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156 lines
5.6 KiB
Markdown
156 lines
5.6 KiB
Markdown
# Deployment checklist — RAG pipeline (pre-deploy & post-deploy)
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**Purpose:** a short, rigorous checklist to verify your environment and reduce bootstrap/dependency issues during deployment.
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---
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## Before you deploy (pre-flight)
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### 1) Environment & prerequisites
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- Kubernetes cluster accessible; `kubectl` points to correct context.
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```bash
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kubectl config current-context
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kubectl get nodes
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* Ensure cluster resources: CPU / memory / ephemeral storage for vectorstore. Confirm quotas.
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* Secrets: API keys (LLM), db credentials, vectorstore creds in k8s Secret or vault.
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* Helm chart / manifests: reviewed and values set for production (replicas, resources, liveness/readiness).
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### 2) Configuration sanity
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* `values.yaml` contains:
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* `resources.requests` and `limits` for retriever/generator.
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* `replicaCount >= 2` for critical services (if expected load > small).
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* `readinessProbe` and `livenessProbe` configured.
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* Vector store sizing: `index_shards`, disk IOPS, memory (embedding index memory).
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* Network egress rules for model API (if external LLM).
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### 3) Observability & alarms
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* Prometheus scraping configured for app metrics endpoints (`/metrics`).
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* Default dashboards in Grafana (latency, error-rate, retriever QPS, CHR).
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* Alerts configured (see `live_monitoring_rag.md` for suggested alerts).
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---
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## Deploy steps
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1. Create namespace & secrets:
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```bash
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kubectl create ns rag-prod || true
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kubectl -n rag-prod apply -f k8s/secrets.yaml
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```
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2. Install/upgrade Helm chart:
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```bash
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helm upgrade --install rag . -n rag-prod -f values.prod.yaml
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```
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3. Wait for pods to be ready (watch):
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```bash
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kubectl -n rag-prod rollout status deploy/rag-api -w
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kubectl -n rag-prod get pods -o wide
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```
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4. Smoke tests (simple requests):
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```bash
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curl -fsS http://<ingress>/healthz
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curl -fsS -X POST http://<ingress>/api/qa -d '{"qid":"smoke-1","q":"Who is the CEO of WFGY?" }' | jq
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```
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---
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## Post-deploy checks (first 15 minutes)
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* Confirm retriever returns docs for 10 sample queries:
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* Use your `retrieval` debug endpoint to inspect `retrieved_ids`.
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* Confirm p95 E2E latency ≤ target (by env). Collect from Grafana or `kubectl logs`.
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* Confirm CHR on 10 smoke items ≥ expected baseline (manually assert correctness).
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* Check for error spikes in logs:
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```bash
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kubectl -n rag-prod logs -l app=rag --since=10m | egrep "ERROR|WARN" | head -n 200
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```
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---
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## Common config gotchas (double-check)
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* Vectorstore read-only mode accidentally set? (affects writes)
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* LLM rate-limiting / auth errors (wrong key or quota).
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* Wrong index/namespace names between chunker and retriever (off-by-one).
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* Probes misconfigured — containers get restarted continuously.
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---
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## Rollback criteria
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Rollback if any of:
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* P95 > target and sustained for 10m.
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* Error rate > 3× baseline and not transient.
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* Retrieval failures (empty pool) > 1% of requests.
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Rollback command example:
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```bash
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helm rollback rag <previous_revision> -n rag-prod
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```
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---
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### Quick checklist (copy/paste)
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* [ ] Namespace created, secrets applied
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* [ ] Helm values validated (resources, probes)
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* [ ] Prometheus/Grafana dashboards in place
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* [ ] Smoke tests passed (health & basic QA)
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* [ ] Alerts deployed
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* [ ] Canary traffic small → monitor 10–30 min
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---
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### Links
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* Debug playbook → [debug\_playbook.md](./debug_playbook.md)
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* Live monitoring → [live\_monitoring\_rag.md](./live_monitoring_rag.md)
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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|------|------|--------------|
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Layer | Page | What it’s for |
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| --- | --- | --- |
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| ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
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| ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) |
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| ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems |
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| ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) |
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| 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map |
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| 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis |
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| 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map |
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| 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap |
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| 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS |
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| 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control |
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| 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users |
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If this repository helped, starring it improves discovery so more builders can find the docs and tools.
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[](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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