# Content Domain 3: Design High-Performing Architectures
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**Topics**
+ [Task 3.1: Determine high-performing and/or scalable storage solutions](#solutions-architect-associate-03-domain3-task1)
+ [Task 3.2: Design high-performing and elastic compute solutions](#solutions-architect-associate-03-domain3-task2)
+ [Task 3.3: Determine high-performing database solutions](#solutions-architect-associate-03-domain3-task3)
+ [Task 3.4: Determine high-performing and/or scalable network architectures](#solutions-architect-associate-03-domain3-task4)
+ [Task 3.5: Determine high-performing data ingestion and transformation solutions](#solutions-architect-associate-03-domain3-task5)

## Task 3.1: Determine high-performing and/or scalable storage solutions
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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

## Task 3.2: Design high-performing and elastic compute solutions
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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

## Task 3.3: Determine high-performing database solutions
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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

## Task 3.4: Determine high-performing and/or scalable network architectures
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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)
+ 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

## Task 3.5: Determine high-performing data ingestion and transformation solutions
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Knowledge of:
+ Data analytics and visualization services with appropriate use cases (for example, Amazon Athena, AWS Lake Formation, Amazon QuickSuite)
+ 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)