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j
2026-03-17 23:41:46 +13:00
parent fca9167883
commit ab01d81795
10 changed files with 0 additions and 590 deletions
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11
llamacpp-monitor/config/service.env
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# Service settings specific to this server
# (can also override anything in the template_info.env file)
# URL of the llama.cpp server to monitor
LLAMA_SERVER_URL="http://localhost:8080"
# Port to serve the monitor dashboard on
MONITOR_PORT=80
# Server Settings
SSH_USER="root"

16
llamacpp-monitor/install.sh
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#!/bin/bash
source "${AGENT_PATH}/common.sh"
_check_required_env_vars "CONTAINER_NAME" "IMAGE_REGISTRY" "IMAGE_REPO" "IMAGE_TAG"
echo "Pulling image ${IMAGE_REGISTRY}/${IMAGE_REPO}:${IMAGE_TAG}..."
docker pull "$IMAGE_REGISTRY/$IMAGE_REPO:$IMAGE_TAG" || _die "Failed to pull image $IMAGE_REGISTRY/$IMAGE_REPO:$IMAGE_TAG"
echo "Stopping and removing any existing container..."
_stop_container $CONTAINER_NAME
_remove_container $CONTAINER_NAME || _die "Failed to remove container ${CONTAINER_NAME}"
echo "Starting container..."
bash ./start.sh || _die "Failed to start container ${CONTAINER_NAME}"
echo "Installation complete for service ${CONTAINER_NAME}."
echo "Dashboard available at http://${HOST_NAME}:${MONITOR_PORT}"

8
llamacpp-monitor/logs.sh
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#!/bin/bash
source "${AGENT_PATH}/common.sh"
_check_required_env_vars "CONTAINER_NAME"
echo "Showing logs for ${CONTAINER_NAME}... (Press Ctrl+C to stop)"
_grey_start
_get_container_logs $CONTAINER_NAME
_grey_end

465
llamacpp-monitor/monitor.py
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#!/usr/bin/env python3
"""llama.cpp monitor - lightweight diagnostics dashboard."""
import http.server
import json
import os
import re
import subprocess
import time
import urllib.error
import urllib.request
LLAMA_SERVER_URL = os.environ.get("LLAMA_SERVER_URL", "http://localhost:8080")
MONITOR_PORT = int(os.environ.get("MONITOR_PORT", "80"))
def get_gpu_stats():
try:
result = subprocess.run(
["nvidia-smi",
"--query-gpu=utilization.gpu,memory.used,memory.total,temperature.gpu,power.draw,power.limit,fan.speed,name",
"--format=csv,noheader,nounits"],
capture_output=True, text=True, timeout=5
)
if result.returncode == 0:
parts = [p.strip() for p in result.stdout.strip().split(",")]
return {
"available": True,
"utilization": float(parts[0]),
"memory_used": float(parts[1]),
"memory_total": float(parts[2]),
"temperature": float(parts[3]),
"power_draw": float(parts[4]),
"power_limit": float(parts[5]),
"fan_speed": float(parts[6]),
"name": parts[7],
}
except Exception:
pass
return {"available": False}
def fetch_json(path):
try:
req = urllib.request.urlopen(f"{LLAMA_SERVER_URL}{path}", timeout=3)
return json.loads(req.read())
except Exception:
return None
def fetch_text(path):
try:
req = urllib.request.urlopen(f"{LLAMA_SERVER_URL}{path}", timeout=3)
return req.read().decode()
except Exception:
return None
def parse_prometheus(text):
if not text:
return {}
metrics = {}
for line in text.strip().split("\n"):
if line.startswith("#"):
continue
m = re.match(r'^([\w:]+)(?:\{[^}]*\})?\s+([\d.eE+-]+)', line)
if m:
key, val = m.group(1), m.group(2)
try:
metrics[key] = float(val)
except ValueError:
pass
return metrics
