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Advisory: choosing OCI storage - Block Volume, File Storage, Object Storage tiers or Lustre

A design guide for matching data to OCI storage services. Decide by access method and sharing model, then compare performance, availability scope, snapshots and replication, and cost model. Includes common workload mappings and the traps that cause slow or fragile designs.

Deepak Bhardwaj3 min read

Applies toOCI Block Volume (and boot volumes), OCI File Storage (NFS), OCI Object Storage (Standard, Infrequent Access, Archive tiers), OCI File Storage with Lustre, local NVMe on Dense I/O shapes

By access method

Access Service
Block device for one instance (OS, databases, apps) Block Volume
Shared NFS file system for many clients File Storage
Object API (backups, data lakes, media, logs) Object Storage
Parallel high-throughput file system for HPC/AI File Storage with Lustre (check region availability)
Very low-latency local scratch Local NVMe on Dense I/O shapes (data lost if instance is lost)

Comparison

Block Volume File Storage Object Storage Lustre
Protocol iSCSI / paravirtualized NFSv3 HTTPS (S3-compatible API available) Lustre client
Sharing One instance (shareable volumes for clusters) Many clients Any client Many clients
Scope Availability domain Availability domain Region Availability domain
Performance Set by VPUs and size Scales with data; mount target throughput options High throughput, object latency Very high throughput
Protection Backups, clones, cross-region replication Snapshots, replication Versioning, replication, retention rules Backups/integration per service

Note the AD scope of block and file storage: in multi-AD regions, an instance in AD-2 can't attach a volume from AD-1.

Common mappings

Workload Typical choice
Database on a VM (self-managed) Block Volume (Higher/Ultra High Performance)
Shared web content, home directories, app shared config File Storage
NFS file server replacement File Storage (see the NFS transformation post)
RMAN backups, exports Object Storage (Standard → Archive with lifecycle)
Data lake for analytics Object Storage
AI training data with high read throughput Lustre or Object Storage with caching
Container persistent volumes Block Volume (RWO), File Storage (RWX)

Object Storage tiers

Tier Use
Standard Frequently accessed
Infrequent Access Accessed rarely; retrieval fee and minimum retention apply
Archive Long-term; restore takes hours before reading
Auto-tiering (bucket setting) Moves objects between Standard and Infrequent Access by access pattern

Design questions

  • What protocol does the application use, and can it change?
  • How many clients read and write concurrently?
  • Measured IOPS, throughput and latency at peak?
  • AD-level failure: is the data replicated or backed up elsewhere?
  • Restore granularity (file, volume, object version) and RPO/RTO?
  • Encryption keys: Oracle-managed or customer-managed in Vault?

Traps

Trap Avoid by
File Storage for a database Use block volumes
Assuming block volumes survive AD failure Cross-region/AD replication or backups
Archive tier for data needed quickly in an incident Infrequent Access or Standard
Small-file heavy workloads on NFS without testing Pilot with real data; consider app changes
Local NVMe for data without replication Only scratch or replicated data

Tip

Run a short pilot with real data volumes and client counts. Storage behaviour with many small files and metadata operations rarely matches what the datasheet suggests.

Checklist

  • Access method and sharing model identified
  • Performance measured on the current system
  • Service and tier chosen; AD scope understood
  • Protection, replication and RPO designed
  • Encryption keys decided
  • Pilot with real workload