nxtgauge-gitops/docs/PROJECT_STATUS_SUMMARY.md

Project Status Summary - Nxtgauge Infrastructure

Last Updated

2026-06-15

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What Has Been Completed

1. LiteLLM AI Gateway Deployment ✅

• Status: Fully deployed and working
• Namespace: nxtgauge-ai
• Service: litellm.nxtgauge-ai.svc.cluster.local:4000
• Ingress: https://llm.nxtgauge.com (TLS via cert-manager)
• Models configured:
  • askash-fast → qwen3:4b (fast, 2.5GB)
  • askash-main → qwen3:8b (powerful, 5.2GB)
  • Plus 10 specialized model aliases for different use cases
• Security: API key required via LITELLM_MASTER_KEY
• Ollama: Remains internal-only, NOT exposed publicly
• Files created:
  • apps/litellm/base/configmap.yaml
  • apps/litellm/base/deployment.yaml
  • apps/litellm/base/service.yaml
  • apps/litellm/base/ingress.yaml
  • apps/litellm/base/secret.yaml
  • apps/litellm/base/ratelimit.yaml
  • apps/litellm/base/kustomization.yaml
  • apps/litellm/README.md
  • apps/litellm/OPENCODE_CONNECT.md

2. Kubernetes Cluster Expansion ✅

• Added 4th worker node: nxtgauge-4 / Ramaris (89.167.0.148)
• All nodes labeled with character names:
  • nxtgauge-1 → Rimuru (control plane)
  • nxtgauge-2 → Veldora (worker)
  • nxtgauge-3 → Diablo (worker)
  • nxtgauge-4 → Ramaris (worker)
• All nodes Ready and schedulable

3. GHCR Registry Authentication ✅

• Created ghcr-regcred secret in nxtgauge and nxtgauge-ai namespaces
• Updated registries.yaml on all K3s nodes to authenticate with GHCR
• Restarted K3s services on all nodes
• All deployments now pulling images successfully from GitHub Container Registry

4. Latest Code Deployed via GitHub Actions + Flux ✅

All four repositories are live with their latest commits:

Repository	Branch	Commit	Status
nxtgauge-frontend-solid	high-performance	3b8f75d feat: add AI usage widget to user dashboard	✅ Deployed
nxtgauge-admin-solid	high-performance	f511a3c feat: add AI management page to admin panel	✅ Deployed
nxtgauge-ai-assistant	main	4505d89 feat: add Ask Ash AI assistant implementation	✅ Deployed
nxtgauge-backend-rust	high-performance	ba63736 feat: add AI management endpoints and LiteLLM support	✅ Deployed

• Flux synced to latest gitops commit c5b32538
• 22/22 deployments ready

5. Ollama Models Downloaded ✅

• gemma3:270m (291 MB) - original model
• qwen3:4b (2.5 GB) - fast/general use
• qwen3:8b (5.2 GB) - powerful/long-form generation

6. OpenCode Configuration ✅

• Updated OpenCode binary from 1.14.20 → 1.17.7
• Reverted config back to use Ollama Cloud with Kimi K2.7
• Config file: ~/.config/opencode/opencode.jsonc

7. AI Plans Implementation Plan ✅

• Created detailed implementation plan:
  • docs/AI_PLANS_IMPLEMENTATION_PLAN.md
  • docs/AI_PLANS_FINAL_PLAN.md
• Plan covers:
  • Database schema
  • Plan tiers (Free/Pro/Business/Enterprise)
  • API key generation
  • Usage tracking
  • Rate limiting
  • Model access control
  • Backend services architecture
  • API endpoints
  • Frontend integration
  • Deployment steps

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What We Are Stuck At / Blocked On

1. PostgreSQL for LiteLLM (Optional Advanced Tracking)

• Status: Attempted but not critical
• Issue: Tried to deploy PostgreSQL in nxtgauge-ai namespace for LiteLLM's built-in virtual key tracking, but it failed to schedule on the new node due to Longhorn CSI driver not being available on nxtgauge-4
• Impact: LOW - This is not required. We are building our own API key/usage tracking system instead.
• Decision: Skip LiteLLM-native virtual keys. Use custom backend implementation.

2. AI Plans Implementation ✅

• Status: Core backend implementation complete
• Completed: Database migration, models, repositories, core services, LiteLLM integration, endpoint wiring, admin endpoints, cron jobs, AI credit packages, auto-apply/auto-request log endpoints
• Remaining: Kubernetes env-var wiring (AI_CREDIT_ADMIN_TOKEN), real payment gateway integration, automated integration tests
• Next step: Apply migrations in target environment and configure Kubernetes secrets

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Current System Health

Component	Status
Kubernetes cluster	✅ 4 nodes Ready
Flux GitOps	✅ Synced
All 22 deployments	✅ Running
LiteLLM gateway	✅ Running
Ollama	✅ Running
AI Assistant	✅ Running
Frontend	✅ Running
Admin panel	✅ Running
19 backend rust services	✅ Running

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Decisions Made

1. ✅ Using GitHub Container Registry (GHCR) instead of registry.nxtgauge.com
2. ✅ Using GitHub Actions + Flux instead of Forgejo/Gitea
3. ✅ Using custom API key/usage tracking instead of LiteLLM Enterprise
4. ✅ Using qwen3:4b as main fast model and qwen3:8b for long-form/power tasks
5. ✅ Keeping Ollama internal-only, exposing only LiteLLM
6. ✅ OpenCode using Ollama Cloud Kimi K2.7

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Next Recommended Actions

1. Run database migrations for AI plans and credit packages (cargo run -p db-migrate or sqlx migrate run)
2. Configure AI_CREDIT_ADMIN_TOKEN secret for payments service to credit AI credits via users admin endpoint
3. Add LITELLM_BASE_URL env var for users service (default already points to cluster local service)
4. Credit purchase flow — integrate real payment gateway with /api/admin/ai/users/{id}/credits
5. Add monitoring/alerting for AI usage and credit thresholds

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Key Files and Commands

Useful Commands

# Check cluster nodes
kubectl get nodes -o custom-columns='NAME:.metadata.name,CHARACTER:.metadata.labels.node-name,ROLE:.metadata.labels.node-role\.kubernetes\.io/worker,STATUS:.status.conditions[-1].type,IP:.status.addresses[0].address'

# Check deployments
kubectl get deployments -n nxtgauge

# Check AI namespace
kubectl get pods -n nxtgauge-ai

# Check LiteLLM models
curl http://litellm.nxtgauge-ai.svc.cluster.local:4000/v1/models \
  -H "Authorization: Bearer sk-litellm-prod-1c66d63e701c32cd85922a62fd2e087469486a9b7a34d950423a8726d0aceec9"

# Check Flux status
flux get kustomizations --all-namespaces

# Get LiteLLM master key
kubectl get secret litellm-secrets -n nxtgauge-ai -o jsonpath='{.data.LITELLM_MASTER_KEY}' | base64 -d

Important Paths

• GitOps repo: /home/ashwin/nxtgauge-gitops
• Frontend repo: /home/ashwin/nxtgauge-projects/nxtgauge-frontend-solid
• Backend repo: /home/ashwin/nxtgauge-projects/nxtgauge-backend-rust
• Admin repo: /home/ashwin/nxtgauge-projects/nxtgauge-admin-solid
• AI Assistant repo: /home/ashwin/nxtgauge-projects/nxtgauge-ai-assistant
• AI plans plan: /home/ashwin/nxtgauge-gitops/docs/AI_PLANS_FINAL_IMPLEMENTATION.md

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Blockers Requiring User Input

None currently. Core AI plans implementation is complete on the backend.

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Notes

• The PostgreSQL deployment attempt left a postgres-pvc in nxtgauge-ai namespace. It can be cleaned up safely since we are not using it.
• No git commits have been made during recent infrastructure changes unless explicitly requested.
• All changes were applied directly to Kubernetes and config files.
• Local .opencode plugin was updated, but OpenCode binary upgrade was done via built-in opencode upgrade command.