def get_all_stats():
gpu = get_gpu_stats()
health = fetch_json("/health")
slots = fetch_json("/slots")
model = fetch_json("/v1/models")
metrics = parse_prometheus(fetch_text("/metrics"))
return {
"timestamp": time.time(),
"gpu": gpu,
"health": health,
"slots": slots,
"model": model,
"metrics": metrics,
"llama_url": LLAMA_SERVER_URL,
}
DASHBOARD_HTML = r"""<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>llama.cpp Monitor</title>
<style>
*{margin:0;padding:0;box-sizing:border-box}
body{background:#0f0f1a;color:#d0d0e0;font-family:'Courier New',monospace;font-size:14px;padding:16px}
h1{font-size:18px;color:#7aa2f7;margin-bottom:12px;display:flex;align-items:center;gap:12px}
h1 .status{font-size:12px;padding:2px 8px;border-radius:4px;font-weight:normal}
h1 .status.ok{background:#1a3a1a;color:#9ece6a}
h1 .status.err{background:#3a1a1a;color:#f7768e}
.grid{display:grid;grid-template-columns:1fr 1fr;gap:12px;margin-bottom:12px}
.card{background:#1a1b2e;border:1px solid #2a2b3e;border-radius:8px;padding:14px}
.card h2{font-size:13px;color:#565f89;text-transform:uppercase;letter-spacing:1px;margin-bottom:10px}
.metric{display:flex;justify-content:space-between;align-items:baseline;margin-bottom:6px}
.metric .label{color:#787c99}
.metric .value{font-size:18px;font-weight:bold;color:#c0caf5}
.metric .unit{font-size:12px;color:#565f89;margin-left:2px}
.bar-wrap{background:#1f2035;border-radius:4px;height:20px;overflow:hidden;margin-bottom:8px}
.bar-fill{height:100%;border-radius:4px;transition:width 0.5s ease}
.bar-fill.mem{background:linear-gradient(90deg,#7aa2f7,#bb9af7)}
.bar-fill.util{background:linear-gradient(90deg,#9ece6a,#e0af68)}
.bar-fill.hot{background:linear-gradient(90deg,#e0af68,#f7768e)}
.spark-wrap{height:50px;margin-top:6px}
canvas{width:100%;height:50px;display:block}
.slots-grid{display:grid;grid-template-columns:repeat(auto-fill,minmax(280px,1fr));gap:8px}
.slot{background:#1f2035;border-radius:6px;padding:10px;border-left:3px solid #565f89}
.slot.active{border-left-color:#9ece6a}
.slot .slot-head{display:flex;justify-content:space-between;margin-bottom:4px}
.slot .slot-state{font-size:11px;padding:1px 6px;border-radius:3px}
.slot .slot-state.idle{background:#1a2a3a;color:#7aa2f7}
.slot .slot-state.processing{background:#1a3a1a;color:#9ece6a}
.metrics-grid{display:grid;grid-template-columns:repeat(auto-fill,minmax(180px,1fr));gap:8px}
.metrics-grid .m-item{background:#1f2035;border-radius:6px;padding:10px;text-align:center}
.metrics-grid .m-val{font-size:20px;font-weight:bold;color:#c0caf5}
.metrics-grid .m-label{font-size:11px;color:#565f89;margin-top:2px}
.full-width{grid-column:1/-1}
.model-info{display:flex;flex-wrap:wrap;gap:16px}
.model-info .mi{display:flex;flex-direction:column}
.model-info .mi .mi-val{font-size:16px;color:#c0caf5;font-weight:bold}
.model-info .mi .mi-label{font-size:11px;color:#565f89}
.no-gpu{color:#565f89;font-style:italic}
</style>
</head>
<body>
<h1>
llama.cpp Monitor
<span class="status" id="srv-status">...</span>
<span style="flex:1"></span>
<span style="font-size:12px;color:#565f89;font-weight:normal" id="srv-url"></span>
</h1>
<div class="grid">
<!-- GPU Utilization -->
<div class="card" id="gpu-card">
<h2>GPU Utilization</h2>
<div id="gpu-util-content">
<div class="metric">
<span class="label">Load</span>
<span><span class="value" id="gpu-util">--</span><span class="unit">%</span></span>
</div>
