Day 113: Implementing Tiered Storage for Log Data

By Drew Dru October 22, 2025
Automatic Movement of Logs Between Storage Tiers
Day 113: Implementing Tiered Storage for Log Data

Day 113: Implementing Tiered Storage for Log Data

Working Code Demo:

Today's Build Agenda

You'll implement an intelligent tiered storage system that automatically moves log data across four storage tiers based on age, access patterns, and cost optimization. This enterprise-grade feature reduces storage costs by 60-80% while maintaining query performance.

What We're Building:

  • Hot Tier: Recent logs (0-7 days) on high-performance SSD storage
  • Warm Tier: Moderately accessed logs (7-30 days) on standard storage
  • Cold Tier: Rarely accessed logs (30-365 days) on low-cost storage
  • Archive Tier: Long-term retention logs (365+ days) on tape/glacier storage
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    • Core Concepts: Intelligent Data Lifecycle Management

    Tiered storage transforms static data storage into a dynamic, cost-aware system. Instead of keeping all logs on expensive high-performance storage, data automatically migrates based on access patterns and business rules.

    Key Design Principles:

  • Performance Degradation Acceptance: Newer logs need millisecond access, older logs can tolerate seconds
  • Cost Optimization: Storage costs decrease by 90% from hot to archive tiers
  • Transparent Migration: Applications continue working without knowing data location
  • Policy-Driven Movement: Business rules, not technical constraints, drive data movement

    • Real-world impact: Netflix saves millions annually by moving viewing logs from expensive NVMe storage to glacier archives after 90 days, while keeping recent data hot for recommendation algorithms.

  • * *

    • Context in Distributed Systems

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    ](https://substackcdn.com/image/fetch/$s!jQ3f!,fauto,qauto:good,flprogressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F1a140536-2119-4124-ad8e-192ed08c3564_691x493.png)

    Tiered storage sits at the intersection of storage management, cost optimization, and performance engineering. In distributed log processing, it enables horizontal scaling without linear cost increases.

    System Integration Points:

  • Query Router: Determines which tier contains requested data
  • Storage Controller: Manages data movement between tiers
  • Metadata Index: Tracks data location and access patterns
  • Policy Engine: Evaluates migration rules and schedules transfers

    • Your tiered storage integrates with previous components: authentication (Day 112) ensures only authorized users access archived data, while upcoming lifecycle policies (Day 114) will define retention rules across tiers.

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    • [Read more](https://sdcourse.substack.com/p/day-113-implementing-tiered-storage)

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