CSE层监控中心

前提条件

• 已采集CSE日志。
• 日志配置结构化，详情请参见结构化配置。

背景信息

微服务引擎（Cloud Service Engine，CSE），是用于微服务应用的云中间件，支持华为云贡献到Apache社区的注册配置中心Servicecomb引擎和开源增强的注册配置中心Nacos引擎。用户可结合其他云服务，快速构建云原生微服务体系，实现微服务应用的快速开发和高可用运维。

分析网站访问情况

1. 登录云日志服务控制台。
2. 在左侧导航栏中选择“仪表盘 ”。
3. 在仪表盘模板下方，选择“CSE仪表盘模板>CSE层监控中心”仪表盘，查看图表详情。

CSE层监控中心仪表盘中的过滤器说明如下所示：

• 过滤上游IP，所关联的查询分析语句如下所示：

  select distinct(upstream_host)

• 过滤调用链trace_id，所关联的查询分析语句如下所示：

  select distinct(trace_id)

重要图表说明

CSE层监控中心仪表盘中的重要图表说明如下所示：

• 访问量PV图展示访问量的变化情况，所关联的查询分析语句如下所示：

  SELECT TIME_FORMAT( _time_, 'yyyy-MM-dd HH:mm:ss') as _time_,PV FROM ( SELECT TIME_CEIL ( TIME_PARSE(start_time), 'PT300S' ) AS _time_, count( 1 ) AS PV FROM log GROUP BY _time_ )

• 请求成功率图展示请求成功率的变化情况，所关联的查询分析语句如下所示：

  select ROUND(sum(case when response_code < 400 then 1 else 0 end) * 100.0 / count(1),2) as cnt

• 平均延迟图展示平均延迟的变化情况，所关联的查询分析语句如下所示：

  select round(avg(duration) * 1000, 3) as cnt

• 4XX请求数图展示4xx的请求状态码的变化情况，所关联的查询分析语句如下所示：

  SELECT COUNT(1) as cnt WHERE "response_code" >= 400 and "response_code" < 500

• 404请求数图展示404请求状态码的变化情况，所关联的查询分析语句如下所示：

  SELECT COUNT(1) as cnt WHERE "response_code" = 404

• 429请求数图展示429请求状态码的变化情况，所关联的查询分析语句如下所示：

  SELECT COUNT(1) as cnt WHERE "response_code" = 429

• 504请求数图展示504请求状态码的变化情况，所关联的查询分析语句如下所示：

  SELECT COUNT(1) as cnt WHERE "response_code" = 504

• 5XX请求数图展示5xx的请求状态码的变化情况，所关联的查询分析语句如下所示：

  SELECT TIME_FORMAT( _time_, 'yyyy-MM-dd HH:mm:ss') as _time_,cnt FROM ( SELECT TIME_CEIL ( TIME_PARSE(start_time), 'PT300S' ) AS _time_, count( 1 ) AS cnt FROM log where "response_code" >= 500 GROUP BY _time_ )

• 状态码分布图展示请求状态码的变化情况，所关联的查询分析语句如下所示：

  SELECT response_code, COUNT(1) AS rm GROUP BY response_code

• 访问量UV图展示访问量UV的变化情况，所关联的查询分析语句如下所示：

  SELECT TIME_FORMAT( _time_, 'yyyy-MM-dd HH:mm:ss') as _time_,UV FROM (select TIME_CEIL(TIME_PARSE(start_time),'PT600S') AS _time_ , APPROX_COUNT_DISTINCT(authority) as UV  from log group by _time_)

• 流量图展示入流量和出流量的变化情况，所关联的查询分析语句如下所示：

  select TIME_FORMAT(_time_,'yyyy-MM-dd HH:mm:ss') AS _time_,round( CASE WHEN "入流量" > 0 THEN "入流量" ELSE 0 END, 2 ) AS "入流量",round( CASE WHEN "出流量" > 0 THEN "出流量" ELSE 0 END, 2 ) AS "出流量" FROM (SELECT TIME_CEIL(TIME_PARSE(start_time),'PT600S') AS _time_,sum(bytes_received) / 1024.0 AS "入流量",sum(bytes_sent) / 1024.0 AS "出流量" group by  _time_)

