Serverga chiqarish: Compose, qayta ishga tushirish va teskari proksi

docker run -d -p 8000:8000 mlops-servis:v1

services:
  servis:
    image: mlops-servis:v1
    container_name: mlops-servis
    restart: unless-stopped          # <-- eng muhim qator
    ports:
      - "18110:8000"
    environment:
      MODEL_YOLI: /app/model.onnx
      BROKER_CHEGARASI: "0.5"
    healthcheck:
      test: ["CMD", "python3", "-c",
             "import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/healthz')"]
      interval: 15s
      timeout: 3s
      retries: 3
      start_period: 10s
    deploy:
      resources:
        limits:
          memory: 512M

python3 -c "
import sys, pathlib; sys.path.insert(0, 'src')
if not pathlib.Path('model.onnx').exists():
    import pandas as pd
    from sklearn.ensemble import RandomForestClassifier
    from sklearn.model_selection import train_test_split
    from quvur.xususiyat import XUSUSIYATLAR, tayyorla
    from quvur.format import onnx_ga
    d = pd.read_csv('../datasets/ijara.csv')
    x, y = tayyorla(d), d['broker']
    Xtr, _, ytr, _ = train_test_split(x, y, test_size=0.25, stratify=y, random_state=42)
    m = RandomForestClassifier(n_estimators=150, min_samples_leaf=3,
                               random_state=42, n_jobs=1).fit(Xtr, ytr)
    onnx_ga(m, len(XUSUSIYATLAR), 'model.onnx')
print('model tayyor')
"
docker images mlops-servis:v1 -q | grep -q . || docker build -q -f Dockerfile.servis -t mlops-servis:v1 . > /dev/null 2>&1
docker compose -f compose.yaml down > /dev/null 2>&1
docker compose -f compose.yaml up -d > /dev/null 2>&1
for i in $(seq 1 40); do
  [ "$(curl -s -o /dev/null -w %{http_code} http://127.0.0.1:18110/healthz 2>/dev/null)" = "200" ] && { echo "servis ${i} urinishda tayyor"; break; }
  sleep 0.5
done
docker compose -f compose.yaml ps --format '{{.Name}}  {{.Status}}' 2>/dev/null

echo "qulashdan oldin:"
docker inspect mlops-servis --format '  holat: {{.State.Status}}  qayta ishga tushish: {{.RestartCount}}'
docker exec mlops-servis kill 1 > /dev/null 2>&1
sleep 8
echo "qulagandan keyin:"
docker inspect mlops-servis --format '  holat: {{.State.Status}}  qayta ishga tushish: {{.RestartCount}}'
for i in $(seq 1 30); do curl -s http://127.0.0.1:18110/healthz > /dev/null 2>&1 && break; sleep 1; done
echo -n "  servis javob beryaptimi: "; curl -s http://127.0.0.1:18110/healthz
echo ""

events {}

http {
  # 29-bobdagi yuk sinovi: cheklovsiz server navbatga to'ladi
  limit_req_zone $binary_remote_addr zone=bashorat:10m rate=30r/s;

  upstream model {
    server servis:8000;
  }

  server {
    listen 80;

    # sog'liq tekshiruvi - cheklovsiz
    location /healthz {
      proxy_pass http://model;
    }

    location / {
      limit_req zone=bashorat burst=20 nodelay;
      limit_req_status 429;

      proxy_pass http://model;
      proxy_set_header Host $host;
      proxy_set_header X-Real-IP $remote_addr;
      proxy_connect_timeout 2s;
      proxy_read_timeout 10s;
    }
  }
}

services:
  servis:
    image: mlops-servis:v1
    restart: unless-stopped
    environment:
      MODEL_YOLI: /app/model.onnx
    expose:
      - "8000"                       # faqat ichki tarmoqqa

