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Multi-Cloud Free Tier RAG Training Platform

Currently under development

GitHub Repo: Multi cloud RAG Free

Oracle 24GB/400GB + GCP/Azure/AWS micros; K8s-federated Haystack/Milvus/Ollama.

##Execution Plan: Multi-Cloud RAG Training Platform (No Spot GPU) Provide pathway to skip GPUs; leverage Oracle free ARM CPUs (4 OCPU/24GB) for inference/fine-tuning (e.g., LoRA on Llama.cpp); GCP/Azure/AWS free micros for redundancy. Total idle cost: $0 (free tiers); scale storage/compute PAYG (pay as you go) minimally on Oracle #2 instance.

Architecture Overview

K8s multi-cluster (OKE/GKE/AKS/EKS free tiers) federated via Rancher; RAG pipeline (Haystack + Milvus + Ollama) via Helm; datasets in buckets; Terraform IaC.

Quickstart

terraform init && apply bash scripts/deploy-rancher.sh helm repo add bitnami https://charts.bitnami.com/bitnami helm install rag-stack helm-charts/rag-stack/ -f helm-charts/values.yaml

Idle: $0. Train LoRA CPU-only. Fork: https://github.com/YOUR/multi-cloud-rag-free Demo: https://YOUR.github.io/multi-cloud-rag-free

Step-by-Step Build (Timings are estimates if you follow the build process and things run flawlessly.)

  1. Signups/Free Tiers (@15-30min): Oracle/GCP/Azure/AWS accounts; enable Always Free (Oracle 2 instances), $300 GCP trial
  2. Terraform Infra (@30-60min): Git clone repo; tf apply for K8s clusters (1 per cloud, free ctrl plane). Oracle: 2x A1.Flex (24GB total). Var: max Oracle PAYG $0.01/hr equiv.
  3. Rancher Federation (@ 20-40min): Deploy Rancher on Oracle cluster (helm install); import GKE/AKS/EKS. Unified dashboard/policy.
  4. RAG Stack Deploy (Helm, @ about 45min):
    • Milvus vector DB: helm install milvus oci://registry-1.docker.io/bitnamicharts/milvus --set persistence.size=200Gi (Oracle vol).
    • Haystack pipeline: NVIDIA Blueprint Helm chart; config ingest/retrieve/generate.
    • Ollama pod: helm install ollama --set model=llama3.1:8b on Oracle ARM. VM to be Linux flavor of user choice that supports dev.
  5. Data/Storage (20min): Buckets (Oracle 10GB free, GCP 5GB); sync datasets via Rclone/MinIO operator.
  6. Ray/Kubeflow (30min): Helm Ray for distributed jobs; autoscaling policy (Oracle priority).
  7. Access/Monitor (15min): Guacamole/Ingress for RDP-like "cloud PC"; Prometheus/Grafana for union view.
  8. Test/Scale (30min): Train sample RAG (e.g., Calgary hikes docs); failover test.

Resource Table

Cloud Role Specs (Free)
Oracle #1/#2 Primary compute/DB 4 OCPU/24GB, 200GB blk x2
GCP Redundancy/ingest e2-micro, 30GB
Azure Backup storage B1s 1GB, 64GB
AWS S3 mirror t4g.nano, 30GB EBS

##Risks/Mitigations

  • Free limits: Policy tags/alerts (Rancher).
  • Latency: Toronto DCs (<50ms Calgary).
  • Cost creep: Budget alarms; Oracle PAYG cap via tf vars.

##Repo Structure

multi-cloud-rag-free
├── README.md
├── terraform/
│ └── main.tf
├── helm-charts/
| └── values.yaml
├── scripts/
│ └── deploy-rancher.sh
├── docs/
│ └── index.html #Github pages root
└── .gitignore

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Multi-Cloud Free Tier RAG Training Platform Oracle 24GB/400GB + GCP/Azure/AWS micros; K8s-federated Haystack/Milvus/Ollama

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