Free Practice Questions for AWS Certified Solutions Architect - Associate (SAA-C03) Certification

Knowledge of:

• Access controls and management across multiple accounts • AWS federated access and identity services (for example, IAM, AWS IAM Identity Center) • AWS global infrastructure (for example, Availability Zones, AWS Regions)

• AWS security best practices (for example, the principle of least privilege) • The AWS shared responsibility model

Skills in:

• Applying AWS security best practices to IAM users and root users (for example, multi-factor authentication [MFA]) • Designing a flexible authorization model that includes IAM users, groups, roles, and policies • Designing a role-based access control strategy (for example, AWS STS, role switching, cross-account access) • Designing a security strategy for multiple AWS accounts (for example, AWS Control Tower, service control policies [SCPs])

• Determining the appropriate use of resource policies for AWS services • Determining when to federate a directory service with IAM roles

Knowledge of:

• Application configuration and credentials security • AWS service endpoints • Control ports, protocols, and network traffic on AWS

• Secure application access • Security services with appropriate use cases (for example, Amazon Cognito, Amazon GuardDuty, Amazon Macie) • Threat vectors external to AWS (for example, DDoS, SQL injection)

Skills in:

• Designing VPC architectures with security components (for example, security groups, route tables, network ACLs, NAT gateways) • Determining network segmentation strategies (for example, using public subnets and private subnets) • Integrating AWS services to secure applications (for example, AWS Shield, AWS WAF, IAM Identity Center, AWS Secrets Manager) • Securing external network connections to and from the AWS Cloud (for example, VPN, AWS Direct Connect)

Knowledge of:

• Data access and governance • Data recovery • Data retention and classification • Encryption and appropriate key management

Skills in:

• Aligning AWS technologies to meet compliance requirements • Encrypting data at rest (for example, AWS KMS) • Encrypting data in transit (for example, AWS Certificate Manager [ACM] using TLS) • Implementing access policies for encryption keys • Implementing data backups and replications • Implementing policies for data access, lifecycle, and protection • Rotating encryption keys and renewing certificates

Knowledge of:

• API creation and management (for example, Amazon API Gateway, REST API) • AWS managed services with appropriate use cases (for example, AWS Transfer Family, Amazon SQS, AWS Secrets Manager) • Caching strategies • Design principles for microservices (for example, stateless workloads compared with stateful workloads) • Event-driven architectures • Horizontal scaling and vertical scaling • How to appropriately use edge accelerators (for example, content delivery network [CDN]) • How to migrate applications into containers • Load balancing concepts (for example, Application Load Balancer [ALB]) • Multi-tier architectures • Queuing and messaging concepts (for example, publish/subscribe) • Serverless technologies and patterns (for example, AWS Fargate, AWS Lambda) • Storage types with associated characteristics (for example, object, file, block) • The orchestration of containers (for example, Amazon ECS, Amazon EKS) • When to use read replicas • Workflow orchestration (for example, AWS Step Functions)

Skills in:

• Designing event-driven, microservice, and/or multi-tier architectures based on requirements

• Determining scaling strategies for components used in an architecture design • Determining the AWS services required to achieve loose coupling based on requirements • Determining when to use containers • Determining when to use serverless technologies and patterns • Recommending appropriate compute, storage, networking, and database technologies based on requirements • Using purpose-built AWS services for workloads

Knowledge of:

• AWS global infrastructure (for example, Availability Zones, AWS Regions, Amazon Route 53) • AWS Managed Services (AMS) with appropriate use cases (for example, Amazon Comprehend, Amazon Polly) • Basic networking concepts (for example, route tables) • Disaster recovery (DR) strategies (for example, backup and restore, pilot light, warm standby, active-active failover, recovery point objective [RPO], recovery time objective [RTO]) • Distributed design patterns • Failover strategies • Immutable infrastructure • Load balancing concepts (for example, ALB) • Proxy concepts (for example, Amazon RDS Proxy) • Service quotas and throttling (for example, how to configure the service quotas for a workload in a standby environment) • Storage options and characteristics (for example, durability, replication) • Workload visibility (for example, AWS X-Ray)

Skills in:

• Determining automation strategies to ensure infrastructure integrity • Determining the AWS services required to provide a highly available and/or fault-tolerant architecture across AWS Regions or Availability Zones

