elasticsearch,cubism.js,Javascript,elasticsearch,Cubism.js" /> elasticsearch,cubism.js,Javascript,elasticsearch,Cubism.js" />

Javascript Elasticsearch中的立体主义和度量(statsd/diamond)

Javascript Elasticsearch中的立体主义和度量(statsd/diamond),javascript,elasticsearch,cubism.js,Javascript,elasticsearch,Cubism.js,在测试环境设置中,我使用将服务器统计数据和指标发送到statsd,然后使用statsd将它们发送到elasticsearch elasticsearch数据如下所示: { "hits" : { "hits" : [ { "_source":{"ns":"servers","grp":"server1","tgt":"vmstat","act":"pswpout","val":"0","@timestamp":"1438565055000"} }, {

在测试环境设置中,我使用将服务器统计数据和指标发送到statsd,然后使用statsd将它们发送到elasticsearch

elasticsearch数据如下所示:

{
  "hits" : {
    "hits" : [ {
      "_source":{"ns":"servers","grp":"server1","tgt":"vmstat","act":"pswpout","val":"0","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"vmstat","act":"pgpgin","val":"0","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"vmstat","act":"pswpin","val":"0","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"cpu","act":"total.nice","val":"0","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"cpu","act":"total.irq","val":"0","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"cpu","act":"total.guest","val":"0","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"diskspace","act":"_logs.byte_used","val":"209944576","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"diskspace","act":"_logs.byte_free","val":"887513440256","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"diskspace","act":"_logs.byte_avail","val":"842419666944","@timestamp":"1438565055000"}
    }, {
      "_source":{"ns":"servers","grp":"server1","tgt":"diskspace","act":"_logs.inodes_used","val":"11","@timestamp":"1438565055000"}
    } ]
  }
}
我将如何使用立体主义渲染这些数据?我可以使用elasticsearch.js提取数据,但通常我都不知道如何进行渲染,因此,我可以可视化每个不同操作的时间序列数据。例如。

您可以尝试或使用后端。 对于这些,后端提供了很棒的可视化工具

根据他们的网站,如果你选择Graphite cubism作为数据提供商,那么你也可以使用它:

看看ATSD。如果功能足够,Axibase时间序列数据库社区版是免费的。顺便说一下,它直接支持Graphite wire协议,因此您可以直接将数据从diamond守护进程流式传输到数据库中


披露:我为这家公司工作。

它必须是立体主义的还是你需要这些指标的功能图?@SergeiRodionov正在寻找使用这些指标的功能图。进一步回答:你不想使用ES,因为它不是时间序列数据库,你也不想使用Kibana,因为它每小时只能绘制1个指标查询(在一个图表上绘制最小值、最大值和平均值需要3个查询,而不是一个具有复杂结果集的查询)。使用grafana和XDB,不要对抗堆栈的默认值。