<div class="bar-wrap"><div class="bar-fill util" id="gpu-util-bar" style="width:0%"></div></div>
<div class="spark-wrap"><canvas id="gpu-util-chart"></canvas></div>
</div>
</div>
<!-- GPU Memory -->
<div class="card">
<h2>GPU Memory</h2>
<div id="gpu-mem-content">
<div class="metric">
<span class="label">Used</span>
<span><span class="value" id="gpu-mem-used">--</span><span class="unit">MiB</span>
/ <span id="gpu-mem-total">--</span><span class="unit">MiB</span></span>
</div>
<div class="bar-wrap"><div class="bar-fill mem" id="gpu-mem-bar" style="width:0%"></div></div>
<div class="spark-wrap"><canvas id="gpu-mem-chart"></canvas></div>
</div>
</div>
<!-- GPU Vitals -->
<div class="card">
<h2>GPU Vitals</h2>
<div id="gpu-vitals-content">
<div class="metric">
<span class="label">Temperature</span>
<span><span class="value" id="gpu-temp">--</span><span class="unit">&deg;C</span></span>
</div>
<div class="bar-wrap"><div class="bar-fill hot" id="gpu-temp-bar" style="width:0%"></div></div>
<div class="metric">
<span class="label">Power</span>
<span><span class="value" id="gpu-power">--</span><span class="unit">W</span>
/ <span id="gpu-power-limit">--</span><span class="unit">W</span></span>
</div>
<div class="metric">
<span class="label">Fan</span>
<span><span class="value" id="gpu-fan">--</span><span class="unit">%</span></span>
</div>
<div class="metric">
<span class="label">GPU</span>
<span style="font-size:12px;color:#787c99" id="gpu-name">--</span>
</div>
</div>
</div>
<!-- Model Info -->
<div class="card">
<h2>Model</h2>
<div class="model-info" id="model-info">
<div class="mi"><span class="mi-val" id="model-name">--</span><span class="mi-label">Model</span></div>
<div class="mi"><span class="mi-val" id="model-params">--</span><span class="mi-label">Parameters</span></div>
<div class="mi"><span class="mi-val" id="model-size">--</span><span class="mi-label">Size</span></div>
<div class="mi"><span class="mi-val" id="model-ctx">--</span><span class="mi-label">Context (train)</span></div>
<div class="mi"><span class="mi-val" id="model-ngl">--</span><span class="mi-label">GPU Layers</span></div>
</div>
</div>
<!-- Throughput Metrics -->
<div class="card full-width">
<h2>Throughput</h2>
<div class="metrics-grid" id="throughput-grid">
<div class="m-item"><div class="m-val" id="m-prompt-tps">--</div><div class="m-label">Prompt tok/s</div></div>
<div class="m-item"><div class="m-val" id="m-gen-tps">--</div><div class="m-label">Generate tok/s</div></div>
<div class="m-item"><div class="m-val" id="m-prompt-tokens">--</div><div class="m-label">Prompt Tokens (total)</div></div>
<div class="m-item"><div class="m-val" id="m-gen-tokens">--</div><div class="m-label">Gen Tokens (total)</div></div>
<div class="m-item"><div class="m-val" id="m-requests">--</div><div class="m-label">Requests</div></div>
<div class="m-item"><div class="m-val" id="m-kv-pct">--</div><div class="m-label">KV Cache Used</div></div>
</div>
</div>
<!-- Slots -->
<div class="card full-width">
<h2>Slots</h2>
<div class="slots-grid" id="slots-container">
<div class="slot"><span class="no-gpu">Waiting for data...</span></div>
</div>
</div>
</div>
<script>
const HISTORY_LEN = 120;
const gpuUtilHistory = [];
const gpuMemHistory = [];
function drawSparkline(canvasId, data, maxVal, color1, color2) {
const canvas = document.getElementById(canvasId);
if (!canvas) return;
const ctx = canvas.getContext('2d');
