Content Domain 3: Cloud Technology and Services

Domain 3 covers Cloud Technology and Services and represents 34% of the scored content on the exam.

Topics

• Content Domain 3: Cloud Technology and Services
• Task Statement 3.1: Define methods of deploying and operating in the AWS Cloud.
• Task Statement 3.2: Define the AWS global infrastructure.
• Task Statement 3.3: Identify AWS compute services.
• Task Statement 3.4: Identify AWS database services.
• Task Statement 3.5: Identify AWS network services.
• Task Statement 3.6: Identify AWS storage services.
• Task Statement 3.7: Identify AWS artificial intelligence and machine learning (AI/ML) services and analytics services.
• Task Statement 3.8: Identify services from other in-scope AWS service categories.

Task Statement 3.1: Define methods of deploying and operating in the AWS Cloud.

Knowledge of:

• Various ways of provisioning and operating in the AWS Cloud
• Various ways to access AWS services
• Types of cloud deployment models

Skills in:

• Deciding between options such as programmatic access (for example, APIs, SDKs, CLI), the AWS Management Console, and infrastructure as code (IaC)
• Evaluating requirements to determine whether to use one-time operations or repeatable processes
• Identifying deployment models (for example, cloud, hybrid, on-premises)

Task Statement 3.2: Define the AWS global infrastructure.

Knowledge of:

• AWS Regions, Availability Zones, and edge locations
• High availability
• Use of multiple Regions
• Benefits of edge locations

Skills in:

• Describing relationships among Regions, Availability Zones, and edge locations
• Describing how to achieve high availability by using multiple Availability Zones
• Recognizing that Availability Zones do not share single points of failure
• Describing when to use multiple Regions (for example, disaster recovery, business continuity, low latency for end users, data sovereignty)

Task Statement 3.3: Identify AWS compute services.

Knowledge of:

• AWS compute services

Skills in:

• Recognizing the appropriate use of various Amazon EC2 instance types (for example, compute optimized, storage optimized)
• Recognizing the appropriate use of various container options (for example, Amazon Elastic Container Service [Amazon ECS], Amazon Elastic Kubernetes Service [Amazon EKS])
• Recognizing the appropriate use of various serverless compute options (for example, AWS Fargate, AWS Lambda)
• Recognizing that auto scaling provides elasticity
• Identifying the purposes of load balancers

Task Statement 3.4: Identify AWS database services.

Knowledge of:

• AWS database services
• Database migration

Skills in:

• Deciding when to use EC2 hosted databases or AWS managed databases
• Identifying relational databases (for example, Amazon RDS, Amazon Aurora)
• Identifying NoSQL databases (for example, Amazon DynamoDB)
• Identifying memory-based databases (for example, Amazon ElastiCache)
• Identifying database migration tools (for example, AWS Database Migration Service [AWS DMS], AWS Schema Conversion Tool [AWS SCT])

Task Statement 3.5: Identify AWS network services.

Knowledge of:

• AWS network services

Skills in:

• Identifying the components of a VPC (for example, subnets, gateways)
• Understanding security in a VPC (for example, network ACLs, security groups, Amazon Inspector)
• Understanding the purpose of Amazon Route 53
• Identifying network connectivity options to AWS (for example, AWS VPN, AWS Direct Connect)

Task Statement 3.6: Identify AWS storage services.

Knowledge of:

• AWS storage services

Skills in:

• Identifying the uses for object storage
• Recognizing the differences in Amazon S3 storage classes
• Identifying block storage solutions (for example, Amazon Elastic Block Store [Amazon EBS], instance store)
• Identifying file services (for example, Amazon Elastic File System [Amazon EFS], Amazon FSx)
• Identifying cached file systems (for example, AWS Storage Gateway)
• Understanding use cases for lifecycle policies
• Understanding use cases for AWS Backup

Task Statement 3.7: Identify AWS artificial intelligence and machine learning (AI/ML) services and analytics services.

Knowledge of:

• AWS AI/ML services
• AWS analytics services

Skills in:

• Understanding AI/ML services and the tasks that they accomplish (for example, Amazon SageMaker AI, Amazon Lex)
• Identifying the services for data analytics (for example, Amazon Athena, Amazon Kinesis, AWS Glue, Amazon Quick Sight)

Task Statement 3.8: Identify services from other in-scope AWS service categories.

Knowledge of:

• Application integration services of Amazon EventBridge, Amazon Simple Notification Service (Amazon SNS), and Amazon Simple Queue Service (Amazon SQS)
• Business application services of Amazon Connect and Amazon Simple Email Service (Amazon SES)
• Customer enablement services (for example, AWS Support)
• Developer tool services and capabilities (for example, AWS CodeBuild, AWS CodePipeline, and AWS X-Ray)
• End-user computing services of Amazon AppStream 2.0, Amazon WorkSpaces, and Amazon WorkSpaces Secure Browser
• Frontend web and mobile services of AWS Amplify
• IoT services (for example, AWS IoT Core)

Skills in:

• Choosing the appropriate service to deliver messages and to send alerts and notifications
• Choosing the appropriate service to meet business application needs
• Choosing the appropriate option for business support assistance
• Identifying the tools to develop, deploy, and troubleshoot applications
• Identifying the services that can present the output of virtual machines (VMs) on end-user machines
• Identifying the services that can create and deploy frontend and mobile services
• Identifying the services that manage IoT devices