Please see data model and exposition format pages for more details. 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. The way labels are stored internally by Prometheus also matters, but thats something the user has no control over. This is true both for client libraries and Prometheus server, but its more of an issue for Prometheus itself, since a single Prometheus server usually collects metrics from many applications, while an application only keeps its own metrics. Theres only one chunk that we can append to, its called the Head Chunk. Its very easy to keep accumulating time series in Prometheus until you run out of memory. Has 90% of ice around Antarctica disappeared in less than a decade? Is a PhD visitor considered as a visiting scholar? Can airtags be tracked from an iMac desktop, with no iPhone? Finally we do, by default, set sample_limit to 200 - so each application can export up to 200 time series without any action. Once it has a memSeries instance to work with it will append our sample to the Head Chunk. Today, let's look a bit closer at the two ways of selecting data in PromQL: instant vector selectors and range vector selectors. This is the standard Prometheus flow for a scrape that has the sample_limit option set: The entire scrape either succeeds or fails. But I'm stuck now if I want to do something like apply a weight to alerts of a different severity level, e.g. 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. For a list of trademarks of The Linux Foundation, please see our Trademark Usage page. Already on GitHub? Going back to our time series - at this point Prometheus either creates a new memSeries instance or uses already existing memSeries. These checks are designed to ensure that we have enough capacity on all Prometheus servers to accommodate extra time series, if that change would result in extra time series being collected. Now we should pause to make an important distinction between metrics and time series. See this article for details. To get a better idea of this problem lets adjust our example metric to track HTTP requests. rate (http_requests_total [5m]) [30m:1m] Secondly this calculation is based on all memory used by Prometheus, not only time series data, so its just an approximation. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. See these docs for details on how Prometheus calculates the returned results. The Head Chunk is never memory-mapped, its always stored in memory. We know that each time series will be kept in memory. I've added a data source (prometheus) in Grafana. 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. 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. I know prometheus has comparison operators but I wasn't able to apply them. 02:00 - create a new chunk for 02:00 - 03:59 time range, 04:00 - create a new chunk for 04:00 - 05:59 time range, 22:00 - create a new chunk for 22:00 - 23:59 time range. If our metric had more labels and all of them were set based on the request payload (HTTP method name, IPs, headers, etc) we could easily end up with millions of time series. At the same time our patch gives us graceful degradation by capping time series from each scrape to a certain level, rather than failing hard and dropping all time series from affected scrape, which would mean losing all observability of affected applications. notification_sender-. TSDB will try to estimate when a given chunk will reach 120 samples and it will set the maximum allowed time for current Head Chunk accordingly. The real power of Prometheus comes into the picture when you utilize the alert manager to send notifications when a certain metric breaches a threshold. This patchset consists of two main elements. count(ALERTS) or (1-absent(ALERTS)), Alternatively, count(ALERTS) or vector(0). information which you think might be helpful for someone else to understand Are there tables of wastage rates for different fruit and veg? Once you cross the 200 time series mark, you should start thinking about your metrics more. Sign in Making statements based on opinion; back them up with references or personal experience. If all the label values are controlled by your application you will be able to count the number of all possible label combinations. what does the Query Inspector show for the query you have a problem with? Theres no timestamp anywhere actually. Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. Yeah, absent() is probably the way to go. which outputs 0 for an empty input vector, but that outputs a scalar *) in region drops below 4. Any other chunk holds historical samples and therefore is read-only. A common pattern is to export software versions as a build_info metric, Prometheus itself does this too: When Prometheus 2.43.0 is released this metric would be exported as: Which means that a time series with version=2.42.0 label would no longer receive any new samples. I.e., there's no way to coerce no datapoints to 0 (zero)? To avoid this its in general best to never accept label values from untrusted sources. binary operators to them and elements on both sides with the same label set Cardinality is the number of unique combinations of all labels. Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2, Prometheus promQL query is not showing 0 when metric data does not exists, PromQL - how to get an interval between result values, PromQL delta for each elment in values array, Trigger alerts according to the environment in alertmanger, Prometheus alertmanager includes resolved alerts in a new alert. instance_memory_usage_bytes: This shows the current memory used. Ive deliberately kept the setup simple and accessible from any address for demonstration. 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 article covered a lot of ground. 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? These queries are a good starting point. Prometheus has gained a lot of market traction over the years, and when combined with other open-source tools like Grafana, it provides a robust monitoring solution. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. This garbage collection, among other things, will look for any time series without a single chunk and remove it from memory. There is no equivalent functionality in a standard build of Prometheus, if any scrape produces some samples they will be appended to time series inside TSDB, creating new time series if needed. What sort of strategies would a medieval military use against a fantasy giant? As we mentioned before a time series is generated from metrics. If such a stack trace ended up as a label value it would take a lot more memory than other time series, potentially even megabytes. Variable of the type Query allows you to query Prometheus for a list of metrics, labels, or label values. Each chunk represents a series of samples for a specific time range. Why is there a voltage on my HDMI and coaxial cables? to your account, What did you do? When Prometheus sends an HTTP request to our application it will receive this response: This format and underlying data model are both covered extensively in Prometheus' own documentation. Finally, please remember that some people read these postings as an email Prometheus metrics can have extra dimensions in form of labels. That way even the most inexperienced engineers can start exporting metrics without constantly wondering Will this cause an incident?. The thing with a metric vector (a metric which has dimensions) is that only the series for it actually get exposed on /metrics which have been explicitly initialized. This helps Prometheus query data faster since all it needs to do is first locate the memSeries instance with labels matching our query and then find the chunks responsible for time range of the query. For example, this expression name match a certain pattern, in this case, all jobs that end with server: All regular expressions in Prometheus use RE2 Its least efficient when it scrapes a time series just once and never again - doing so comes with a significant memory usage overhead when compared to the amount of information stored using that memory. That's the query ( Counter metric): sum (increase (check_fail {app="monitor"} [20m])) by (reason) The result is a table of failure reason and its count. I'm still out of ideas here. I'm not sure what you mean by exposing a metric. You set up a Kubernetes cluster, installed Prometheus on it ,and ran some queries to check the clusters health. This is the modified flow with our patch: By running go_memstats_alloc_bytes / prometheus_tsdb_head_series query we know how much memory we need per single time series (on average), we also know how much physical memory we have available for Prometheus on each server, which means that we can easily calculate the rough number of time series we can store inside Prometheus, taking into account the fact the theres garbage collection overhead since Prometheus is written in Go: memory available to Prometheus / bytes per time series = our capacity. But before that, lets talk about the main components of Prometheus. For Prometheus to collect this metric we need our application to run an HTTP server and expose our metrics there. But the real risk is when you create metrics with label values coming from the outside world. This doesnt capture all complexities of Prometheus but gives us a rough estimate of how many time series we can expect to have capacity for. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. Any excess samples (after reaching sample_limit) will only be appended if they belong to time series that are already stored inside TSDB. It saves these metrics as time-series data, which is used to create visualizations and alerts for IT teams. Second rule does the same but only sums time series with status labels equal to "500". We know that time series will stay in memory for a while, even if they were scraped only once. what error message are you getting to show that theres a problem? It doesnt get easier than that, until you actually try to do it. To get rid of such time series Prometheus will run head garbage collection (remember that Head is the structure holding all memSeries) right after writing a block. After sending a request it will parse the response looking for all the samples exposed there. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Its not going to get you a quicker or better answer, and some people might This works well if errors that need to be handled are generic, for example Permission Denied: But if the error string contains some task specific information, for example the name of the file that our application didnt have access to, or a TCP connection error, then we might easily end up with high cardinality metrics this way: Once scraped all those time series will stay in memory for a minimum of one hour. The containers are named with a specific pattern: I need an alert when the number of container of the same pattern (eg. Run the following commands on the master node, only copy the kubeconfig and set up Flannel CNI. A simple request for the count (e.g., rio_dashorigin_memsql_request_fail_duration_millis_count) returns no datapoints). Making statements based on opinion; back them up with references or personal experience. @zerthimon You might want to use 'bool' with your comparator Since we know that the more labels we have the more time series we end up with, you can see when this can become a problem. All they have to do is set it explicitly in their scrape configuration. Prometheus allows us to measure health & performance over time and, if theres anything wrong with any service, let our team know before it becomes a problem. Each Prometheus is scraping a few hundred different applications, each running on a few hundred servers. are going to make it Its not difficult to accidentally cause cardinality problems and in the past weve dealt with a fair number of issues relating to it. Stumbled onto this post for something else unrelated, just was +1-ing this :). Prometheus does offer some options for dealing with high cardinality problems. What this means is that a single metric will create one or more time series. We know what a metric, a sample and a time series is. notification_sender-. Creating new time series on the other hand is a lot more expensive - we need to allocate new memSeries instances with a copy of all labels and keep it in memory for at least an hour. Returns a list of label names. It might seem simple on the surface, after all you just need to stop yourself from creating too many metrics, adding too many labels or setting label values from untrusted sources. I have a query that gets a pipeline builds and its divided by the number of change request open in a 1 month window, which gives a percentage. returns the unused memory in MiB for every instance (on a fictional cluster vishnur5217 May 31, 2020, 3:44am 1. Labels are stored once per each memSeries instance. Both of the representations below are different ways of exporting the same time series: Since everything is a label Prometheus can simply hash all labels using sha256 or any other algorithm to come up with a single ID that is unique for each time series. The main reason why we prefer graceful degradation is that we want our engineers to be able to deploy applications and their metrics with confidence without being subject matter experts in Prometheus. Time arrow with "current position" evolving with overlay number. In the same blog post we