To set up Prometheus to monitor app metrics: Download and install Prometheus. Internally all time series are stored inside a map on a structure called Head. The number of time series depends purely on the number of labels and the number of all possible values these labels can take. This is a deliberate design decision made by Prometheus developers. Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. I was then able to perform a final sum by over the resulting series to reduce the results down to a single result, dropping the ad-hoc labels in the process. First is the patch that allows us to enforce a limit on the total number of time series TSDB can store at any time. Our CI would check that all Prometheus servers have spare capacity for at least 15,000 time series before the pull request is allowed to be merged. count(container_last_seen{name="container_that_doesn't_exist"}), What did you see instead? So lets start by looking at what cardinality means from Prometheus' perspective, when it can be a problem and some of the ways to deal with it. With this simple code Prometheus client library will create a single metric. Knowing that it can quickly check if there are any time series already stored inside TSDB that have the same hashed value. What sort of strategies would a medieval military use against a fantasy giant? Thank you for subscribing! By setting this limit on all our Prometheus servers we know that it will never scrape more time series than we have memory for. Prometheus Authors 2014-2023 | Documentation Distributed under CC-BY-4.0. This holds true for a lot of labels that we see are being used by engineers. You set up a Kubernetes cluster, installed Prometheus on it ,and ran some queries to check the clusters health. After a chunk was written into a block and removed from memSeries we might end up with an instance of memSeries that has no chunks. PromQL allows you to write queries and fetch information from the metric data collected by Prometheus. Next you will likely need to create recording and/or alerting rules to make use of your time series. instance_memory_usage_bytes: This shows the current memory used. It would be easier if we could do this in the original query though. The most basic layer of protection that we deploy are scrape limits, which we enforce on all configured scrapes. what does the Query Inspector show for the query you have a problem with? If we let Prometheus consume more memory than it can physically use then it will crash. (pseudocode): summary = 0 + sum (warning alerts) + 2*sum (alerts (critical alerts)) This gives the same single value series, or no data if there are no alerts. Our metrics are exposed as a HTTP response. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. Even i am facing the same issue Please help me on this. This allows Prometheus to scrape and store thousands of samples per second, our biggest instances are appending 550k samples per second, while also allowing us to query all the metrics simultaneously. - grafana-7.1.0-beta2.windows-amd64, how did you install it? Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? Since labels are copied around when Prometheus is handling queries this could cause significant memory usage increase. to get notified when one of them is not mounted anymore. Lets adjust the example code to do this. Other Prometheus components include a data model that stores the metrics, client libraries for instrumenting code, and PromQL for querying the metrics. Managing the entire lifecycle of a metric from an engineering perspective is a complex process. Once Prometheus has a list of samples collected from our application it will save it into TSDB - Time Series DataBase - the database in which Prometheus keeps all the time series. but still preserve the job dimension: If we have two different metrics with the same dimensional labels, we can apply an EC2 regions with application servers running docker containers. entire corporate networks, You're probably looking for the absent function. If instead of beverages we tracked the number of HTTP requests to a web server, and we used the request path as one of the label values, then anyone making a huge number of random requests could force our application to create a huge number of time series. Every two hours Prometheus will persist chunks from memory onto the disk. Use Prometheus to monitor app performance metrics. Simply adding a label with two distinct values to all our metrics might double the number of time series we have to deal with. Stumbled onto this post for something else unrelated, just was +1-ing this :). The subquery for the deriv function uses the default resolution. That's the query (Counter metric): sum(increase(check_fail{app="monitor"}[20m])) by (reason). With our custom patch we dont care how many samples are in a scrape. Which in turn will double the memory usage of our Prometheus server. So when TSDB is asked to append a new sample by any scrape, it will first check how many time series are already present. If we configure a sample_limit of 100 and our metrics response contains 101 samples, then Prometheus wont scrape anything at all. Better to simply ask under the single best category you think fits and see *) in region drops below 4. alert also has to fire if there are no (0) containers that match the pattern in region. Going back to our metric with error labels we could imagine a scenario where some operation returns a huge error message, or even stack trace with hundreds of lines. By merging multiple blocks together, big portions of that index can be reused, allowing Prometheus to store more data using the same amount of storage space. The containers are named with a specific pattern: notification_checker [0-9] notification_sender [0-9] I need an alert when the number of container of the same pattern (eg. notification_sender-. Those limits are there to catch accidents and also to make sure that if any application is exporting a high number of time series (more than 200) the team responsible for it