retention-archival

id	SKL-retention-RETENTIONARCHIVAL
name	Retention Archival
description	Policy and automation for data retention (how long to keep data), archival (move to cold storage), and deletion (permanently remove). This skill enables compliance with GDPR/CCPA retention limits, cos
version	1.0.0
status	active
owner	@cerebra-team
last_updated	2026-02-22
category	Backend
tags	["api","backend","server","database"]
stack	["Python","Node.js","REST API","GraphQL"]
difficulty	Intermediate

Retention Archival

Skill Profile

(Select at least one profile to enable specific modules)

• DevOps
• Backend
• Frontend
• AI-RAG
• Security Critical

Overview

Policy and automation for data retention (how long to keep data), archival (move to cold storage), and deletion (permanently remove). This skill enables compliance with GDPR/CCPA retention limits, cost optimization through cold storage, improved query performance, and legal right to deletion.

Why This Matters

• Compliance: GDPR, CCPA retention limits
• Cost: Cold storage is cheaper than hot storage
• Performance: Less data = faster queries
• Legal: Right to deletion

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Core Concepts & Rules

1. Core Principles

• Follow established patterns and conventions
• Maintain consistency across codebase
• Document decisions and trade-offs

2. Implementation Guidelines

• Start with the simplest viable solution
• Iterate based on feedback and requirements
• Test thoroughly before deployment

Inputs / Outputs / Contracts

• Inputs:
  • Retention policy configuration
  • Table schemas with retention requirements
  • Archive storage configuration (S3, Glacier)
  • Deletion request data
• Entry Conditions:
  • Archive storage is configured and accessible
  • Database supports partitioning
  • Retention policy is documented and approved
• Outputs:
  • Archived data in cold storage
  • Deleted data from hot storage
  • Audit logs for all operations
  • Retention compliance reports
• Artifacts Required (Deliverables):
  • Retention policy document
  • Archival scripts