• 访问失败率图展示访问失败率和5xx的变化情况，所关联的查询分析语句如下所示：

  SELECT TIME_FORMAT( _time_, 'yyyy-MM-dd HH:mm:ss') as _time_,round( CASE WHEN "失败率" > 0 THEN "失败率" ELSE 0 END, 2 ) AS "失败率",round( CASE WHEN "5XX比例" > 0 THEN "5XX比例" ELSE 0 END, 2 ) AS "5XX比例" from (select TIME_CEIL(TIME_PARSE(start_time),'PT600S') AS _time_,sum(case when response_code >= 400 then 1 else 0 end) * 100.0 / count(1) as '失败率' , sum(case when response_code >=500 THEN 1 ELSE 0 END)*100.0/COUNT(1) as '5XX比例' group by  _time_)

• 延迟图展示访问P50、P90、P99、P9999延迟的变化情况，所关联的查询分析语句如下所示：

  select TIME_FORMAT( _time_, 'yyyy-MM-dd HH:mm:ss') as _time_,round( CASE WHEN "平均" > 0 THEN "平均" ELSE 0 END, 2 ) AS "平均",round( CASE WHEN "P50" > 0 THEN "P50" ELSE 0 END, 2 ) AS "P50",round( CASE WHEN "P90" > 0 THEN "P90" ELSE 0 END, 2 ) AS "P90",round( CASE WHEN "P99" > 0 THEN "P99" ELSE 0 END, 2 ) AS "P99",round( CASE WHEN "P9999" > 0 THEN "P9999" ELSE 0 END, 2 ) AS "P9999" from (select TIME_CEIL(TIME_PARSE(start_time),'PT600S') as _time_,avg(duration) * 1000 as "平均", APPROX_QUANTILE_DS("duration", 0.50)*1000 as "P50", APPROX_QUANTILE_DS("duration", 0.90)*1000 as "P90" ,APPROX_QUANTILE_DS("duration", 0.99)*1000 as 'P99',APPROX_QUANTILE_DS("duration", 0.9999)*1000 as 'P9999' group by  _time_)

• Host请求TOP图展示主机请求TOP信息的变化情况，所关联的查询分析语句如下所示：

  SELECT "upstream_host", pv, uv, round( CASE WHEN "访问成功率(%)" > 0 THEN "访问成功率(%)" ELSE 0 END, 2 ) AS "访问成功率(%)", round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)", round( CASE WHEN "入流量(KB)" > 0 THEN "入流量(KB)" ELSE 0 END, 3 ) AS "入流量(KB)", round( CASE WHEN "出流量(KB)" > 0 THEN "出流量(KB)" ELSE 0 END, 3 ) AS "出流量(KB)"  FROM ( SELECT "upstream_host", count( 1 ) AS pv, APPROX_COUNT_DISTINCT ( authority ) AS uv, sum( CASE WHEN "response_code" < 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问成功率(%)", avg( duration ) * 1000 AS "平均延迟(ms)", sum( bytes_received ) / 1024.0 AS "入流量(KB)", sum( bytes_sent ) / 1024.0 AS "出流量(KB)"  WHERE "upstream_host" != ''  GROUP BY "upstream_host" ) ORDER BY pv DESC

• Host延迟TOP图展示主机延迟TOP信息的变化情况，所关联的查询分析语句如下所示：

  SELECT "upstream_host", pv, round( CASE WHEN "访问成功率(%)" > 0 THEN "访问成功率(%)" ELSE 0 END, 2 ) AS "访问成功率(%)", round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)", round( CASE WHEN "P90延迟(ms)" > 0 THEN "P90延迟(ms)" ELSE 0 END, 3 ) AS "P90延迟(ms)", round( CASE WHEN "P99延迟(ms)" > 0 THEN "P99延迟(ms)" ELSE 0 END, 3 ) AS "P99延迟(ms)" FROM ( SELECT "upstream_host", count( 1 ) AS pv, sum( CASE WHEN "response_code" < 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问成功率(%)", avg( duration ) * 1000 AS "平均延迟(ms)",APPROX_QUANTILE_DS(duration, 0.9) * 1000 AS "P90延迟(ms)", APPROX_QUANTILE_DS(duration, 0.99) * 1000 AS "P99延迟(ms)" WHERE "upstream_host" != ''  GROUP BY "upstream_host" ) ORDER BY "平均延迟(ms)" desc

