Prometheus percentage of total

And those numbers should make sense to anybody looking at them, without much interpretation. Plus they should reflect to as large an extent as possible how happy your customers are when using your application. A common way to map these aspects to real numbers is to use the following approach: For a specific use case, find a way to measure how long this takes.

There are multiple ways of doing this, either by instrumenting your own code, or by measuring via black box testing from the outside. Prometheus then stores the scraped metrics in its time series database.

Prometheus encourages you to use the following type of buckets:. Creating this kind of metric is quite simple if you use one of the many Prometheus client libraries ; most have direct support for histogram type metrics out of the box.

Given that Prometheus now scrapes your histogram metrics, there will now be metrics inside Prometheus which look approximately like this, at a specific point in time:. Which means: Since the start of the service, Fortunately, the answer to most of the above questions is the quite remarkable Prometheus function rate. The second thing we need is the the aggregation operator sumwhich does just that, sums up metrics over different labels, in our case over different instance labels.

The value here shows e. Perhaps due to caching effects, or other startup latencies. Displaying the above value in a dashboard for immediate view is a good idea. But this is just a snapshot of the current SLI, for the previous n minutes.

prometheus percentage of total

In combination with a ten hour time series, we can now ask for the aggregated SLI for the entire day, using a single API call:. Adding a scalar function to the expression makes the resulting JSON even easier to parse:. In the simplest case, Prometheus can reach the end to end monitoring application, which collects metrics just as with the white box instrumentation.

The setup for that could look like this:. This obviously requires Prometheus to be able to reach the monitoring application, and it needs to have a reachable metrics end point.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Prometheus is awesome, but the human mind doesn't work in PromQL. The intention of this repository is to become a simple place for people to provide examples of queries they've found useful.

We encourage all to contribute so that this can become something valuable to the community. These examples are formatted as recording rulesbut can be used as normal expressions. Please ensure all examples are submitted in the same format, we'd like to keep this nice and easy to read and maintain. The examples may contain some metric names and labels that aren't present on your system, if you're looking to re-use these then make sure validate the labels and metric names match your system.

This query ultimately provides an overall metric for CPU usage, per instance. It does this by a calculation based on the idle metric of the CPU, working out the overall percentage of the other states for a CPU in a 5 minute window and presenting that data per instance. Summary: This query selects the status rate for any job, instance, method, and path combinations for which the status rate is not at least 50 times higher than the status rate.

The rate function has been used here as it's designed to be used with the counters in this query. It calculates the 90th percentile latency for each sub-dimension. To filter the resulting bad latencies and retain only those that receive more than one request per second. Summary: The rate function calculates the per-second average rate of time series in a range vector.

Combining all the above tools, we can get the rates of HTTP requests of a specific timeframe. The query calculates the per-second rates of all HTTP requests that occurred in the last 5 minutes, an hour ago. Suitable for usage on a counter metric.

How to create Grafana Dashboards: The Easy way

Link: Tom Verelst - Ordina. Summary: How much memory are the tools in the kube-system namespace using? Break it down by Pod and NameSpace! Summary: Which are your most expensive time series to store? When tuning Prometheus, these quries can help you monitor your most expensive metrics.

Be cautious, this query is expensive to run. Link: Brian Brazil - Robust Perception. Summary: Which of your jobs have the most timeseries? These are examples of rules you can use with Prometheus to trigger the firing of an event, usually to the Prometheus alertmanager application. You can refer to the official documentation for more information. Summary: Asks Prometheus to predict if the hosts disks will fill within four hours, based upon the last hour of sampled data.

Calculating SLIs with Prometheus

Summary: Trigger an alert if the memory of a host is almost full. This is done by deducting the total memory by the free, buffered and cached memory and dividing it by total again to obtain a percentage. Link: Stefan Prodan - Blog. Summary: Trigger an alert if Prometheus begins to throttle its ingestion. If you see this, some TLC is required. Skip to content. Permalink Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

Sign up. Branch: master. Find file Copy path. Rucknar Merge branch 'master' into recordings ae8e Nov 13, Raw Blame History.This directory contains example components for running either an operational Prometheus setup for your OpenShift cluster, or deploying a standalone secured Prometheus instance for configurating yourself.

