datadog agent接收指标数据,自己实现server
Posted yaoyu1983
tags:
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datadog agent配置datadog.yaml
dd_url: http://192.168.2.133:31636
重启datadog,service datadog-agent restart
spring boot启动类:
import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.EnableAutoConfiguration; import org.springframework.boot.context.properties.EnableConfigurationProperties; import org.springframework.context.annotation.ComponentScan; import org.springframework.context.annotation.Configuration; @Configuration @EnableAutoConfiguration @EnableConfigurationProperties @ComponentScan public class StartApplication { public static void main(String[] args) throws Exception { SpringApplication.run(StartApplication.class, args); } }
实现controller:
import java.io.ByteArrayOutputStream; import java.io.IOException; import java.util.zip.InflaterInputStream; import javax.servlet.http.HttpServletRequest; import javax.servlet.http.HttpServletResponse; import org.springframework.context.annotation.Description; import org.springframework.stereotype.Controller; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RequestMethod; @Controller @Description("A controller for handling requests for hello messages") public class SampleController { @RequestMapping("/metrics") public String foo() { return "test"; } @RequestMapping(value = { "/api/v1/series" }, method = RequestMethod.POST) public void dataDogRev(HttpServletRequest request, HttpServletResponse response) { try { InflaterInputStream iis = new InflaterInputStream(request.getInputStream()); ByteArrayOutputStream baos = new ByteArrayOutputStream(); byte[] data = new byte[2048]; int len = 0; while ((len = iis.read(data)) > -1) { baos.write(data, 0, len); } String dataStr = new String(baos.toByteArray(), "UTF-8"); System.out.println(dataStr); } catch (IOException e) { e.printStackTrace(); } } }
打印出的agent上报的监控数据,json格式内容如下:
{ "series": [{ "metric": "datadog.trace_agent.stats_writer.stats_buckets", "points": [ [1580960310, 0] ], "tags": ["version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "rate", "interval": 10 }, { "metric": "datadog.trace_agent.receiver.tcp_connections", "points": [ [1580960310, 0] ], "tags": ["status:accepted", "version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "rate", "interval": 10 }, { "metric": "datadog.trace_agent.events.max_eps.sample_rate", "points": [ [1580960310, 1] ], "tags": ["version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "gauge", "interval": 10 }, { "metric": "datadog.trace_agent.trace_writer.traces", "points": [ [1580960310, 0] ], "tags": ["version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "rate", "interval": 10 }, { "metric": "datadog.trace_agent.stats_writer.retries", "points": [ [1580960310, 0] ], "tags": ["version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "rate", "interval": 10 }, { "metric": "datadog.process.agent", "points": [ [1580960310, 1] ], "tags": ["revision:02e0969", "version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "gauge", "interval": 10 }, { "metric": "datadog.trace_agent.stats_writer.encode_ms.count", "points": [ [1580960310, 0.1] ], "tags": ["version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "rate", "interval": 10 }, { "metric": "datadog.trace_agent.events.max_eps.current_rate", "points": [ [1580960310, 0] ], "tags": ["version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "gauge", "interval": 10 }, { "metric": "datadog.trace_agent.receiver.ratelimit", "points": [ [1580960310, 1] ], "tags": ["version:7.16.1"], "host": "feiyongguanli-cmp-monitor-6a063.novalocal", "type": "gauge", "interval": 10 }, { "metric": "datadog.trace_agent.trace_writer.bytes", "points": [ [1580960310, 0] ], "tags": 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当两个自定义指标之间的百分比差异超过指定百分比阈值时创建 Datadog 警报