MLSUS03-BP02 Implement data lifecycle policies aligned with your sustainability goals
Classify your data to identify its business relevance and implement efficient storage strategies that support your sustainability goals. By understanding your data's importance, you can appropriately tier storage, implement retention policies, and manage the entire lifecycle to reduce your environmental footprint while meeting business requirements.
Desired outcome: You have a comprehensive data management strategy that classifies data based on business importance and implements automatic storage optimization. Your workloads store data in the most energy-efficient storage tiers possible, and data that no longer serves a business purpose is automatically purged, resulting in minimal storage footprint and reduced environmental impact.
Common anti-patterns:
-
Storing data indefinitely without classification or lifecycle policies.
-
Using a single storage tier for data regardless of access patterns.
-
Manually managing data retention and deletion.
-
Keeping redundant or obsolete data that no longer serves business purposes.
Benefits of establishing this best practice:
-
Reduced storage infrastructure and energy consumption.
-
Improved data governance and adherence.
-
Enhanced system performance with streamlined data management.
Level of risk exposed if this best practice is not established: Medium
Implementation guidance
Implementing data lifecycle policies begins with understanding the relationship between your data and business outcomes. Each category of data has different requirements for retention, access patterns, and eventual disposal. By aligning these requirements with sustainability goals, you can optimize storage utilization while improving business continuity.
Start by creating a data classification framework that categorizes data based on its criticality, frequency of access, and business value over time. This classification will guide your decisions about which storage tiers to use and when data should be moved or deleted. For instance, frequently accessed operational data might remain in high-performance storage, while rarely accessed archival data can be moved to more energy-efficient cold storage options.
Once you've classified your data, use AWS storage features like S3 Lifecycle policies to automate data transitions between storage tiers and eventual deletion. For example, you can configure policies that automatically transition data from S3 Standard to S3 Intelligent-Tiering, S3 Standard-IA, S3 One Zone-IA, and eventually to Amazon Glacier or S3 Glacier Deep Archive based on access patterns and age.
Implementation steps
-
Define your data classification framework. Develop a comprehensive data classification system that categorizes data based on business importance, access frequency, and regulatory requirements. Include clear definitions for each data category and establish ownership for classification decisions.
-
Map retention requirements to data classes. For each data classification, determine appropriate retention periods that satisfy business needs, regulatory requirements, and sustainability goals. Document these requirements to guide policy implementation.
-
Analyze current storage usage patterns. Use Amazon S3 Storage Lens
to gain visibility into your current storage usage patterns, identifying opportunities for optimization and tracking progress on storage efficiency metrics. -
Implement S3 Lifecycle policies. Configure Amazon S3 Lifecycle policies to automatically transition data between storage classes and enforce deletion timelines based on your defined retention requirements.
-
Deploy intelligent storage tiering. Implement Amazon S3 Intelligent-Tiering storage class
to automatically move data between access tiers based on changing access patterns, optimizing for both cost and sustainability. -
Establish monitoring and reporting. Create dashboards to track storage optimization metrics, including total storage used, storage class distribution, and lifecycle transition metrics. Regularly review these metrics to identify further optimization opportunities.
-
Continuously refine data classification. Review and update your data classification framework regularly to align it with evolving business needs and sustainability goals.
Resources
Related documents:
