deploy-multi.sh.example

#!/usr/bin/env bash
# =============================================================================
# dradis deploy-multi.sh TEMPLATE
# Deploys DRADIS trading containers + Control Tower UI
#
# SETUP:
# 1. Copy this file to deploy-multi.sh and fill in HOST, USER, KEY
# 2. Ensure Docker is installed on the remote server
# 3. Run: chmod +x deploy-multi.sh && ./deploy-multi.sh
#
# Phase 3f-6: Two deployment models are now supported:
#
#   MODEL A — Single container, multi-asset (recommended):
#     One dradis container with ASSETS=btc,eth,sol runs all three market loops
#     concurrently in a single process.  Simpler operations, lower memory.
#     DB covers the primary asset (btc); all assets write CSV metrics.
#
#   MODEL B — Separate containers per asset (legacy, still works):
#     dradis-btc, dradis-eth, dradis-sol each run with CRYPTO_FILTER=<asset>.
#     Full DB persistence per asset, easier per-asset restart.
#     Uncomment the individual docker run blocks below to use this model.
#
# Vipers (seven total): Arbitrage, Momentum, Maker, Basis, TimeDecay, GBoost,
#   TrendCapture.  All are enabled when using config.balanced.rs.example or
#   config.aggressive.rs.example.  Disable individually via Control Tower UI.
#
# Containers started (Model A):
#   dradis          — Rust trading engine (all assets) + axum API on :9000
#   control-tower   — Next.js dashboard on :3002
#
# All containers share the 'dradis-net' Docker network so the UI can reach
# the API at http://dradis:9000 without exposing it on the host.
# =============================================================================

set -euo pipefail

# Load .env so CT_USERNAME / CT_PASSWORD are available for the control-tower container
if [ -f ".env" ]; then
  set -o allexport
  # shellcheck disable=SC1091
  source .env
  set +o allexport
fi

# ⚙️  CUSTOMIZE THESE VALUES FOR YOUR SERVER
HOST="<YOUR_SERVER_IP>"       # e.g. "54.12.34.56" or "myserver.example.com"
USER="<YOUR_USERNAME>"        # e.g. "ubuntu", "ec2-user", "root"
KEY="<PATH_TO_SSH_KEY>"       # e.g. "~/.ssh/id_rsa" or "~/.ssh/my-key.pem"
REMOTE_DIR="~/dradis"         # Remote directory to deploy into

# Optional: SSH port (default 22)
SSH_PORT="22"

echo "🚀 Deploying DRADIS + Control Tower to $HOST..."

# ── 1. Create remote directory structure ──────────────────────────────────────
echo "📁 Creating remote directory structure..."
ssh -i "$KEY" "$USER@$HOST" \
  "mkdir -p $REMOTE_DIR/src \
            $REMOTE_DIR/tests \
            $REMOTE_DIR/control-tower"

# ── 2. Copy Rust source ───────────────────────────────────────────────────────
# Use scp -r so every module file is picked up automatically — no manual list
# to maintain.  New files added during refactoring are included without any
# change to this script.
echo "📤 Copying Rust source (src/ → remote)..."
scp -r -P "$SSH_PORT" -i "$KEY" src "$USER@$HOST:$REMOTE_DIR/"

# Test modules
scp -P "$SSH_PORT" -i "$KEY" tests/toctou.rs   "$USER@$HOST:$REMOTE_DIR/tests/toctou.rs"

# Root files
scp -P "$SSH_PORT" -i "$KEY" .env           "$USER@$HOST:$REMOTE_DIR/.env"
scp -P "$SSH_PORT" -i "$KEY" Cargo.toml     "$USER@$HOST:$REMOTE_DIR/Cargo.toml"
scp -P "$SSH_PORT" -i "$KEY" Cargo.lock     "$USER@$HOST:$REMOTE_DIR/Cargo.lock"
scp -P "$SSH_PORT" -i "$KEY" Dockerfile     "$USER@$HOST:$REMOTE_DIR/Dockerfile"