const dpr = window.devicePixelRatio || 1;
const rect = canvas.getBoundingClientRect();
canvas.width = rect.width * dpr;
canvas.height = rect.height * dpr;
ctx.scale(dpr, dpr);
const w = rect.width, h = rect.height;
ctx.clearRect(0, 0, w, h);
if (data.length < 2) return;
const grad = ctx.createLinearGradient(0, h, 0, 0);
grad.addColorStop(0, color1 + '10');
grad.addColorStop(1, color1 + '40');
const step = w / (HISTORY_LEN - 1);
const startX = w - (data.length - 1) * step;
ctx.beginPath();
ctx.moveTo(startX, h);
for (let i = 0; i < data.length; i++) {
const x = startX + i * step;
const y = h - (data[i] / maxVal) * (h - 4) - 2;
if (i === 0) ctx.lineTo(x, y);
else ctx.lineTo(x, y);
}
ctx.lineTo(startX + (data.length - 1) * step, h);
ctx.closePath();
ctx.fillStyle = grad;
ctx.fill();
ctx.beginPath();
for (let i = 0; i < data.length; i++) {
const x = startX + i * step;
const y = h - (data[i] / maxVal) * (h - 4) - 2;
if (i === 0) ctx.moveTo(x, y);
else ctx.lineTo(x, y);
}
ctx.strokeStyle = color1;
ctx.lineWidth = 1.5;
ctx.stroke();
}
function setText(id, val) {
const el = document.getElementById(id);
if (el && el.textContent !== String(val)) el.textContent = val;
}
function setBar(id, pct) {
const el = document.getElementById(id);
if (el) el.style.width = Math.min(100, Math.max(0, pct)) + '%';
}
function fmtNum(n) {
if (n === null || n === undefined) return '--';
if (n >= 1e9) return (n / 1e9).toFixed(1) + 'B';
if (n >= 1e6) return (n / 1e6).toFixed(1) + 'M';
if (n >= 1e3) return (n / 1e3).toFixed(1) + 'K';
return Math.round(n).toString();
}
function fmtBytes(n) {
if (n === null || n === undefined) return '--';
if (n >= 1e12) return (n / 1e12).toFixed(1) + ' TB';
if (n >= 1e9) return (n / 1e9).toFixed(1) + ' GB';
if (n >= 1e6) return (n / 1e6).toFixed(1) + ' MB';
return Math.round(n).toString() + ' B';
}
function update(data) {
// Server status
const statusEl = document.getElementById('srv-status');
if (data.health && data.health.status === 'ok') {
statusEl.textContent = 'online';
statusEl.className = 'status ok';
} else if (data.health) {
statusEl.textContent = data.health.status || 'unknown';
statusEl.className = 'status err';
} else {
statusEl.textContent = 'offline';
statusEl.className = 'status err';
}
setText('srv-url', data.llama_url || '');
// GPU
const gpu = data.gpu;
if (gpu && gpu.available) {
gpuUtilHistory.push(gpu.utilization);
if (gpuUtilHistory.length > HISTORY_LEN) gpuUtilHistory.shift();
gpuMemHistory.push(gpu.memory_used);
if (gpuMemHistory.length > HISTORY_LEN) gpuMemHistory.shift();
setText('gpu-util', Math.round(gpu.utilization));
setBar('gpu-util-bar', gpu.utilization);
setText('gpu-mem-used', Math.round(gpu.memory_used));
setText('gpu-mem-total', Math.round(gpu.memory_total));
setBar('gpu-mem-bar', (gpu.memory_used / gpu.memory_total) * 100);
setText('gpu-temp', Math.round(gpu.temperature));
setBar('gpu-temp-bar', (gpu.temperature / 100) * 100);
setText('gpu-power', Math.round(gpu.power_draw));
setText('gpu-power-limit', Math.round(gpu.power_limit));
setText('gpu-fan', Math.round(gpu.fan_speed));
setText('gpu-name', gpu.name);
drawSparkline('gpu-util-chart', gpuUtilHistory, 100, '#9ece6a', '#e0af68');
drawSparkline('gpu-mem-chart', gpuMemHistory, gpu.memory_total, '#7aa2f7', '#bb9af7');
} else {
setText('gpu-util', '--');
setText('gpu-name', 'nvidia-smi not available');
}
// Model
if (data.model && data.model.data && data.model.data.length > 0) {
