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| .. | ||
| debug_playbook.md | ||
| deployment_checklist.md | ||
| failover_and_recovery.md | ||
| live_monitoring_rag.md | ||
| README.md | ||
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.
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
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.
How to use these runbooks
- Read the deployment checklist before you deploy.
- Use live monitoring to ensure SLOs after deploy.
- If incident happens, follow debug_playbook (triage → isolate → mitigate → fix).
- If controller/broker or core services fail, follow failover_and_recovery.
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).
Where patterns & examples map here
- If retrieval bad → see
ProblemMap/retrieval-collapse.mdand 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.
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.
🔗 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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