SUS03-BP05 Use software patterns and architectures that best support data access and storage patterns

Understand how data is used within your workload, consumed by your users, transferred, and stored. Use software patterns and architectures that best support data access and storage to minimize the compute, networking, and storage resources required to support the workload.

Common anti-patterns:

You assume that all workloads have similar data storage and access patterns.
You only use one tier of storage, assuming all workloads fit within that tier.
You assume that data access patterns will stay consistent over time.
Your architecture supports a potential high data access burst, which results in the resources remaining idle most of the time.

Benefits of establishing this best practice: Selecting and optimizing your architecture based on data access and storage patterns will help decrease development complexity and increase overall utilization. Understanding when to use global tables, data partitioning, and caching will help you decrease operational overhead and scale based on your workload needs.

Level of risk exposed if this best practice is not established: Medium

Implementation guidance

Use software and architecture patterns that aligns best to your data characteristics and access patterns. For example, use modern data architecture on AWS that allows you to use purpose-built services optimized for your unique analytics use cases. These architecture patterns allow for efficient data processing and reduce the resource usage.

Implementation steps

Analyze your data characteristics and access patterns to identify the correct configuration for your cloud resources. Key characteristics to consider include:
- Data type: structured, semi-structured, unstructured
- Data growth: bounded, unbounded
- Data durability: persistent, ephemeral, transient
- Access patterns reads or writes, update frequency, spiky, or consistent
Use architecture patterns that best support data access and storage patterns.
Use technologies that work natively with compressed data.
Use purpose-built analytics services for data processing in your architecture. For detail on AWS purpose-built analytics services, see AWS re:Invent 2022 - Building modern data architectures on AWS.
Use the database engine that best supports your dominant query pattern. Manage your database indexes to ensure efficient querying. For further details, see AWS Databases and AWS re:Invent 2022 - Modernize apps with purpose-built databases.
Select network protocols that reduce the amount of network capacity consumed in your architecture.

Resources

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Document Conventions

SUS03-BP04 Optimize impact on devices and equipment

Data