• Host失败率TOP图展示主机访问失败率TOP的变化情况，所关联的查询分析语句如下所示：

  SELECT "upstream_host", pv,round( CASE WHEN "访问失败率(%)" > 0 THEN "访问失败率(%)" ELSE 0 END, 2 ) AS "访问失败率(%)", round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)", round( CASE WHEN "P90延迟(ms)" > 0 THEN "P90延迟(ms)" ELSE 0 END, 3 ) AS "P90延迟(ms)", round( CASE WHEN "P99延迟(ms)" > 0 THEN "P99延迟(ms)" ELSE 0 END, 3 ) AS "P99延迟(ms)"  FROM ( SELECT "upstream_host", count( 1 ) AS pv, sum( CASE WHEN "response_code" >= 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问失败率(%)", avg( duration ) * 1000 AS "平均延迟(ms)", APPROX_QUANTILE_DS(duration, 0.9) * 1000 AS "P90延迟(ms)", APPROX_QUANTILE_DS(duration, 0.99) * 1000 AS "P99延迟(ms)" WHERE "upstream_host" != ''  GROUP BY "upstream_host") ORDER BY "访问失败率(%)" desc

• URL请求TOP图展示URL请求TOP的变化情况，所关联的查询分析语句如下所示：

  SELECT path, pv,uv, round( CASE WHEN "访问成功率(%)" > 0 THEN "访问成功率(%)" ELSE 0 END, 2 ) AS "访问成功率(%)", round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)", round( CASE WHEN "入流量(KB)" > 0 THEN "入流量(KB)" ELSE 0 END, 3 ) AS "入流量(KB)", round( CASE WHEN "出流量(KB)" > 0 THEN "出流量(KB)" ELSE 0 END, 3 ) AS "出流量(KB)"  FROM ( SELECT path, count( 1 ) AS pv, APPROX_COUNT_DISTINCT ( authority ) AS uv, sum( CASE WHEN "response_code" < 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问成功率(%)", avg( duration ) * 1000 AS "平均延迟(ms)", sum( bytes_received ) / 1024.0 AS "入流量(KB)", sum( bytes_sent ) / 1024.0 AS "出流量(KB)"  WHERE "upstream_host" != ''  GROUP BY path  ) ORDER BY pv desc

• URL失败率TOP图展示URL失败率TOP的变化情况，所关联的查询分析语句如下所示：

  SELECT path, pv, round( CASE WHEN "访问失败率(%)" > 0 THEN "访问失败率(%)" ELSE 0 END, 2 ) AS "访问失败率(%)", round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)", round( CASE WHEN "P90延迟(ms)" > 0 THEN "P90延迟(ms)" ELSE 0 END, 3 ) AS "P90延迟(ms)", round( CASE WHEN "P99延迟(ms)" > 0 THEN "P99延迟(ms)" ELSE 0 END, 3 ) AS "P99延迟(ms)" FROM( SELECT path, count( 1 ) AS pv, sum( CASE WHEN "response_code" >= 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问失败率(%)", avg( duration ) * 1000 AS "平均延迟(ms)", APPROX_QUANTILE_DS(duration, 0.9) * 1000 AS "P90延迟(ms)", APPROX_QUANTILE_DS(duration, 0.99) * 1000 AS "P99延迟(ms)" WHERE "upstream_host" != '' GROUP BY path  ) ORDER BY "访问失败率(%)" desc

• 后端请求TOP图展示后端请求TOP的变化情况，所关联的查询分析语句如下所示：

  SELECT addr, pv, uv, round( CASE WHEN "访问成功率(%)" > 0 THEN "访问成功率(%)" ELSE 0 END, 2 ) AS "访问成功率(%)", round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)", round( CASE WHEN "入流量(KB)" > 0 THEN "入流量(KB)" ELSE 0 END, 3 ) AS "入流量(KB)", round( CASE WHEN "出流量(KB)" > 0 THEN "出流量(KB)" ELSE 0 END, 3 ) AS "出流量(KB)"  FROM ( SELECT authority as addr, count( 1 ) AS pv, APPROX_COUNT_DISTINCT ( authority ) AS uv, sum( CASE WHEN "response_code" < 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问成功率(%)", avg( duration ) * 1000 AS "平均延迟(ms)", sum( bytes_received ) / 1024.0 AS "入流量(KB)", sum( bytes_sent ) / 1024.0 AS "出流量(KB)"  WHERE "upstream_host" != ''  GROUP BY addr  having length(authority) > 2) ORDER BY "pv" desc

