prom_grafana

assets/service/compose.yml

@@ -2,14 +2,40 @@ name: lec_app
 
 services:
   price-predict:
-    image: estate_model:0
+    image: estate_model:1
     ports:
       - "8001:8000"
     volumes:
       - ./models:/models
 
 
+
   requests:
-    image: test_requests:2
+    image: request_service:3
+    deploy: 
+      replicas: 2
+      restart_policy:
+        condition: always
+        delay: 5s
 
 
+
+  prometheus:
+    image: prom/prometheus
+    ports: 
+      - "9090:9090"
+    command:
+      - '--config.file=/etc/prometheus/prometheus.yml'
+    volumes:
+      - "./prometheus/prometheus.yml:/etc/prometheus/prometheus.yml"
+    hostname: prometheus
+
+  
+  graphana:
+    image: grafana/grafana
+    ports:
+      - "3000:3000"
+    environment:
+        - GF_SECURITY_ADMIN_USER=admin
+        - GF_SECURITY_ADMIN_PASSWORD=admin
+    

assets/service/prometheus/prometheus.yml

@@ -0,0 +1,15 @@
+global:
+  scrape_interval: 15s
+  scrape_timeout: 10s
+  # Каждые 15 секунд будет метрики. Если в течение 10с у него не получится их собрать, то будет прерывание 
+  # по таймауту
+scrape_configs:
+  # имя сборщика
+  - job_name: 'scrapping-main-app'
+   # Сбор будет вестись с сервиса price-predict:8000, страница с метриками, доступ по http.
+    metrics_path: /metrics
+    scheme: http
+    
+    static_configs:
+    - targets:
+      - price-predict:8000

assets/service/requests/req.py

@@ -2,7 +2,6 @@ import requests
 import time
 import random
 
-time.sleep(3)
 for i in range(50):
     params = {'flat_id': i}
     data = {
@@ -18,6 +17,6 @@ for i in range(50):
         "object_type":	1,
         "floor_level":	      "mid"
         } 
-    response = requests.post('http://localhost:8000/api/prediction', params=params, json=data)
-    time.sleep(4)
+    response = requests.post('http://price-predict:8000/api/prediction', params=params, json=data)
+    time.sleep(random.randint(1,5))
     print(response.json())