const m = data.model.data[0];
const meta = m.meta || {};
setText('model-name', m.id || '--');
setText('model-params', fmtNum(meta.n_params));
setText('model-size', fmtBytes(meta.size));
setText('model-ctx', fmtNum(meta.n_ctx_train));
}
// Throughput metrics
const met = data.metrics || {};
const now = data.timestamp;
// Use gauge-based tok/s from server (already averaged)
const promptTps = met['llamacpp:prompt_tokens_seconds'];
const genTps = met['llamacpp:predicted_tokens_seconds'];
setText('m-prompt-tps', promptTps !== undefined ? promptTps.toFixed(1) : '--');
setText('m-gen-tps', genTps !== undefined ? genTps.toFixed(1) : '--');
setText('m-prompt-tokens', fmtNum(met['llamacpp:prompt_tokens_total']));
setText('m-gen-tokens', fmtNum(met['llamacpp:tokens_predicted_total']));
setText('m-requests', fmtNum(met['llamacpp:requests_processing']));
setText('m-kv-pct', '--');
// GPU layers from slots
if (data.slots && data.slots.length > 0 && data.slots[0].n_gpu_layers !== undefined) {
setText('model-ngl', data.slots[0].n_gpu_layers);
}
// Slots
const sc = document.getElementById('slots-container');
if (data.slots && data.slots.length > 0) {
let html = '';
for (const s of data.slots) {
const isActive = s.is_processing === true || s.state !== 0;
const stateText = isActive ? 'processing' : 'idle';
const ctxUsed = s.n_past || s.n_predict || 0;
const ctxTotal = s.n_ctx || 0;
const ctxPct = ctxTotal > 0 ? ((ctxUsed / ctxTotal) * 100).toFixed(1) : 0;
html += '<div class="slot ' + (isActive ? 'active' : '') + '">'
+ '<div class="slot-head">'
+ '<span>Slot ' + s.id + '</span>'
+ '<span class="slot-state ' + stateText + '">' + stateText + '</span>'
+ '</div>'
+ '<div class="metric"><span class="label">Context</span>'
+ '<span><span class="value" style="font-size:14px">' + ctxUsed + '</span>'
+ '<span class="unit"> / ' + ctxTotal + ' (' + ctxPct + '%)</span></span></div>'
+ '<div class="bar-wrap"><div class="bar-fill mem" style="width:' + ctxPct + '%;transition:width 0.5s"></div></div>'
+ '</div>';
}
sc.innerHTML = html;
}
}
async function poll() {
try {
const resp = await fetch('/api/stats');
if (resp.ok) {
const data = await resp.json();
update(data);
}
} catch (e) {}
}
poll();
setInterval(poll, 1000);
</script>
</body>
</html>
"""
class Handler(http.server.BaseHTTPRequestHandler):
def do_GET(self):
if self.path == "/" or self.path == "/index.html":
self.send_response(200)
self.send_header("Content-Type", "text/html; charset=utf-8")
self.end_headers()
self.wfile.write(DASHBOARD_HTML.encode())
elif self.path == "/api/stats":
stats = get_all_stats()
self.send_response(200)
self.send_header("Content-Type", "application/json")
self.send_header("Cache-Control", "no-cache")
self.end_headers()
self.wfile.write(json.dumps(stats).encode())
elif self.path == "/health":
self.send_response(200)
self.send_header("Content-Type", "application/json")
self.end_headers()
self.wfile.write(b'{"status":"ok"}')
else:
self.send_response(404)
self.end_headers()
def log_message(self, fmt, *args):
pass # suppress request logging
def main():
server = http.server.HTTPServer(("0.0.0.0", MONITOR_PORT), Handler)
print(f"llama.cpp monitor listening on port {MONITOR_PORT}")
print(f" llama server: {LLAMA_SERVER_URL}")
try:
server.serve_forever()
except KeyboardInterrupt:
pass
server.server_close()
if __name__ == "__main__":
main()

5
llamacpp-monitor/ports.sh