# ── 3. Copy Control Tower UI source ──────────────────────────────────────────
echo "📤 Copying Control Tower source..."
scp -P "$SSH_PORT" -i "$KEY" control-tower/Dockerfile          "$USER@$HOST:$REMOTE_DIR/control-tower/Dockerfile"
scp -P "$SSH_PORT" -i "$KEY" control-tower/.dockerignore       "$USER@$HOST:$REMOTE_DIR/control-tower/.dockerignore"
scp -P "$SSH_PORT" -i "$KEY" control-tower/package.json        "$USER@$HOST:$REMOTE_DIR/control-tower/package.json"
scp -P "$SSH_PORT" -i "$KEY" control-tower/package-lock.json   "$USER@$HOST:$REMOTE_DIR/control-tower/package-lock.json"
scp -P "$SSH_PORT" -i "$KEY" control-tower/next.config.ts      "$USER@$HOST:$REMOTE_DIR/control-tower/next.config.ts"
scp -P "$SSH_PORT" -i "$KEY" control-tower/tailwind.config.ts  "$USER@$HOST:$REMOTE_DIR/control-tower/tailwind.config.ts"
scp -P "$SSH_PORT" -i "$KEY" control-tower/postcss.config.mjs  "$USER@$HOST:$REMOTE_DIR/control-tower/postcss.config.mjs"
scp -P "$SSH_PORT" -i "$KEY" control-tower/tsconfig.json       "$USER@$HOST:$REMOTE_DIR/control-tower/tsconfig.json"
# Copy entire src tree (app, components, lib) — includes api/[...path]/route.ts
scp -r -P "$SSH_PORT" -i "$KEY" control-tower/src              "$USER@$HOST:$REMOTE_DIR/control-tower/"
# public/ dir (may be empty but must exist for Next.js standalone)
scp -r -P "$SSH_PORT" -i "$KEY" control-tower/public           "$USER@$HOST:$REMOTE_DIR/control-tower/"

# ── 4. Build + deploy all containers in one SSH session ───────────────────────
ssh -p "$SSH_PORT" -i "$KEY" "$USER@$HOST" bash -s -- "$REMOTE_DIR" "${CT_USERNAME:-}" "${CT_PASSWORD:-}" << 'REMOTE'
    set -euo pipefail
    REMOTE_DIR="$1"
    CT_USERNAME="$2"
    CT_PASSWORD="$3"
    cd "$REMOTE_DIR"

    echo "🧹 Stopping old containers..."
    docker stop dradis-btc dradis-eth dradis-sol control-tower ollama 2>/dev/null || true
    docker rm   dradis-btc dradis-eth dradis-sol control-tower ollama 2>/dev/null || true
    # Note: do NOT prune volumes — ollama-models volume holds the downloaded LLM (~4 GB).
    # Pruning it forces a full re-download on every deploy.
    docker system prune -af 2>/dev/null || true

    # Create isolated Docker network so containers talk internally
    docker network create dradis-net 2>/dev/null || true

    # ── Ollama (LLM Advisor backend) ─────────────────────────────────────────
    # Serves the Ollama API at http://ollama:11434 on the dradis-net network.
    # Model files are stored in a named volume so they survive container restarts
    # and re-deploys without a costly re-download.
    #
    # Recommended model: qwen2.5:3b-instruct-q4_K_M (~2 GB, fast CPU inference)
    #   Completes in ~30-60s on t3.large CPU — well within the 360s reqwest timeout.
    #   Alternative: phi3:mini (~2.3 GB, very fast) or mistral:7b-instruct-q4_0 (~4.1 GB, slower).
    #   ⚠️  mistral:7b-instruct-q4_K_M (~4.1 GB) regularly exceeds the 360s timeout on t3.large;
    #       use only on t3.xlarge (4 vCPU / 16 GB RAM) or better.
    # Disable by commenting out this block AND removing OLLAMA_URL from .env.
    echo "🤖 Starting Ollama (LLM Advisor)..."
    docker run -d \
        --restart unless-stopped \
        --name ollama \
        --network dradis-net \
        -v ollama-models:/root/.ollama \
        -p 11434:11434 \
        ollama/ollama

    # Wait for Ollama HTTP API to be ready before issuing pull.
    # docker run -d returns immediately but the server needs a few seconds to init.
    echo "⏳ Waiting for Ollama to be ready..."
    for i in $(seq 1 30); do
        if docker exec ollama curl -sf http://localhost:11434/api/tags > /dev/null 2>&1; then
            echo "✅ Ollama is ready."
            break
        fi
        sleep 2
    done