• 后端延迟TOP图展示后端延迟TOP的变化情况，所关联的查询分析语句如下所示：

  SELECT addr,pv,round( CASE WHEN "访问成功率(%)" > 0 THEN "访问成功率(%)" ELSE 0 END, 2 ) AS "访问成功率(%)",round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)",round( CASE WHEN "P90延迟(ms)" > 0 THEN "P90延迟(ms)" ELSE 0 END, 3 ) AS "P90延迟(ms)",round( CASE WHEN "P99延迟(ms)" > 0 THEN "P99延迟(ms)" ELSE 0 END, 3 ) AS "P99延迟(ms)" FROM (SELECT authority as addr,count( 1 ) AS pv,sum( CASE WHEN "response_code" < 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问成功率(%)",avg( duration ) * 1000 AS "平均延迟(ms)",APPROX_QUANTILE_DS(duration, 0.9) * 1000 AS "P90延迟(ms)",APPROX_QUANTILE_DS(duration, 0.99) * 1000 AS "P99延迟(ms)" WHERE "upstream_host" != '' and "authority" != '-' GROUP BY addr ) ORDER BY "平均延迟(ms)" desc

• 后端失败率TOP图展示后端失败率TOP的变化情况，所关联的查询分析语句如下所示：

  SELECT addr, pv, round( CASE WHEN "访问失败率(%)" > 0 THEN "访问失败率(%)" ELSE 0 END, 2 ) AS "访问失败率(%)", round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)", round( CASE WHEN "P90延迟(ms)" > 0 THEN "P90延迟(ms)" ELSE 0 END, 3 ) AS "P90延迟(ms)", round( CASE WHEN "P99延迟(ms)" > 0 THEN "P99延迟(ms)" ELSE 0 END, 3 ) AS "P99延迟(ms)"  FROM ( SELECT authority as addr, count( 1 ) AS pv, sum( CASE WHEN "response_code" >= 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问失败率(%)", avg( duration ) * 1000 AS "平均延迟(ms)", APPROX_QUANTILE_DS(duration, 0.9) * 1000 AS "P90延迟(ms)", APPROX_QUANTILE_DS(duration, 0.99) * 1000 AS "P99延迟(ms)" WHERE "upstream_host" != '' and "authority" != '-' GROUP BY addr) ORDER BY "访问失败率(%)" desc

• URL延迟TOP图展示URL延迟TOP的变化情况，所关联的查询分析语句如下所示：

  SELECT path, pv,round( CASE WHEN "访问成功率(%)" > 0 THEN "访问成功率(%)" ELSE 0 END, 2 ) AS "访问成功率(%)",round( CASE WHEN "平均延迟(ms)" > 0 THEN "平均延迟(ms)" ELSE 0 END, 3 ) AS "平均延迟(ms)",round( CASE WHEN "P90延迟(ms)" > 0 THEN "P90延迟(ms)" ELSE 0 END, 3 ) AS "P90延迟(ms)",round( CASE WHEN "P99延迟(ms)" > 0 THEN "P99延迟(ms)" ELSE 0 END, 3 ) AS "P99延迟(ms)" FROM (SELECT path, count( 1 ) AS pv, sum( CASE WHEN "response_code" < 400 THEN 1 ELSE 0 END ) * 100.0 / count( 1 ) AS "访问成功率(%)", avg( duration ) * 1000 AS "平均延迟(ms)", APPROX_QUANTILE_DS(duration, 0.9) * 1000 AS "P90延迟(ms)", APPROX_QUANTILE_DS(duration, 0.99) * 1000 AS "P99延迟(ms)" WHERE "upstream_host" != ''  GROUP BY path  ) ORDER BY "平均延迟(ms)" desc