also mention one of the tools we use to help our engineers write valid Prometheus alerting rules. ***> wrote: You signed in with another tab or window. Once configured, your instances should be ready for access. When time series disappear from applications and are no longer scraped they still stay in memory until all chunks are written to disk and garbage collection removes them. Inside the Prometheus configuration file we define a scrape config that tells Prometheus where to send the HTTP request, how often and, optionally, to apply extra processing to both requests and responses. These queries will give you insights into node health, Pod health, cluster resource utilization, etc. The region and polygon don't match. privacy statement. but viewed in the tabular ("Console") view of the expression browser. Chunks will consume more memory as they slowly fill with more samples, after each scrape, and so the memory usage here will follow a cycle - we start with low memory usage when the first sample is appended, then memory usage slowly goes up until a new chunk is created and we start again. Is there a single-word adjective for "having exceptionally strong moral principles"? 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. Here at Labyrinth Labs, we put great emphasis on monitoring. Lets create a demo Kubernetes cluster and set up Prometheus to monitor it. The more labels we have or the more distinct values they can have the more time series as a result. For that reason we do tolerate some percentage of short lived time series even if they are not a perfect fit for Prometheus and cost us more memory. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, Simple succinct answer. How can I group labels in a Prometheus query? attacks, keep - grafana-7.1.0-beta2.windows-amd64, how did you install it? "no data". The next layer of protection is checks that run in CI (Continuous Integration) when someone makes a pull request to add new or modify existing scrape configuration for their application. With our example metric we know how many mugs were consumed, but what if we also want to know what kind of beverage it was? Is there a way to write the query so that a default value can be used if there are no data points - e.g., 0. To your second question regarding whether I have some other label on it, the answer is yes I do. Just add offset to the query. Of course there are many types of queries you can write, and other useful queries are freely available. But before doing that it needs to first check which of the samples belong to the time series that are already present inside TSDB and which are for completely new time series. That's the query (Counter metric): sum(increase(check_fail{app="monitor"}[20m])) by (reason). To learn more about our mission to help build a better Internet, start here. 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. I have a query that gets a pipeline builds and its divided by the number of change request open in a 1 month window, which gives a percentage. This is a deliberate design decision made by Prometheus developers. Its also worth mentioning that without our TSDB total limit patch we could keep adding new scrapes to Prometheus and that alone could lead to exhausting all available capacity, even if each scrape had sample_limit set and scraped fewer time series than this limit allows. Names and labels tell us what is being observed, while timestamp & value pairs tell us how that observable property changed over time, allowing us to plot graphs using this data. There is an open pull request which improves memory usage of labels by storing all labels as a single string. Operating such a large Prometheus deployment doesnt come without challenges. I cant see how absent() may help me here @juliusv yeah, I tried count_scalar() but I can't use aggregation with it. For that lets follow all the steps in the life of a time series inside Prometheus. A time series that was only scraped once is guaranteed to live in Prometheus for one to three hours, depending on the exact time of that scrape. Prometheus Authors 2014-2023 | Documentation Distributed under CC-BY-4.0. Adding labels is very easy and all we need to do is specify their names. If we were to continuously scrape a lot of time series that only exist for a very brief period then we would be slowly accumulating a lot of memSeries in memory until the next garbage collection. This is because the Prometheus server itself is responsible for timestamps. It's worth to add that if using Grafana you should set 'Connect null values' proeprty to 'always' in order to get rid of blank spaces in the graph. Explanation: Prometheus uses label matching in expressions. In both nodes, edit the /etc/hosts file to add the private IP of the nodes. Well occasionally send you account related emails. 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). No, only calling Observe() on a Summary or Histogram metric will add any observations (and only calling Inc() on a counter metric will increment it). The actual amount of physical memory needed by Prometheus will usually be higher as a result, since it will include unused (garbage) memory that needs to be freed by Go runtime. Returns a list of label values for the label in every metric. Is there a solutiuon to add special characters from software and how to do it. So when TSDB is asked to append a new sample by any scrape, it will first check how many time series are already present. The speed at which a vehicle is traveling. We can use these to add more information to our metrics so that we can better understand whats going on. Is it possible to rotate a window 90 degrees if it has the same length and width? This means that looking at how many time series an application could potentially export, and how many it actually exports, gives us two completely different numbers, which makes capacity planning a lot harder. to your account. 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? Have a question about this project? I am always registering the metric as defined (in the Go client library) by prometheus.MustRegister(). Why are trials on "Law & Order" in the New York Supreme Court? There is an open pull request on the Prometheus repository. Our metric will have a single label that stores the request path. 