• Identifying metrics based on business requirements to deliver a highly available solution • Implementing designs to mitigate single points of failure • Implementing strategies to ensure the durability and availability of data (for example, backups) • Selecting an appropriate DR strategy to meet business requirements • Using AWS services that improve the reliability of legacy applications and applications not built for the cloud (for example, when application changes are not possible) • Using purpose-built AWS services for workloads

Knowledge of:

• Hybrid storage solutions to meet business requirements • Storage services with appropriate use cases (for example, Amazon S3, Amazon EFS, Amazon EBS) • Storage types with associated characteristics (for example, object, file, block)

Skills in:

• Determining storage services and configurations that meet performance demands • Determining storage services that can scale to accommodate future needs

Knowledge of:

• AWS compute services with appropriate use cases (for example, AWS Batch, Amazon EMR, AWS Fargate) • Distributed computing concepts supported by AWS global infrastructure and edge services

• Queuing and messaging concepts (for example, publish/subscribe)

• Scalability capabilities with appropriate use cases (for example, Amazon EC2 Auto Scaling, AWS Auto Scaling)

• Serverless technologies and patterns (for example, AWS Lambda, Fargate)

• The orchestration of containers (for example, Amazon ECS, Amazon EKS)

Skills in:

• Decoupling workloads so that components can scale independently

• Identifying metrics and conditions to perform scaling actions • Selecting the appropriate compute options and features (for example, EC2 instance types) to meet business requirements

• Selecting the appropriate resource type and size (for example, the amount of Lambda memory) to meet business requirements

Knowledge of:

• AWS global infrastructure (for example, Availability Zones, AWS Regions)

• Caching strategies and services (for example, Amazon ElastiCache)

• Data access patterns (for example, read-intensive compared with write-intensive)

• Database capacity planning (for example, capacity units, instance types, Provisioned IOPS)

• Database connections and proxies • Database engines with appropriate use cases (for example, heterogeneous migrations, homogeneous migrations)

• Database replication (for example, read replicas)

• Database types and services (for example, serverless, relational compared with non-relational, in-memory)

Skills in:

• Configuring read replicas to meet business requirements • Designing database architectures • Determining an appropriate database engine (for example, MySQL compared with PostgreSQL) • Determining an appropriate database type (for example, Amazon Aurora, Amazon DynamoDB) • Integrating caching to meet business requirements

Knowledge of:

• Edge networking services with appropriate use cases (for example, Amazon CloudFront, AWS Global Accelerator) • How to design network architecture (for example, subnet tiers, routing, IP addressing) • Load balancing concepts (for example, Application Load Balancer [ALB]) • Network connection options (for example, AWS VPN, AWS Direct Connect, AWS PrivateLink)

Skills in:

• Creating a network topology for various architectures (for example, global, hybrid, multi-tier) • Determining network configurations that can scale to accommodate future needs • Determining the appropriate placement of resources to meet business requirements • Selecting the appropriate load balancing strategy

Knowledge of:

• Data analytics and visualization services with appropriate use cases (for example, Amazon Athena, AWS Lake Formation, Amazon Quick) • Data ingestion patterns (for example, frequency)

• Data transfer services with appropriate use cases (for example, AWS DataSync, AWS Storage Gateway) • Data transformation services with appropriate use cases (for example, AWS Glue) • Secure access to ingestion access points • Sizes and speeds needed to meet business requirements • Streaming data services with appropriate use cases (for example, Amazon Kinesis)

Skills in:

• Building and securing data lakes • Designing data streaming architectures • Designing data transfer solutions • Implementing visualization strategies • Selecting appropriate compute options for data processing (for example, Amazon EMR) • Selecting appropriate configurations for ingestion • Transforming data between formats (for example, .csv to .parquet)

Knowledge of:

• Access options (for example, an S3 bucket with Requester Pays object storage) • AWS cost management service features (for example, cost allocation tags, multi-account billing) • AWS cost management tools with appropriate use cases (for example, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Report)

