Grafana sends the correct time range, but Prometheus 24h will be relative to that I think.I think I am not clear enough. # Prometheusクエリー Copy link Quote reply Contributor fxmiii commented May 24, 2019. # {','}, 422 Unprocessable Entity when an expression can't be executed(RFC4918).

"resultType": "matrix", logger.debug(','.format(params)) -h, --help show this help message and exit
出力先のファイル名を指定します

The time range is always sent in UTC second epocs, but when converted to your local time should match what you expect.It seems like those 'start' and 'end' are set to be multiples of the step time (24h)? Like say 'last 24 hours'. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together.By clicking “Sign up for GitHub”, you agree to our.What is your dashboard timezone setting ?The timezone settings have always been left to 'default'. # response.raise_for_status() It really seems like a huge bug on prometheus's side if it can't "return stable results" for a query like:But it does seem like it can, and should. -n NAMESPACE, --namespace NAMESPACE for result in results:

"pod_name": "infra-test-nodeport-cust-0" Would the query performance improve when we move to Prometheus 2.1.0?That's getting into profiling, which is possible but tricky to do with metrics.Thanks for contributing an answer to Stack Overflow!By clicking “Post Your Answer”, you agree to our.To subscribe to this RSS feed, copy and paste this URL into your RSS reader.site design / logo © 2020 Stack Exchange Inc; user contributions licensed under,Stack Overflow works best with JavaScript enabled,Where developers & technologists share private knowledge with coworkers,Programming & related technical career opportunities,Recruit tech talent & build your employer brand,Reach developers & technologists worldwide.Well, for the total number of samples I was looking at the value of prometheus_local_storage_ingested_samples_total which is at 9.75 Bil as of now. --end END データの終了時間を指定します（例）20190102-1000 I'll try some examples.When running a query using the quick range "previous month" I get this query:When "Local browser time" is selected, I believe it should it be "start=1554091200" to send my local time zone midnight (I am -4).What does change is just the way grafana displays the data.


Qiita can be used more conveniently after logging in.Help us understand the problem. writer.writeheader() pod_name = result[',']

time_series = collections.defaultdict(dict)

12 comments Comments. There's a query, a start time, an end time, and a step. Namespaceを指定します Would the query performance improve when we move to Prometheus 2.1.0?Asking for help, clarification, or responding to other answers.Making statements based on opinion; back them up with references or personal experience.

2019-01-16 15:20:00,1.2547518466667875,1.5286131908334255,1.8340893729164995,2.258688518749826 "result": [ PromQL 表达式计算出来的值有以下几种类型：

This would be used places where I want data by work shift. I don't think you're telling me everything.Is the query_range performance dependant on the size of the data in Prometheus or the rate of ingestion?The queries work when we use a higher step/ lower resolution, but we really need a 1 second granularity for doing some comparison.

And because the 'start' time is sent to prometheus in UTC I get stuck with my timezone offset in the query?Yes, start & end needs to be multiples of the step to have Prometheus return stable results.I can replicate your issue and I think it's the 24h interval in Prometheus that is not timezone aware. This document is meant as a reference. What does this mean for the future of AI, edge…,Hot Meta Posts: Allow for removal by moderators, and thoughts about future…,Goodbye, Prettify. Prometheus API查询. ], row = {',': datetime.datetime.fromtimestamp(timestamp)} # 時刻毎のデータの辞書を用意する 2019-01-16 15:50:00,1.0475173487499962,1.2800040254167773,1.750940527916403,2.7946370483334704 # csvファイルに保存する writer = csv.DictWriter(csv_file, fieldnames=fieldnames) "values": [

# pprint.pprint(response.json()) 借助IBM中国研究院的创新成果，以及IBM全球实验室众多环境及能源专家的支持，2014年7月...Copyright © 2013 - 2020 Tencent Cloud. ? 注意到上图中的Res框里没有给值，没有给的话Prometheus会自动给一个值，这个值在图示右上角可以看到。,Prometheus在对每段Instant vector selector求值的逻辑是这样的：,图中的绿点是Prometheus实际存储的数据，按照时间轴从左到右排列。蓝点是根据step参数的求值结果。,大家都知道Grafana都是用来画图的，比如下面这张图Y轴是值，X轴则是时间线，因此在X轴方向的每个像素都代表了一个timestamp。.Firebug 的年代，我是火狐（Mozilla Firefox）浏览器的死忠；但后来不知道为什么，该插件停止了开发，导致我不得不寻求一个新的网页开发工具。那段时间，不少人开始推荐 Ch...到目前为止Kubernetes对基于cpu使用率的水平pod自动伸缩支持比较良好，但 根据自定义metrics的HPA支持并不完善，并且使用起来也不方便。 PodのCPU使用率をcsvに出力します。 # [1547535600, ','], var date = new Date(0); # sum(rate(container_cpu_usage_seconds_total{namespace="$namespace"}[$interval])) by (pod_name) * 100 The query range endpoint isn't magic, in fact it is quite dumb. First shift is 5-13, 2nd shift is 13-21, and 3rd shift is 21-5.Yet another case is where I want a single data point per week. # 行に時間の列を追加 "status": "success", # pprint.pprint(time_series)

The queries work when we use a higher step/ lower resolution, but we really need a 1 second granularity for doing some comparison. Prometheus query expression, check out the Prometheus documentation. (it's taking more than 1 min),Some of differences between the two systems I observed are -.Prod is running 1.8.2 version of Prometheus, staging is running 2.1.0 # リクエストを実行 IBM Cloud Privateに同梱のPrometheusから、データをPythonでcsvにエクスポートしてみたメモ。 古き良きシステムで、Pod毎のCPU使用率などの性能情報レポートを、エクセルで作成して報告したい場合を …

# 事前に格納したPod名のリストの方でループする # レスポンスは以下のようなデータ -f FILENAME, --filename FILENAME "Content-Type: application/x-www-form-urlencoded;charset=UTF-8",'query=sum(rate(container_cpu_usage_seconds_total{namespace="default"}[5m])) by (pod_name) * 100',"sum(rate(container_cpu_usage_seconds_total{namespace=,{