/dms/schema-conversion-tool/


NEW QUESTION # 790
A team collects and routes behavioral data for an entire company. The company runs a Multi-AZ VPC environment with public subnets, private subnets, and in internet gateway Each public subnet also contains a NAT gateway Most of the company's applications read from and write to Amazon Kinesis Data Streams. Most of the workloads am in private subnets.
A solutions architect must review the infrastructure. The solutions architect needs to reduce costs and maintain the function of the applications. The solutions architect uses Cost Explorer and notices that the cost in the EC2-Other category is consistently high A further review shows that NatGateway-Bytes charges are increasing the cost in the EC2-Other category.
What should the solutions architect do to meet these requirements?

Answer: B


NEW QUESTION # 791
A company is providing weather data over a REST-based API to several customers. The API is hosted by Amazon API Gateway and is integrated with different AWS Lambda functions for each API operation. The company uses Amazon Route 53 for DNS and has created a resource record of weather.example.com. The company stores data for the API in Amazon DynamoDB tables. The company needs a solution that will give the API the ability to fail over to a different AWS Region.
Which solution will meet these requirements?

Answer: C

Explanation:
https://docs.aws.amazon.com/apigateway/latest/developerguide/dns-failover.html


NEW QUESTION # 792
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