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Data Retention and Backups for Serverless and Edge

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You are in a sub-page of Cloud_Serverless.
To reorient, go back here:

Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.

A practical policy and runbook to keep your serverless and edge stack recoverable without silent loss, schema drift, or broken RAG indexes. Use this to define retention, automate backups, and verify restores with semantic probes.

Open these first


Core acceptance

  • Retention matrix exists and is live enforced Single sheet that lists every store and log with tier, RPO, retention window, encryption, immutability, and regions.

  • Backups are automated and auditable Success rate ≥ 0.99 over 30 days with proofs. All artifacts have checksums and inventory manifests.

  • Restore drills pass Monthly drill to an isolated project recovers data within RTO and meets RPO. All app health checks pass.

  • Semantic integrity after restore Median ΔS(question, retrieved) ≤ 0.45 on the probe set and coverage ≥ 0.70 to the correct section. λ remains convergent across three paraphrases and two seeds. Open: Retrieval Traceability

  • Security and privacy Backups are encrypted at rest with KMS. Access paths are separate from production roles. Legal holds and deletion pipelines are verified.


Retention matrix template

Store Tier RPO RTO Retention Encryption Immutability Regions Verify
Postgres primary S 5 min 30 min 35 days KMS AES256 PITR logs A, B PITR replay to staging
Vector DB docs-v3 A 24 h 60 min 30 days KMS AES256 Versioned export A, B ΔS and coverage probes
Object store doc-blobs A 1 h 60 min 90 days KMS AES256 Object lock A, B Inventory and checksum
KV session cache B N A 15 min 0 days N A N A A, B Not retained by policy
CDN logs A 24 h 24 h 180 days Provider default WORM if available Multi Export to lake and count

Keep this matrix inside your repo and update during each infra change. Use it as the source of truth during drills.


Backup patterns by datastore

Object stores

  • Enable versioning and object lock where supported.
  • Use lifecycle rules to expire incomplete uploads and previous versions.
  • Export inventory manifests and store checksums next to objects.
  • Replicate to a second region and a second account for blast radius control.

Relational and document databases

  • Combine periodic snapshots with continuous logs for point in time.
  • Keep schema and migration history with every backup set.
  • Restore into an isolated project, then run integrity checks and app probes.

Queues, KV, and cache

  • Do not back up volatile caches. Prove idempotency on replay.
  • For durable queues, export to cold storage before purge. Open: Stateless KV and Queues

Vector stores and embeddings

  • Snapshot with an index manifest: INDEX_HASH, metric, analyzer, model version, chunking recipe.
  • Store snippet and citation schema with the snapshot.
  • After restore, run ΔS and coverage probes and rebuild if mismatched. Open: Embedding ≠ Semantic · Chunking Checklist · Reindex Migration

Edge and CDN

  • Retain raw logs to a data lake for at least 180 days.
  • Keep invalidation logs and request header samples for cache investigations. Open: Edge Cache Invalidation

Restore drill playbook

  1. Provision an isolated target New project, new KMS keys, and no production secrets. Open: Runtime Env Parity

  2. Restore order Secrets and IAM first, then databases, then object stores, then vector indexes. Open: Bootstrap Ordering

  3. Rebuild indexes if needed Compare manifest fields. If metric or analyzer differs, trigger a clean rebuild.

  4. Run probes and health checks App flow checks, ΔS and coverage probes, cache warmup, and p95 latency.

  5. Freeze evidence Store counts, checksums, and probe board CSV. File a retro with gaps and actions.


Common failure smells and the right fix


Verification suite

Counts and constraints

  • Row counts by table, uniques on business keys, foreign key checks.

Checksums

  • Per file and per batch manifests for object stores.

Semantic probes

Operational health


Copy-paste LLM prompt for retention audits

You have TXT OS and the WFGY Problem Map loaded.

Audit my data retention and backups:

- retention matrix rows: [paste table]
- backup logs: [success rate, last artifacts]
- vector index manifests: [INDEX_HASH, metric, analyzer, model]
- legal hold and deletion rules: [one line]

Tell me:
1) gaps vs the matrix and the Problem Map pages to open,
2) restore drill order and the minimal set to verify RPO and RTO,
3) which vector indexes must be rebuilt and why,
4) a short JSON summary with ΔS and coverage medians after restore.
Keep it auditable and short.

🔗 Quick-Start Downloads (60 sec)

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Explore More

Layer Page What it’s for
⭐ Proof WFGY Recognition Map External citations, integrations, and ecosystem proof
⚙️ Engine WFGY 1.0 Original PDF tension engine and early logic sketch (legacy reference)
⚙️ Engine WFGY 2.0 Production tension kernel for RAG and agent systems
⚙️ Engine WFGY 3.0 TXT based Singularity tension engine (131 S class set)
🗺️ Map Problem Map 1.0 Flagship 16 problem RAG failure taxonomy and fix map
🗺️ Map Problem Map 2.0 Global Debug Card for RAG and agent pipeline diagnosis
🗺️ Map Problem Map 3.0 Global AI troubleshooting atlas and failure pattern map
🧰 App TXT OS .txt semantic OS with fast bootstrap
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