Part 14 — Infrastructure and Operations

This section covers running memory as infrastructure: deployment models, scaling, backups, HA, APIs, auth, capacity planning, and compliance for long-lived stores.

What you will learn

  • Self-hosted vs managed deployment choices for vector-native memory
  • Backup, restore, disaster recovery, and schema evolution
  • API, auth, rate limiting, and environment separation
  • Cost optimization, multi-region design, and portability concerns

Chapters in this section

There are 18 chapters in this part. Open any chapter to read it on its own, or work through them in order.

  1. 1 Self-Hosted vs Managed Memory Infrastructure
  2. 2 Deployment Models for Vector-Native Memory Systems
  3. 3 Scaling Vector Databases for High-Volume Memory Workloads
  4. 4 Backup and Restore Strategies for Persistent Memory
  5. 5 Disaster Recovery Planning for Memory Infrastructure
  6. 6 Data Migration Between Memory System Versions
  7. 7 High-Availability Design for Memory Services
  8. 8 Rate Limiting and Throttling Memory Write Pipelines
  9. 9 API Design for Memory Services: REST and SDK Patterns
  10. 10 Authentication and API Key Management for Memory Systems
  11. 11 Environment Separation: Staging vs Production Memory Stores
  12. 12 Cost Optimization for Long-Term Memory Storage
  13. 13 Capacity Planning for Growing Memory Volumes
  14. 14 Index Maintenance and Background Optimization
  15. 15 Handling Schema Evolution in Long-Lived Memory Systems
  16. 16 Multi-Region Deployment for Global Agent Memory
  17. 17 Compliance Considerations in Memory Infrastructure
  18. 18 Vendor Lock-In and Portability in Memory Architecture