• AWS storage services with appropriate use cases (for example, Amazon FSx, Amazon EFS, Amazon S3, Amazon EBS) • Backup strategies • Block storage options (for example, hard disk drive [HDD] volume types, solid state drive [SSD] volume types) • Data lifecycles • Hybrid storage options (for example, AWS DataSync, AWS Transfer Family, AWS Storage Gateway) • Storage access patterns • Storage tiering (for example, cold tiering for object storage) • Storage types with associated characteristics (for example, object, file, block)

Skills in:

• Designing appropriate storage strategies (for example, batch uploads to Amazon S3 compared with individual uploads) • Determining the correct storage size for a workload • Determining the lowest cost method of transferring data for a workload to AWS storage • Determining when storage auto scaling is required • Managing S3 object lifecycles • Selecting the appropriate backup and/or archival solution • Selecting the appropriate service for data migration to storage services • Selecting the appropriate storage tier • Selecting the correct data lifecycle for storage • Selecting the most cost-effective storage service for a workload

Knowledge of:

• AWS cost management service features (for example, cost allocation tags, multi-account billing) • AWS cost management tools with appropriate use cases (for example, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Report)

• AWS global infrastructure (for example, Availability Zones, AWS Regions) • AWS purchasing options (for example, Spot Instances, Reserved Instances, Savings Plans) • Distributed compute strategies (for example, edge processing) • Hybrid compute options (for example, AWS Outposts) • Instance types, families, and sizes (for example, memory optimized, compute optimized, virtualization) • Optimization of compute utilization (for example, containers, serverless computing, microservices) • Scaling strategies (for example, auto scaling, hibernation)

Skills in:

• Determining an appropriate load balancing strategy (for example, Application Load Balancer [Layer 7] compared with Network Load Balancer [Layer 4] compared with Gateway Load Balancer) • Determining appropriate scaling methods and strategies for elastic workloads (for example, horizontal compared with vertical, EC2 hibernation) • Determining cost-effective AWS compute services with appropriate use cases (for example, AWS Lambda, Amazon EC2, AWS Fargate) • Determining the required availability for different classes of workloads (for example, production workloads, non-production workloads) • Selecting the appropriate instance family for a workload • Selecting the appropriate instance size for a workload

Knowledge of:

• AWS cost management service features (for example, cost allocation tags, multi-account billing) • AWS cost management tools with appropriate use cases (for example, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Report) • Caching strategies • Data retention policies

• Database capacity planning (for example, capacity units) • Database connections and proxies

• Database engines with appropriate use cases (for example, heterogeneous migrations, homogeneous migrations)

• Database replication (for example, read replicas)

• Database types and services (for example, relational compared with non-relational, Amazon Aurora, Amazon DynamoDB)

Skills in:

• Designing appropriate backup and retention policies (for example, snapshot frequency)

• Determining an appropriate database engine (for example, MySQL compared with PostgreSQL) • Determining cost-effective AWS database services with appropriate use cases (for example, DynamoDB compared with Amazon RDS, serverless)

• Determining cost-effective AWS database types (for example, time series format, columnar format)

• Migrating database schemas and data to different locations and/or different database engines

Knowledge of:

• AWS cost management service features (for example, cost allocation tags, multi-account billing)

• AWS cost management tools with appropriate use cases (for example, AWS Cost Explorer, AWS Budgets, AWS Cost and Usage Report)

• Load balancing concepts (for example, Application Load Balancer [ALB])

• NAT gateways (for example, NAT instance costs compared with NAT gateway costs) • Network connectivity (for example, private lines, dedicated lines, VPNs)

• Network routing, topology, and peering (for example, AWS Transit Gateway, VPC peering)

• Network services with appropriate use cases (for example, DNS)

Skills in:

• Configuring appropriate NAT gateway types for a network (for example, a single shared NAT gateway compared with NAT gateways for each Availability Zone) • Configuring appropriate network connections (for example, AWS Direct Connect compared with VPN compared with internet) • Configuring appropriate network routes to minimize network transfer costs (for example, Region to Region, Availability Zone to Availability Zone, private to public, AWS Global Accelerator, VPC endpoints) • Determining strategic needs for content delivery networks (CDNs) and edge caching • Reviewing existing workloads for network optimizations • Selecting an appropriate throttling strategy • Selecting the appropriate bandwidth allocation for a network device (for example, a single VPN compared with multiple VPNs, Direct Connect speed)