Python prometheus_client使用方式

缺乏、安全感 2023-06-13 12:29 7阅读 0赞

# 背景说明 #

服务部署在阿里云的K8s上，配置了基于Prometheus的Grafana监控。原本用的是自定义的Metrics接口统计，上报一些字段，后面发现Prometheus自带的监控非常全面好用，适合直接抓取统计，所以做了一些改变。

## Python prometheus-client 安装 ##

pip install prometheus-client

## Python封装 ##

# encoding: utf-8
    from prometheus_client import Counter, Gauge, Summary
    from prometheus_client.core import CollectorRegistry
    from prometheus_client.exposition import choose_encoder
    
    
    class Monitor:
        def __init__(self):
        # 注册收集器&最大耗时map
        self.collector_registry = CollectorRegistry(auto_describe=False)
        self.request_time_max_map = {}
    
        # 接口调用summary统计
        self.http_request_summary = Summary(name="http_server_requests_seconds",
                                       documentation="Num of request time summary",
                                       labelnames=("method", "code", "uri"),
                                       registry=self.collector_registry)
        # 接口最大耗时统计
        self.http_request_max_cost = Gauge(name="http_server_requests_seconds_max",
                                      documentation="Number of request max cost",
                                      labelnames=("method", "code", "uri"),
                                      registry=self.collector_registry)
    
        # 请求失败次数统计
        self.http_request_fail_count = Counter(name="http_server_requests_error",
                                          documentation="Times of request fail in total",
                                          labelnames=("method", "code", "uri"),
                                          registry=self.collector_registry)
    
        # 模型预测耗时统计
        self.http_request_predict_cost = Counter(name="http_server_requests_seconds_predict",
                                            documentation="Seconds of prediction cost in total",
                                            labelnames=("method", "code", "uri"),
                                            registry=self.collector_registry)
        # 图片下载耗时统计
        self.http_request_download_cost = Counter(name="http_server_requests_seconds_download",
                                             documentation="Seconds of download cost in total",
                                             labelnames=("method", "code", "uri"),
                                             registry=self.collector_registry)
    
        # 获取/metrics结果
        def get_prometheus_metrics_info(self, handler):
            encoder, content_type = choose_encoder(handler.request.headers.get('accept'))
            handler.set_header("Content-Type", content_type)
            handler.write(encoder(self.collector_registry))
            self.reset_request_time_max_map()
    
        # summary统计
        def set_prometheus_request_summary(self, handler):
            self.http_request_summary.labels(handler.request.method, handler.get_status(), handler.request.path).observe(handler.request.request_time())
            self.set_prometheus_request_max_cost(handler)
    
        # 自定义summary统计
        def set_prometheus_request_summary_customize(self, method, status, path, cost_time):
            self.http_request_summary.labels(method, status, path).observe(cost_time)
            self.set_prometheus_request_max_cost_customize(method, status, path, cost_time)
    
        # 失败统计
        def set_prometheus_request_fail_count(self, handler, amount=1.0):
            self.http_request_fail_count.labels(handler.request.method, handler.get_status(), handler.request.path).inc(amount)
    
        # 自定义失败统计
        def set_prometheus_request_fail_count_customize(self, method, status, path, amount=1.0):
            self.http_request_fail_count.labels(method, status, path).inc(amount)
    
        # 最大耗时统计
        def set_prometheus_request_max_cost(self, handler):
            requset_cost = handler.request.request_time()
            if self.check_request_time_max_map(handler.request.path, requset_cost):
                self.http_request_max_cost.labels(handler.request.method, handler.get_status(), handler.request.path).set(requset_cost)
                self.request_time_max_map[handler.request.path] = requset_cost
    
        # 自定义最大耗时统计
        def set_prometheus_request_max_cost_customize(self, method, status, path, cost_time):
            if self.check_request_time_max_map(path, cost_time):
                self.http_request_max_cost.labels(method, status, path).set(cost_time)
                self.request_time_max_map[path] = cost_time
    
        # 预测耗时统计
        def set_prometheus_request_predict_cost(self, handler, amount=1.0):
            self.http_request_predict_cost.labels(handler.request.method, handler.get_status(), handler.request.path).inc(amount)
    
        # 自定义预测耗时统计
        def set_prometheus_request_predict_cost_customize(self, method, status, path, cost_time):
            self.http_request_predict_cost.labels(method, status, path).inc(cost_time)
    
        # 下载耗时统计
        def set_prometheus_request_download_cost(self, handler, amount=1.0):
            self.http_request_download_cost.labels(handler.request.method, handler.get_status(), handler.request.path).inc(amount)
    
        # 自定义下载耗时统计
        def set_prometheus_request_download_cost_customize(self, method, status, path, cost_time):
            self.http_request_download_cost.labels(method, status, path).inc(cost_time)
    
        # 校验是否赋值最大耗时map
        def check_request_time_max_map(self, uri, cost):
            if uri not in self.request_time_max_map:
                return True
            if self.request_time_max_map[uri] < cost:
                return True
            return False
    
        # 重置最大耗时map
        def reset_request_time_max_map(self):
            for key in self.request_time_max_map:
                self.request_time_max_map[key] = 0.0

## 调用 ##

import tornado
    import tornado.ioloop
    import tornado.web
    import tornado.gen
    from datetime import datetime
    from tools.monitor import Monitor
    
    global g_monitor
    
    class ClassifierHandler(tornado.web.RequestHandler):
        def post(self):
            # TODO Something you need
            # work....
            # 统计Summary，包括请求次数和每次耗时
            g_monitor.set_prometheus_request_summary(self)
            self.write("OK")
    
    
    class PingHandler(tornado.web.RequestHandler):
        def head(self):
            print('INFO', datetime.now(), "/ping Head.")
            g_monitor.set_prometheus_request_summary(self)
            self.write("OK")
    
        def get(self):
            print('INFO', datetime.now(), "/ping Get.")
            g_monitor.set_prometheus_request_summary(self)
            self.write("OK")
    
    
    class MetricsHandler(tornado.web.RequestHandler):
        def get(self):
            print('INFO', datetime.now(), "/metrics Get.")
    		g_monitor.set_prometheus_request_summary(self)
    		# 通过Metrics接口返回统计结果
        	g_monitor.get_prometheus_metrics_info(self)
        
    
    def make_app():
        return tornado.web.Application([
            (r"/ping?", PingHandler),
            (r"/metrics?", MetricsHandler),
            (r"/work?", ClassifierHandler)
        ])
    
    if __name__ == "__main__":
        g_monitor = Monitor()
    	
    	app = make_app()
        app.listen(port)
        tornado.ioloop.IOLoop.current().start()

## Metrics返回结果实例 ##

![Metrics返回结果截图][Metrics]

[Metrics]: https://img-blog.csdnimg.cn/20191117160008811.jpg?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2ppYW9v,size_16,color_FFFFFF,t_70