hello i really want to use bosun/tsdbrelay/opentsdb with the telegraf collector, as it gets all the metrics we want to monitor out of the box.
i allready have a small setup to push metrics from 5 servers to bosun for indexing and opentsdb for storage.
i used the haproxy configs from kyle brandts bosun infrastructure blog to make the tsdbs ha-ready
but bosun is showing that it cannot use the auto-type for metrics, and also in the primary stats view does not show any graphs for cpu / mem etc.
what can i provide that the graphs show up.
kind regards.
Both of these features are mostly scollector specific. The "host" view (I've considered ripping that out, it was done in the early days, better to use something like grafana) depends on scollector specific metrics such as os.cpu.
As far as "Auto" for rate vs gauge, that is also metadata that comes from scollector and sent to bosun. If you want to try to mimic the behavior see https://github.com/bosun-monitor/bosun/blob/master/metadata/metadata.go#L30 and https://github.com/bosun-monitor/bosun/blob/master/metadata/metadata.go#L195 - you would need to create at least the "rate" key for each metric you are getting from telegraph.
Related
my goal is to observe metrics (like CPU, Memory usage etc.) with Prometheus on a server and on its running docker containers. Before sending an alarm, I would like to compare the certain values of those metrics with e.g. an 0.95 quantile. However, over several weeks of search in the internet I still struggle to create metrics for the certain quantiles. Therefore I ask in this thread for your help/advice, how a quantile for certain metrics can be created.
Background
The code base is a fork of the docprom repository. This code relies on Prometheus for monitoring. Prometheus retrieves its data from a running cAdvisor container. The provided metrics of cAdvisor for Prometheus can be seen on the following page. However, it provides only Gauge and Counter metric types. During my research I was not able to find parameters that would enable modifications/extensions of those provided metrics.
Problem
According to my current understanding, the metric type should be a Histogram or Summary in order to observe the quantiles. What is the best approach to use the histogram_quantile query on the metrics provided by cAdvisor?
My current idea is to
create a custom server
fetch the desired data from Prometheus
calculate the desired data
provide it as a metric from the server, so that Prometheus can scrape it
Run histogram_quantile on the custom metric
Is it the right approach in order to create a metric that can be used with quantiles?
For example I would like to fire an alarm if a certain containers' CPU usage exceeds a 0,95 quantile. The code for the CPU usage can be seen exemplary below:
sum(rate(container_cpu_usage_seconds_total{name="CONTAINER_NAME"}[10m]))) / count(node_cpu_seconds_total{mode="system"}) * 100
What would be the best approach to create the desired quantiles? Am I on the right path or am I missing something simple here? Because it looks way too hard for me in order to get a simple query with a quantile.
I am thankful for all help and information.
I am looking for monitoring tool for the following use cases:
Collect basic metrics about virtual machine (cpu usage, memory usage, i/o, available space)
Extract metrics from SQL Server (probably running some queries)
Extract information from external service about processing i.e how many processing are currently running and for how long. I am thinking about writing python scripts, but don't know how to combine with monitoring tool
Have the ability to plot charts and manage alerts and it will nice to have ability to send not only mails, but send message to slack/ms teams.
I was thing about Prometheus, because it has wmi_exporter, node_exporter, sql exporter, alert manager with possibility to send notifications to multiple destinations, but I don't know what to do with this external service and python scripts.
Any suggestions?
Prometheus can definitely do what you say you need done. Some of it may not be trivial, but you can definitely fill in the blanks yourself.
E.g. you can get machine metrics basically out of the box by firing up a node_exporter and having it scraped by Prometheus, but I don't think it has e.g. information on all running processes. The latter might require you to write an agent/exporter: a simple web server that exposes metrics on /metrics; there exists a Python client library to help with that. Or have said processes (assuming they're your code) push metrics to a Pushgateway instead, if they're short lived batch jobs.
Oh, and for charts/dashboards you probably want Grafana, as Prometheus' abilities in that area are rather limited and Grafana integrates rather well with Prometheus.
Sorry I just started to learn docker. My question may seem stupid for some of you.
In fact, I would like to know if there is a way to collect performance metrics from "CAdvisor" container (not from cgroup) at runtime ? I mean, extract performance values from the curves designed by cadvisor like memory usage or network traffic.