  proksi:
    image: nginx:1.27-alpine
    container_name: mlops-proksi
    restart: unless-stopped
    ports:
      - "18120:80"                   # tashqariga FAQAT proksi chiqadi
    volumes:
      - ./nginx.conf:/etc/nginx/nginx.conf:ro
    depends_on:
      - servis

docker compose -f compose.yaml down > /dev/null 2>&1
docker compose -f compose-proksi.yaml up -d > /dev/null 2>&1
for i in $(seq 1 40); do
  [ "$(curl -s -o /dev/null -w %{http_code} http://127.0.0.1:18120/healthz 2>/dev/null)" = "200" ] && { echo "proksi ${i} urinishda tayyor"; break; }
  sleep 0.5
done
echo -n "proksi orqali healthz : "; curl -s http://127.0.0.1:18120/healthz
echo ""
echo -n "proksi orqali bashorat: "
curl -s -X POST http://127.0.0.1:18120/bashorat -H "Content-Type: application/json" -d '{
  "xonalar": 2, "maydon": 55, "qavat": 3, "jami_qavat": 9, "narx_mln": 4.2,
  "tavsif_uzunligi": 60, "rasmlar_soni": 2, "telefon_takrorlanishi": 18,
  "kunlik_elonlar": 9, "egasi_tasdiqlangan": 0}'
echo ""
echo -n "servisga TO'G'RIDAN kirish: "
curl -s -m 3 -o /dev/null -w "HTTP %{http_code}\n" http://127.0.0.1:18110/healthz || echo "ULANIB BO'LMADI (kutilgani)"

python3 -c "
import urllib.request, urllib.error, json
from concurrent.futures import ThreadPoolExecutor
import collections

ELON = {'xonalar': 2, 'maydon': 55, 'qavat': 3, 'jami_qavat': 9, 'narx_mln': 4.5,
        'tavsif_uzunligi': 300, 'rasmlar_soni': 8, 'telefon_takrorlanishi': 4,
        'kunlik_elonlar': 2, 'egasi_tasdiqlangan': 0}
xom = json.dumps(ELON).encode()

def sorov(_):
    r = urllib.request.Request('http://127.0.0.1:18120/bashorat', data=xom,
                               headers={'Content-Type': 'application/json'})
    try:
        with urllib.request.urlopen(r, timeout=10) as j:
            j.read(); return 200
    except urllib.error.HTTPError as e:
        return e.code
    except Exception:
        return 0

with ThreadPoolExecutor(max_workers=60) as ex:
    kodlar = collections.Counter(ex.map(sorov, range(400)))

print('400 ta tez sorov natijasi:')
for k, n in sorted(kodlar.items()):
    nom = {200: 'OK', 429: 'juda kop sorov (cheklov ishladi)', 0: 'ulanmadi'}.get(k, 'boshqa')
    print(f'  HTTP {k}: {n:>4}  {nom}')
"

import pandas as pd
show(pd.DataFrame([
    {"Narsa": "Port", "Bu yerda": "18120", "Haqiqiy serverda": "80 va 443"},
    {"Narsa": "TLS", "Bu yerda": "Yo'q", "Haqiqiy serverda": "Let's Encrypt (certbot)"},
    {"Narsa": "Domen", "Bu yerda": "127.0.0.1", "Haqiqiy serverda": "model.domeningiz.uz"},
    {"Narsa": "Rasm", "Bu yerda": "Mahalliy qurilgan", "Haqiqiy serverda": "Registry dan (31-bob)"},
    {"Narsa": "Yangilash", "Bu yerda": "Qo'lda", "Haqiqiy serverda": "CI/CD (31, 32-bob)"},
    {"Narsa": "Kirish", "Bu yerda": "Ochiq", "Haqiqiy serverda": "Faqat kalit bilan SSH"},
]))

docker compose -f compose-proksi.yaml down > /dev/null 2>&1
docker compose -f compose.yaml down > /dev/null 2>&1
echo "compose xizmatlari to'xtatildi"
docker ps --format '{{.Names}}' | grep -v k3d