Data Retention and Backups for Serverless and Edge
March 6, 2026 · View on GitHub
🧭 Quick Return to Map
You are in a sub-page of Cloud_Serverless.
To reorient, go back here:
- Cloud_Serverless — scalable functions and event-driven pipelines
- WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
- WFGY Problem Map 1.0 — 16 reproducible failure modes
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
- Cloud companions: Region Failover Drills · Multi-Region Routing · Blue-Green Switchovers · Canary Release · Edge Cache Invalidation · Stateless KV and Queues · Runtime Env Parity · Egress Rules and Webhooks
- Problem Map anchors: Bootstrap Ordering · Deployment Deadlock · Pre-Deploy Collapse · Retrieval Traceability · Data Contracts · Embedding ≠ Semantic · Chunking Checklist · Reindex Migration
Core acceptance
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Retention matrix exists and is live enforced Single sheet that lists every store and log with tier, RPO, retention window, encryption, immutability, and regions.
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Backups are automated and auditable Success rate ≥ 0.99 over 30 days with proofs. All artifacts have checksums and inventory manifests.
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Restore drills pass Monthly drill to an isolated project recovers data within RTO and meets RPO. All app health checks pass.
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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
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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
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Provision an isolated target New project, new KMS keys, and no production secrets. Open: Runtime Env Parity
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Restore order Secrets and IAM first, then databases, then object stores, then vector indexes. Open: Bootstrap Ordering
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Rebuild indexes if needed Compare manifest fields. If metric or analyzer differs, trigger a clean rebuild.
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Run probes and health checks App flow checks, ΔS and coverage probes, cache warmup, and p95 latency.
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Freeze evidence Store counts, checksums, and probe board CSV. File a retro with gaps and actions.
Common failure smells and the right fix
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Snapshots exist but first call fails after restore → Pre-Deploy Collapse
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Restore works but RAG answers are wrong → Embedding ≠ Semantic and rerun the Chunking Checklist
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Backups succeed but cannot decrypt → Verify KMS policy and run Secrets Rotation
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Different retention across regions → Align with Runtime Env Parity
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Webhook replays create duplicates after restore → Add fences and dedupe keys with Egress Rules and Webhooks
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
- 50 to 200 gold questions, track ΔS and coverage medians and tails. Open: Retrieval Traceability
Operational health
- p95 warm latency and error classes on main routes. Open: Observability and SLO
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)
| Tool | Link | 3-Step Setup |
|---|---|---|
| WFGY 1.0 PDF | Engine Paper | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>” |
| TXT OS (plain-text OS) | TXTOS.txt | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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 |
| 🧰 App | Blah Blah Blah | Abstract and paradox Q&A built on TXT OS |
| 🧰 App | Blur Blur Blur | Text to image generation with semantic control |
| 🏡 Onboarding | Starter Village | Guided entry point for new users |
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