The prometheus. It is protected by an OAuth proxy that only allows access for users who have view access to the kube-system namespace. The optional node-exporter component may be installed as a daemon set to gather host level metrics. It requires additional privileges to view the host and should only be run in administrator controlled namespaces. The prometheus-standalone. It expects two secrets to be created ahead of time:.

The example uses secrets instead of config maps in case either config file needs to reference a secret. You can find the Prometheus route by invoking oc get routes and then browsing in your web console. Users who are granted view access on the namespace will have access to login to Prometheus.

Number of metrics series per metric a series is a unique combination of labels for a given metric. Number of samples individual metric values exposed by each endpoint at the time it was scraped. If this goes over ms, the cluster might destabilize.

Over ms and things definitely start falling apart. This number will include image pulls, so often will be hundreds of seconds. Returns a running count not a rate of docker operations that have timed out since the kubelet was started.

Returns a running count not a rate of docker operations that have failed since the kubelet was started. Returns PLEG pod lifecycle event generator latency metrics. This represents the latency experienced by calls from the kubelet to the container runtime i. Returns the number of builds which have not yet started after 10 minutes. This query filters out builds where the fact they have not started could be cited as resulting from user error.

Calculates the error rate for builds, where the error might indicate issues with the cluster or namespace. Note, it ignores builds in the "Failed" and "Cancelled" phases, as builds typically end up in one of those phases as the result of a user choice or error.

Administrators after some experience with their cluster could decide what is an acceptable error rate and monitor when it is exceeded. Calculates the percentage of builds that were successful in the last hour. Note that this value is only accurate if no pruning of builds is performed, otherwise it is impossible to determine how many builds ran successfully or otherwise in the last hour.

Similar to the two queries above, this query will predict what the error rate will be in one hour based on last hours data. Returns the number of failed builds because of problems retrieving source from the associated Git repository.

Skip to content. Branch: master. Create new file Find file History. Latest commit.Some functions have default arguments, e.

Graphite and Grafana – How to calculate Percentage of Total/Percent Distribution

This means that there is one argument v which is an instant vector, which if not provided it will default to the value of the expression vector time. This is useful for alerting on when no time series exist for a given metric name and label combination. In the first two examples, absent tries to be smart about deriving labels of the 1-element output vector from the input vector. This is useful for alerting on when no time series exist for a given metric name and label combination for a certain amount of time.

prometheus percentage of total

For each input time series, changes v range-vector returns the number of times its value has changed within the provided time range as an instant vector. Returned values are from 1 to Returned values are from 0 to 6, where 0 means Sunday etc. Returned values are from 28 to The delta is extrapolated to cover the full time range as specified in the range vector selector, so that it is possible to get a non-integer result even if the sample values are all integers.

The following example expression returns the difference in CPU temperature between now and 2 hours ago:. Special cases are:. The samples in b are the counts of observations in each bucket.

Each sample must have a label le where the label value denotes the inclusive upper bound of the bucket. Samples without such a label are silently ignored. To calculate the 90th percentile of request durations over the last 10m, use the following expression:. To aggregate, use the sum aggregator around the rate function.

The following expression aggregates the 90th percentile by job :. Otherwise, NaN is returned. If a quantile is located in the highest bucket, the upper bound of the second highest bucket is returned. A lower limit of the lowest bucket is assumed to be 0 if the upper bound of that bucket is greater than 0. In that case, the usual linear interpolation is applied within that bucket. Otherwise, the upper bound of the lowest bucket is returned for quantiles located in the lowest bucket.

If b contains fewer than two buckets, NaN is returned. The lower the smoothing factor sfthe more importance is given to old data. The higher the trend factor tfthe more trends in the data is considered.

Both sf and tf must be between 0 and 1. Returned values are from 0 to Breaks in monotonicity such as counter resets due to target restarts are automatically adjusted for. The increase is extrapolated to cover the full time range as specified in the range vector selector, so that it is possible to get a non-integer result even if a counter increases only by integer increments.