    # Pull the LLM model only if it is not already present in the ollama-models volume.
    # `ollama list` is a local operation (no registry contact) — if the model shows up, skip.
    # This saves ~2 GB of bandwidth and 2-4 minutes on every deploy after the first.
    # To force a re-pull (e.g. to upgrade to a newer quantization), delete the named volume
    # with:  docker volume rm ollama-models
    echo "📥 Checking for qwen2.5:3b-instruct-q4_K_M in local model cache..."
    if docker exec ollama ollama list 2>/dev/null | grep -q "qwen2.5:3b-instruct-q4_K_M"; then
        echo "✅ Model already cached — skipping pull."
    else
        echo "📥 Model not found — pulling qwen2.5:3b-instruct-q4_K_M (~2 GB)..."
        docker exec ollama ollama pull qwen2.5:3b-instruct-q4_K_M || true
    fi

    echo "🔨 Building DRADIS image..."
    docker build -t dradis .

    echo "🔨 Building Control Tower image..."
    docker build -t dradis-ui control-tower/

    # ── MODEL A: Single container, multi-asset (Phase 3f-6 — recommended) ───────
    # ASSETS=btc,eth,sol runs all three market loops concurrently in one process.
    # DB persists the primary asset (btc); secondary assets use CSV-only metrics.
    #
    # Worker threads: the runtime defaults to the host's core count (floor 2).
    # For 3 concurrent asset loops, provision at least 4 vCPUs and set
    # TOKIO_WORKER_THREADS to the core count (or a bit higher) so the patrol
    # loops don't oversubscribe — e.g. `-e TOKIO_WORKER_THREADS=4` on a t3.xlarge.
    echo "🚀 Starting dradis (BTC+ETH+SOL concurrent, API on :9000)..."
    docker run -d \
        --restart unless-stopped \
        --name dradis \
        --network dradis-net \
        --env-file .env \
        -e ASSETS=btc,eth,sol \
        -e API_PORT=9000 \
        -e TOKIO_WORKER_THREADS=4 \
        -e OLLAMA_URL=http://ollama:11434 \
        -e OLLAMA_MODEL=qwen2.5:3b-instruct-q4_K_M \
        -p 9000:9000 \
        -v $(pwd)/logs:/app/logs \
        dradis

#    # ── MODEL B: Separate containers per asset (legacy — full DB per asset) ────
#    echo "🚀 Starting dradis-btc (BTC filter, API on :9000)..."
#    docker run -d \
#        --restart unless-stopped \
#        --name dradis-btc \
#        --network dradis-net \
#        --env-file .env \
#        -e CRYPTO_FILTER=btc \
#        -e API_PORT=9000 \
#        -e OLLAMA_URL=http://ollama:11434 \
#        -e OLLAMA_MODEL=qwen2.5:3b-instruct-q4_K_M \
#        -p 9000:9000 \
#        -v $(pwd)/logs:/app/logs \
#        dradis
#

    echo "🌐 Starting Control Tower UI (port :3002)..."
    docker run -d \
        --restart unless-stopped \
        --name control-tower \
        --network dradis-net \
        -e DRADIS_API_URL=http://dradis-btc:9000 \
        -e CT_USERNAME="$CT_USERNAME" \
        -e CT_PASSWORD="$CT_PASSWORD" \
        -p 3002:3002 \
        dradis-ui

    echo ""
    echo "✅ Deployment complete!"
    echo "📜 Running containers:"
    docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Ports}}" | grep -E "(dradis|control|ollama)"
    echo ""
    echo "🌐 Control Tower: http://$(hostname -I | awk '{print $1}'):3002"
    echo "📡 DRADIS API:    http://$(hostname -I | awk '{print $1}'):9000/api/health"
    echo "🤖 Ollama API:    http://$(hostname -I | awk '{print $1}'):11434"
REMOTE

echo ""
echo "✅ Deployment complete on $HOST!"
echo "🌐 Control Tower: http://$HOST:3002"
echo "📡 DRADIS API:    http://$HOST:9000/api/health"
echo "🤖 Ollama API:    http://$HOST:11434 (internal-only; not exposed to public)"
echo ""
echo "📜 Tailing BTC logs (Ctrl+C to stop):"
ssh -p "$SSH_PORT" -i "$KEY" "$USER@$HOST" "docker logs -f dradis-btc --tail 30"