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#!/bin/bash
source "${AGENT_PATH}/common.sh"
_check_required_env_vars "MONITOR_PORT"
echo $MONITOR_PORT

43
llamacpp-monitor/start.sh
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#!/bin/bash
source "${AGENT_PATH}/common.sh"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
_check_required_env_vars "CONTAINER_NAME" "LLAMA_SERVER_URL" "MONITOR_PORT" "IMAGE_REGISTRY" "IMAGE_REPO" "IMAGE_TAG"
# Build GPU device mounts if nvidia-smi is available on the host
GPU_ARGS=""
if command -v nvidia-smi &>/dev/null; then
GPU_ARGS="--device /dev/nvidia0:/dev/nvidia0 \
--device /dev/nvidiactl:/dev/nvidiactl \
--device /dev/nvidia-uvm:/dev/nvidia-uvm \
-v /usr/bin/nvidia-smi:/usr/bin/nvidia-smi:ro \
-v /usr/lib/nvidia:/usr/lib/nvidia:ro \
-e LD_LIBRARY_PATH=/usr/lib/nvidia"
fi
DOCKER_RUN_CMD="docker run -d \
--restart unless-stopped \
--name ${CONTAINER_NAME} \
--network host \
${GPU_ARGS} \
-e LLAMA_SERVER_URL=${LLAMA_SERVER_URL} \
-e MONITOR_PORT=${MONITOR_PORT} \
-v ${SCRIPT_DIR}/monitor.py:/app/monitor.py:ro \
${IMAGE_REGISTRY}/${IMAGE_REPO}:${IMAGE_TAG} \
python3 /app/monitor.py"
echo "Starting container ${CONTAINER_NAME}..."
if ! _create_and_start_container "$DOCKER_RUN_CMD" "$CONTAINER_NAME"; then
if _is_container_exists $CONTAINER_NAME; then
echo "Attempting to get logs from failed container..."
_get_container_logs $CONTAINER_NAME
fi
_die "Failed to start container ${CONTAINER_NAME}"
fi
if ! _is_container_running "$CONTAINER_NAME"; then
_get_container_logs $CONTAINER_NAME
_die "Container ${CONTAINER_NAME} is not running after start attempt"
fi
echo "Service ${CONTAINER_NAME} started on port ${MONITOR_PORT}."

11
llamacpp-monitor/status.sh
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#!/bin/bash
source "${AGENT_PATH}/common.sh"
_check_required_env_vars "CONTAINER_NAME" "MONITOR_PORT"
_is_container_running $CONTAINER_NAME || _die "Service is not running - did not find container $CONTAINER_NAME."
curl -sf http://localhost:${MONITOR_PORT}/health > /dev/null \
|| _die "Service is not healthy - no response from monitor on port ${MONITOR_PORT}."
echo "Service ${CONTAINER_NAME} is healthy."
exit 0

7
llamacpp-monitor/stop.sh
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#!/bin/bash
source "${AGENT_PATH}/common.sh"
_check_required_env_vars "CONTAINER_NAME"
echo "Stopping service ${CONTAINER_NAME}..."
_stop_container $CONTAINER_NAME || _die "Failed to stop container ${CONTAINER_NAME}"
echo "Service ${CONTAINER_NAME} stopped."

17
llamacpp-monitor/template_info.env
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# DO NOT EDIT THIS FILE FOR YOUR SERVICE!
# This file is replaced from the template whenever there is an update.
# Edit the service.env file to make changes.
# Template to use - always required!
TEMPLATE=llamacpp-monitor
REQUIRES_HOST_ROOT=false
REQUIRES_DOCKER=true
REQUIRES_DOCKER_ROOT=true
# Container settings
CONTAINER_NAME="llamacpp-monitor"
# Image settings
IMAGE_REGISTRY="docker.io"
IMAGE_REPO="python"
IMAGE_TAG="3.12-slim"

7
llamacpp-monitor/uninstall.sh
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#!/bin/bash
source "${AGENT_PATH}/common.sh"
_check_required_env_vars "CONTAINER_NAME"
echo "Uninstalling service ${CONTAINER_NAME}..."
_remove_container $CONTAINER_NAME || _die "Failed to remove container ${CONTAINER_NAME}"
echo "Service ${CONTAINER_NAME} uninstalled."