WFGY/ProblemMap/ops

Ops — Deploy & Runbook (Problem Map)

Purpose: this folder contains operational runbooks, checklists and playbooks for deploying, observing, debugging and failing-over RAG pipelines and their surrounding infra.
Target audience: SREs and engineers responsible for production RAG services. Newbie friendly — each section has a checklist and exact commands.

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Quick nav

• Deployment checklist → deployment_checklist.md
• Live monitoring & alerts (RAG) → live_monitoring_rag.md
• Debug playbook (step-by-step) → debug_playbook.md
• Failover & recovery → failover_and_recovery.md

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Scope & assumptions

• Production topology: API gateway → RAG service (retriever + generator + guard) → Vector DB + Source storage.
• Infra: Kubernetes (Helm) or docker-compose for small envs. Prometheus + Grafana for metrics; centralized logs (ELK/Fluentd/Vector).
• Safety-first: ops steps favor read-only diagnostic commands until root cause is clear.

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How to use these runbooks

1. Read the deployment checklist before you deploy.
2. Use live monitoring to ensure SLOs after deploy.
3. If incident happens, follow debug_playbook (triage → isolate → mitigate → fix).
4. If controller/broker or core services fail, follow failover_and_recovery.

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Quick operator checks (first 60s)

• Is service responding? curl -fsS http://$SERVICE/healthz || true
• Are pods healthy? kubectl get pods -n $NS
• Any obvious error spikes in logs (last 1 minute): kubectl logs -n $NS -l app=$APP --since=1m | tail -n 200
• Check key metrics in Prometheus (latency/p95, error rate, retriever QPS).

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Where patterns & examples map here

• If retrieval bad → see ProblemMap/retrieval-collapse.md and examples for vector-store repair.
• If bootstrap ordering failures on start → see ProblemMap/bootstrap-ordering.md & pattern_bootstrap_deadlock.md.
• For memory/state issues → ProblemMap/patterns/pattern_memory_desync.md.

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If you want me to also generate ready-to-apply Kubernetes manifests or Prometheus alerts for your environment (Helm values), I can produce them next — tell me cluster flavor (k8s / k3s / kind / docker-compose) and I’ll adapt.

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🔗 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

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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 based tension engine
Engine	WFGY 2.0	Production tension kernel and math engine for RAG and agents
Engine	WFGY 3.0	TXT based Singularity tension engine, 131 S class set
Map	Problem Map 1.0	Flagship 16 problem RAG failure checklist and fix map
Map	Problem Map 2.0	RAG focused recovery pipeline
Map	Problem Map 3.0	Global Debug Card, image as a debug protocol layer
Map	Semantic Clinic	Symptom to family to exact fix
Map	Grandma’s Clinic	Plain language stories mapped to Problem Map 1.0
Onboarding	Starter Village	Guided tour for newcomers
App	TXT OS	TXT semantic OS, fast boot
App	Blah Blah Blah	Abstract and paradox Q and A built on TXT OS
App	Blur Blur Blur	Text to image with semantic control
App	Blow Blow Blow	Reasoning game engine and memory demo

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