I need to record this values and save them in a database so that, I can perform a statistic analyzes upon these generated values (like comparing memory consumption for two docker containers at t=50s).
Thanks in advance.
As other answers mention, cAdvisor doesn't provide its own performance data API, instead it exposes metrics which are typically handled in a separate database if one wants to derive performance data beyond "real time". For example, cAdvisor exports Prometheus metrics natively:
http://prometheus.io/docs/instrumenting/exporters/
The Prometheus metric types:
http://prometheus.io/docs/concepts/metric_types/
Prometheus supports a fairly rich functional expression language that can be used for querying and visualization:
http://prometheus.io/docs/querying/basics/
cAdvisor does provide a rest endpoint to get any stats in real time. By default, it keeps latest two minute of data. You can configure it to keep more or less. It also supports a storage backend to keep dumping stats to an influxdb database.
REST Api:
eg. /api/v1.3/containers
doc: https://github.com/google/cadvisor/blob/master/docs/api.md
Doc on setting up InfluxDB:
https://github.com/google/cadvisor/blob/master/docs/influxdb.md
I think you could use https://github.com/tutumcloud/container-metrics for this. Basically what that would be doing is using influxdb http://influxdb.com/ as a time series data store.
There is some more information available here: http://blog.tutum.co/2014/08/25/panamax-docker-application-template-with-cadvisor-elasticsearch-grafana-and-influxdb/
A couple of people seemed to be looking into the ELK stack (Elastic Search, Logstash, Kibana) for visualising some of this data here: https://github.com/google/cadvisor/issues/634
This is in the context of a small data-center setup where the number of servers to be monitored are only in double-digits and may grow only slowly to few hundreds (if at all). I am a ganglia newbie and have just completed setting up a small ganglia test bed (and have been reading and playing with it). The couple of things I realise -
gmetad supports interactive queries on port 8652 using which I can get metric data subsets - say data of particular metric family in a specific cluster
gmond seems to always return the whole dump of data for all metrics from all nodes in a cluster (on doing 'netcat host 8649')
In my setup, I dont want to use gmetad or RRD. I want to directly fetch data from the multiple gmond clusters and store it in a single data-store. There are couple of reasons to not use gmetad and RRD -
I dont want multiple data-stores in the whole setup. I can have one dedicated machine to fetch data from the multiple, few clusters and store them
I dont plan to use gweb as the data front end. The data from ganglia will be fed into a different monitoring tool altogether. With this setup, I want to eliminate the latency that another layer of gmetad could add. That is, gmetad polls say every minute and my management tool polls gmetad every minute will add 2 minutes delay which I feel is unnecessary for a relatively small/medium sized setup
There are couple of problems in the approach for which I need help -
I cannot get filtered data from gmond. Is there some plugin that can help me fetch individual metric/metric-group information from gmond (since different metrics are collected in different intervals)
gmond output is very verbose text. Is there some other (hopefully binary) format that I can configure for export?
Is my idea of eliminating gmetad/RRD completely a very bad idea? Has anyone tried this approach before? What should I be careful of, in doing so from a data collection standpoint.
Thanks in advance.
I am using grinder in order to generate reports for the performance tests for my application. But I noticed that it does not generate any report on CPU and memory usage. On further investigation, I found that Grinder does not provide this information. Now, my question is, is there any tool that can be hooked up with grinder, to record the CPU and memory usage details?
As you have discovered, this is not supported directly in The Grinder itself. You will need to use a collection of tools to accomplish this.
I use a combination of Quickstatd, Graphite, and Grinder to Graphite to get all my results in the same place where I can see them. If you need to support Windows, you can probably use collectd (with ssc-serv and the Graphite plugin) instead of Quickstatd, which is based on bash scripts.
You can also pull in server side metrics (like DB lookups per second, etc.) with tools like jmxtrans, statsd, and metrics.
Having all that information in the same place is really powerful, and can give you some good insights.
If you grind a Java server, you can get data via JMX from OperatingSystemMXBean and MemoryMXBean.
Then add the data to a Grinder user Statistic and the data will end up in the -data.log
grinder.statistics.registerDataLogExpression("Load", "userDouble0")
..
grinder.statistics.forCurrentTest.setDouble("userDouble0", systemLoadAverage)
the -data.log can directly be fed into Gnuplot
gnuplot> plot 'client-0-data.log' using 2:7 title "System Load"