The following example expression returns the number of HTTP requests as measured over the last 5 minutes, per time series in the range vector:.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again. If nothing happens, download the GitHub extension for Visual Studio and try again. Prometheus monitoring for your gRPC Go servers and clients. It is a perfect way to implement common patterns: auth, logging and To use Interceptors in chains, please see go-grpc-middleware. There are two types of interceptors: client-side and server-side.

This package provides monitoring Interceptors for both. Both of them have mirror-concepts. Similarly all methods contain the same rich labels:. Differentiating between the two is important especially for latency measurements. The list of all statuses is to long, but here are some common ones:.

For simplicity, let's assume we're tracking a single server-side RPC call of mwitkow. TestServicecalling the method PingList. The call succeeds and returns 20 messages in the stream. Then the user logic gets invoked. The user logic may return an error, or send multiple messages back to the client.

In this case, on each of the 20 messages sent back, a counter will be incremented:. Prometheus histograms are a great way to measure latency distributions of your RPCs. However, since it is bad practice to have metrics of high cardinality the latency monitoring metrics are disabled by default.

To enable them please call the following in your server initialization code:. The histogram variable contains three sub-metrics:. Prometheus philosophy is to provide raw metrics to the monitoring system, and let the aggregations be handled there. The verbosity of above metrics make it possible to have that flexibility.

Here's a couple of useful monitoring queries:.When working with Grafana and Graphite, it is quite common that I need to calculate the percentage of a total from Graphite time series.

There are a few variations on this that are solved in different ways. With the SingleStat panel in Grafana, you need to reduce a time series down to one number.

prometheus percentage of total

For example, to calculate the available memory percentage for a group of servers we need to sum all available memory for all servers and sum total memory for all servers and then divide the available memory total by the total memory total. The way to do this in Grafana is to create two queries, A for the total and B for the subtotal and then divide B by A.

Graphite has a function divideSeries that you can use for this. Then hide A you can see that is grayed out below and use B for the SingleStat value.

The divideSeries function can be used in a Graph panel too, as long as the divisor is a single time series for example, it will work for the sum of all servers but not when grouped by server. In this case, divideSeries will not work. One way to solve this is to use a different graphite function called reduceSeries. In the example, there are two values, capacity the total and usage the subtotal.

First, a groupByNode function is applied, this will return a list with the two values for each server e. The mapSeries and reduceSeries take this list and for each server applies the asPercent reduce function to the two values. The result is a list of percentage totals per server. The reduceSeries function can also apply two other reduce functions: a diff function and a divide function.

Calculating percentages in a query

Another function worth checking out is the AsPercent function which might work better in some cases. The example below uses the same two query technique that we used for divideSeries but it works with multiple time series!

I did not know them before so I think they will help others too. Irishman living and working in Sweden. View all posts by Daniel Lee. Thanks for posting this. I have really tried to make my calulation correct but it just wont work. Maybe I am just to stupid. I have the total value and the used value but wont get the percentage used in the graph.

Like my post here. You probably have solved this already but in your case it sounds like you have a total and subtotal so the divideSeries function that I describe at the beginning is probably what want.

Important note: some of the functions described here are only in the latest version of Graphite 1. You are commenting using your WordPress.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Already on GitHub? Sign in to your account.

We are trying to migrate to the new netdata from the old one and convert our old charts. It seems there is a bug which prevents to use different dimensions in the same query. Well, you ask prometheus for user cpu and you get it, then you ask for system cpu and you get this too, but when you add these two, you get no data. Thank you, yesterday the guys told the magic pattern on the prometheus channel.

Thanks to SuperQ and estol. It would be nice if netdata exposed the cpu dimension in addition to the cpu mode. We already have an open issue to fix these. I understand we should probably provide some kind of mapping to have them mapped in the format you suggest I think I found a way to do this in netdata. Check Skip to content. Dismiss Join GitHub today GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.

Sign up. New issue. Jump to bottom. Labels question. Copy link Quote reply. This comment has been minimized.

prometheus percentage of total

Sign in to view. Not sure it is Prometheus or we are trying it wrong Well, you ask prometheus for user cpu and you get it, then you ask for system cpu and you get this too, but when you add these two, you get no data.


Replies to “Prometheus percentage of total”

Leave a Reply

Your email address will not be published. Required fields are marked *