Content Domain 3: Cloud Technology and Services - AWS Certification
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.

Content Domain 3: Cloud Technology and Services

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

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, Amazon Kendra)

  • Identifying the services for data analytics (for example, Amazon Athena, Amazon Kinesis, AWS Glue, Amazon QuickSight)

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 and AWS AppSync

  • 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