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. Although you can tweak some of Prometheus' behavior and tweak it more for use with short lived time series, by passing one of the hidden flags, its generally discouraged to do so. This is the last line of defense for us that avoids the risk of the Prometheus server crashing due to lack of memory. About an argument in Famine, Affluence and Morality. our free app that makes your Internet faster and safer. In addition to that in most cases we dont see all possible label values at the same time, its usually a small subset of all possible combinations. Using a query that returns "no data points found" in an expression. I'm sure there's a proper way to do this, but in the end, I used label_replace to add an arbitrary key-value label to each sub-query that I wished to add to the original values, and then applied an or to each. (pseudocode): This gives the same single value series, or no data if there are no alerts. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? 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. (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. whether someone is able to help out. How to tell which packages are held back due to phased updates. That map uses labels hashes as keys and a structure called memSeries as values. Have you fixed this issue? And then there is Grafana, which comes with a lot of built-in dashboards for Kubernetes monitoring. Monitor the health of your cluster and troubleshoot issues faster with pre-built dashboards that just work. You can use these queries in the expression browser, Prometheus HTTP API, or visualization tools like Grafana. Prometheus and PromQL (Prometheus Query Language) are conceptually very simple, but this means that all the complexity is hidden in the interactions between different elements of the whole metrics pipeline. For instance, the following query would return week-old data for all the time series with node_network_receive_bytes_total name: node_network_receive_bytes_total offset 7d Once TSDB knows if it has to insert new time series or update existing ones it can start the real work. When you add dimensionality (via labels to a metric), you either have to pre-initialize all the possible label combinations, which is not always possible, or live with missing metrics (then your PromQL computations become more cumbersome). What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? This makes a bit more sense with your explanation. Where does this (supposedly) Gibson quote come from? The reason why we still allow appends for some samples even after were above sample_limit is that appending samples to existing time series is cheap, its just adding an extra timestamp & value pair. In this query, you will find nodes that are intermittently switching between Ready" and NotReady" status continuously. Will this approach record 0 durations on every success? AFAIK it's not possible to hide them through Grafana. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. The result is a table of failure reason and its count. In our example case its a Counter class object. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. The below posts may be helpful for you to learn more about Kubernetes and our company. Ive added a data source(prometheus) in Grafana. This is in contrast to a metric without any dimensions, which always gets exposed as exactly one present series and is initialized to 0. If you do that, the line will eventually be redrawn, many times over. These will give you an overall idea about a clusters health. Or do you have some other label on it, so that the metric still only gets exposed when you record the first failued request it? How Intuit democratizes AI development across teams through reusability. How to react to a students panic attack in an oral exam? You signed in with another tab or window. Our metrics are exposed as a HTTP response. If this query also returns a positive value, then our cluster has overcommitted the memory. This had the effect of merging the series without overwriting any values. Since the default Prometheus scrape interval is one minute it would take two hours to reach 120 samples. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . This is because the only way to stop time series from eating memory is to prevent them from being appended to TSDB. Find centralized, trusted content and collaborate around the technologies you use most. 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! This pod wont be able to run because we dont have a node that has the label disktype: ssd. Name the nodes as Kubernetes Master and Kubernetes Worker. The more any application does for you, the more useful it is, the more resources it might need. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. want to sum over the rate of all instances, so we get fewer output time series, Vinayak is an experienced cloud consultant with a knack of automation, currently working with Cognizant Singapore. In reality though this is as simple as trying to ensure your application doesnt use too many resources, like CPU or memory - you can achieve this by simply allocating less memory and doing fewer computations. source, what your query is, what the query inspector shows, and any other The TSDB limit patch protects the entire Prometheus from being overloaded by too many time series. We will also signal back to the scrape logic that some samples were skipped. There is a single time series for each unique combination of metrics labels. By default Prometheus will create a chunk per each two hours of wall clock. 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). (fanout by job name) and instance (fanout by instance of the job), we might privacy statement. All rights reserved. We protect Both rules will produce new metrics named after the value of the record field. Thanks for contributing an answer to Stack Overflow! 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. Making statements based on opinion; back them up with references or personal experience. No error message, it is just not showing the data while using the JSON file from that website. You saw how PromQL basic expressions can return important metrics, which can be further processed with operators and functions. type (proc) like this: Assuming this metric contains one time series per running instance, you could The number of times some specific event occurred. A sample is something in between metric and time series - its a time series value for a specific timestamp. At this point, both nodes should be ready. your journey to Zero Trust. syntax. To get a better understanding of the impact of a short lived time series on memory usage lets take a look at another example. Find centralized, trusted content and collaborate around the technologies you use most. Why do many companies reject expired SSL certificates as bugs in bug bounties? Prometheus's query language supports basic logical and arithmetic operators. This is the standard flow with a scrape that doesnt set any sample_limit: With our patch we tell TSDB that its allowed to store up to N time series in total, from all scrapes, at any time.