knows about it. Prometheus does offer some options for dealing with high cardinality problems. which Operating System (and version) are you running it under? On the worker node, run the kubeadm joining command shown in the last step. Yeah, absent() is probably the way to go. Find centralized, trusted content and collaborate around the technologies you use most. Lets pick client_python for simplicity, but the same concepts will apply regardless of the language you use. First rule will tell Prometheus to calculate per second rate of all requests and sum it across all instances of our server. or Internet application, ward off DDoS - I am using this in windows 10 for testing, which Operating System (and version) are you running it under? Prometheus lets you query data in two different modes: The Console tab allows you to evaluate a query expression at the current time. I can get the deployments in the dev, uat, and prod environments using this query: So we can see that tenant 1 has 2 deployments in 2 different environments, whereas the other 2 have only one. This article covered a lot of ground. These will give you an overall idea about a clusters health. What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? PromQL queries the time series data and returns all elements that match the metric name, along with their values for a particular point in time (when the query runs). The containers are named with a specific pattern: I need an alert when the number of container of the same pattern (eg. If a law is new but its interpretation is vague, can the courts directly ask the drafters the intent and official interpretation of their law? Then imported a dashboard from 1 Node Exporter for Prometheus Dashboard EN 20201010 | Grafana Labs".Below is my Dashboard which is showing empty results.So kindly check and suggest. This also has the benefit of allowing us to self-serve capacity management - theres no need for a team that signs off on your allocations, if CI checks are passing then we have the capacity you need for your applications. 2023 The Linux Foundation. How to react to a students panic attack in an oral exam? By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Setting label_limit provides some cardinality protection, but even with just one label name and huge number of values we can see high cardinality. To get a better understanding of the impact of a short lived time series on memory usage lets take a look at another example. which version of Grafana are you using? Does a summoned creature play immediately after being summoned by a ready action? to your account, What did you do? It will return 0 if the metric expression does not return anything. gabrigrec September 8, 2021, 8:12am #8. @rich-youngkin Yes, the general problem is non-existent series. privacy statement. syntax. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. If I now tack on a != 0 to the end of it, all zero values are filtered out: Thanks for contributing an answer to Stack Overflow! Of course there are many types of queries you can write, and other useful queries are freely available. If a sample lacks any explicit timestamp then it means that the sample represents the most recent value - its the current value of a given time series, and the timestamp is simply the time you make your observation at. Chunks that are a few hours old are written to disk and removed from memory. I am interested in creating a summary of each deployment, where that summary is based on the number of alerts that are present for each deployment. Once the last chunk for this time series is written into a block and removed from the memSeries instance we have no chunks left. t]. Internet-scale applications efficiently, PromQL allows querying historical data and combining / comparing it to the current data. At this point we should know a few things about Prometheus: With all of that in mind we can now see the problem - a metric with high cardinality, especially one with label values that come from the outside world, can easily create a huge number of time series in a very short time, causing cardinality explosion. rev2023.3.3.43278. This makes a bit more sense with your explanation. ***> wrote: You signed in with another tab or window. Prometheus is a great and reliable tool, but dealing with high cardinality issues, especially in an environment where a lot of different applications are scraped by the same Prometheus server, can be challenging. I used a Grafana transformation which seems to work. We will examine their use cases, the reasoning behind them, and some implementation details you should be aware of. How can I group labels in a Prometheus query? All they have to do is set it explicitly in their scrape configuration. Even Prometheus' own client libraries had bugs that could expose you to problems like this. The simplest construct of a PromQL query is an instant vector selector. Ive added a data source(prometheus) in Grafana. It saves these metrics as time-series data, which is used to create visualizations and alerts for IT teams. Time arrow with "current position" evolving with overlay number. Labels are stored once per each memSeries instance. The problem is that the table is also showing reasons that happened 0 times in the time frame and I don't want to display them. And this brings us to the definition of cardinality in the context of metrics. Prometheus's query language supports basic logical and arithmetic operators. The more labels you have, or the longer the names and values are, the more memory it will use. