Platform
Object storage
How object storage supports large artifacts such as snapshots, binaries, and logs, separate from transactional configuration storage.
Design intent
Use this lens when implementing Object storage across a fleet: define clear boundaries, make change snapshot-based, and keep operational signals observable.
- Immutable artifacts support reproducible deployments and audits
- Retention must match incident and compliance needs
- Artifacts must be traceable back to version IDs
What it is
Object storage is used for large, immutable or append-only artifacts: exported snapshots, bundles, logs, and other binary assets.
What belongs in object storage
- Deployment bundles and exported snapshots
- Diagnostic captures and logs that are too large for transactional stores
- Immutable artifacts tied to a version identifier
Design constraints
- Immutable artifacts support reproducible deployments and audits
- Retention must match incident and compliance needs
- Artifacts must be traceable back to version IDs
Architecture at a glance
- Define a stable artifact boundary (what you deploy) and a stable signal boundary (what you observe)
- Treat changes as versioned, testable, rollbackable units
- Use health + telemetry gates to scale safely
Typical workflow
- Define scope and success criteria (what should change, what must stay stable)
- Create or update a snapshot, then validate against a canary environment/site
- Deploy progressively with health/telemetry gates and explicit rollback criteria
- Confirm acceptance tests and operational dashboards before expanding
System boundary
Treat Object storage as a repeatable interface between engineering intent (design) and runtime reality (deployments + signals). Keep site-specific details configurable so the same design scales across sites.
Example artifact
Implementation notes (conceptual)
topic: Object storage
plan: define -> snapshot -> canary -> expand
signals: health + telemetry + events tied to version
rollback: select known-good snapshotWhy it matters
- Scales storage cost-effectively for large artifacts
- Keeps databases focused on transactional workloads
- Enables reliable distribution of deployment bundles
Engineering outcomes
- Immutable artifacts support reproducible deployments and audits
- Retention must match incident and compliance needs
- Artifacts must be traceable back to version IDs
Quick acceptance checks
- Store snapshots/bundles as immutable artifacts with stable naming
- Keep retention policies aligned with audit/incident needs
Common failure modes
- Drift between desired and actual running configuration
- Changes without clear rollback criteria
- Insufficient monitoring for acceptance after rollout
Acceptance tests
- Verify the deployed snapshot/version matches intent (no drift)
- Run a canary validation: behavior, health, and telemetry align with expectations
- Verify rollback works and restores known-good behavior
In the platform
- Store versioned bundles and exported designs
- Archive operational logs and diagnostic captures
- Support content distribution for deployments
Failure modes
- Missing/expired artifacts that break reproducibility
- Inconsistent naming/versioning that makes artifacts hard to trace
- Permissions misconfiguration that blocks edge downloads/uploads
Implementation checklist
- Store snapshots/bundles as immutable artifacts with stable naming
- Keep retention policies aligned with audit/incident needs
- Validate permissions for edge download/upload flows
- Ensure artifacts are traceable back to snapshot/version IDs
Rollout guidance
- Start with a canary site that matches real conditions
- Use health + telemetry gates; stop expansion on regressions
- Keep rollback to a known-good snapshot fast and rehearsed
Acceptance tests
- Verify the deployed snapshot/version matches intent (no drift)
- Run a canary validation: behavior, health, and telemetry align with expectations
- Verify rollback works and restores known-good behavior
Deep dive
Practical next steps
How teams typically apply this in real deployments.
Key takeaways
- Immutable artifacts support reproducible deployments and audits
- Retention must match incident and compliance needs
- Artifacts must be traceable back to version IDs
Checklist
- Store snapshots/bundles as immutable artifacts with stable naming
- Keep retention policies aligned with audit/incident needs
- Validate permissions for edge download/upload flows
- Ensure artifacts are traceable back to snapshot/version IDs
Next steps
Related topics
Deep dive
Common questions
Quick answers that help during commissioning and operations.
What should never be stored only in object storage?
Transactional configuration needed for queries and control plane operations. Use object storage for large artifacts and logs; keep authoritative state in transactional stores.
What breaks reproducibility most often?
Missing or expired artifacts (retention mismatch) and inconsistent naming/versioning. Tie artifacts to version IDs and validate availability during deploy planning.
How do we keep costs predictable?
Use retention tiers and avoid storing high-cardinality telemetry blobs as artifacts. Prefer structured telemetry stores for query workloads.