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. And then there is Grafana, which comes with a lot of built-in dashboards for Kubernetes monitoring. So just calling WithLabelValues() should make a metric appear, but only at its initial value (0 for normal counters and histogram bucket counters, NaN for summary quantiles). The result is a table of failure reason and its count. It enables us to enforce a hard limit on the number of time series we can scrape from each application instance. I believe it's the logic that it's written, but is there any conditions that can be used if there's no data recieved it returns a 0. what I tried doing is putting a condition or an absent function,but not sure if thats the correct approach. This means that Prometheus must check if theres already a time series with identical name and exact same set of labels present. We know that the more labels on a metric, the more time series it can create. In this article, you will learn some useful PromQL queries to monitor the performance of Kubernetes-based systems. Return the per-second rate for all time series with the http_requests_total Once you cross the 200 time series mark, you should start thinking about your metrics more. help customers build He has a Bachelor of Technology in Computer Science & Engineering from SRMS. The only exception are memory-mapped chunks which are offloaded to disk, but will be read into memory if needed by queries. We can use these to add more information to our metrics so that we can better understand whats going on. what error message are you getting to show that theres a problem? The Prometheus data source plugin provides the following functions you can use in the Query input field. For example our errors_total metric, which we used in example before, might not be present at all until we start seeing some errors, and even then it might be just one or two errors that will be recorded. In our example we have two labels, content and temperature, and both of them can have two different values. node_cpu_seconds_total: This returns the total amount of CPU time. If the time series doesnt exist yet and our append would create it (a new memSeries instance would be created) then we skip this sample. What is the point of Thrower's Bandolier? I then hide the original query. This process helps to reduce disk usage since each block has an index taking a good chunk of disk space. The advantage of doing this is that memory-mapped chunks dont use memory unless TSDB needs to read them. @rich-youngkin Yeah, what I originally meant with "exposing" a metric is whether it appears in your /metrics endpoint at all (for a given set of labels). By default Prometheus will create a chunk per each two hours of wall clock. For example, the following query will show the total amount of CPU time spent over the last two minutes: And the query below will show the total number of HTTP requests received in the last five minutes: There are different ways to filter, combine, and manipulate Prometheus data using operators and further processing using built-in functions. Neither of these solutions seem to retain the other dimensional information, they simply produce a scaler 0. Once configured, your instances should be ready for access. Well be executing kubectl commands on the master node only. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. If all the label values are controlled by your application you will be able to count the number of all possible label combinations. Thats why what our application exports isnt really metrics or time series - its samples. By default we allow up to 64 labels on each time series, which is way more than most metrics would use. This is one argument for not overusing labels, but often it cannot be avoided. Another reason is that trying to stay on top of your usage can be a challenging task. Have a question about this project? Then you must configure Prometheus scrapes in the correct way and deploy that to the right Prometheus server. If we make a single request using the curl command: We should see these time series in our application: But what happens if an evil hacker decides to send a bunch of random requests to our application? Is there a solutiuon to add special characters from software and how to do it. If both the nodes are running fine, you shouldnt get any result for this query. Also the link to the mailing list doesn't work for me. but it does not fire if both are missing because than count() returns no data the workaround is to additionally check with absent() but it's on the one hand annoying to double-check on each rule and on the other hand count should be able to "count" zero . This selector is just a metric name. Why are trials on "Law & Order" in the New York Supreme Court? You must define your metrics in your application, with names and labels that will allow you to work with resulting time series easily. If you need to obtain raw samples, then a range query must be sent to /api/v1/query. Cardinality is the number of unique combinations of all labels. In general, having more labels on your metrics allows you to gain more insight, and so the more complicated the application you're trying to monitor, the more need for extra labels. Internally time series names are just another label called __name__, so there is no practical distinction between name and labels. by (geo_region) < bool 4 If, on the other hand, we want to visualize the type of data that Prometheus is the least efficient when dealing with, well end up with this instead: Here we have single data points, each for a different property that we measure. There is an open pull request on the Prometheus repository. as text instead of as an image, more people will be able to read it and help. Short story taking place on a toroidal planet or moon involving flying, How to handle a hobby that makes income in US, Doubling the cube, field extensions and minimal polynoms, Follow Up: struct sockaddr storage initialization by network format-string. You can calculate how much memory is needed for your time series by running this query on your Prometheus server: Note that your Prometheus server must be configured to scrape itself for this to work. The result of an expression can either be shown as a graph, viewed as tabular data in Prometheus's expression browser, or consumed by external systems via the HTTP API. We know that time series will stay in memory for a while, even if they were scraped only once.
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