website Ive 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. We can add more metrics if we like and they will all appear in the HTTP response to the metrics endpoint. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? That's the query (Counter metric): sum(increase(check_fail{app="monitor"}[20m])) by (reason). 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. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. The text was updated successfully, but these errors were encountered: It's recommended not to expose data in this way, partially for this reason. Play with bool Timestamps here can be explicit or implicit. Why are physically impossible and logically impossible concepts considered separate in terms of probability? hackers at I am always registering the metric as defined (in the Go client library) by prometheus.MustRegister(). 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. Each Prometheus is scraping a few hundred different applications, each running on a few hundred servers. Youll be executing all these queries in the Prometheus expression browser, so lets get started. VictoriaMetrics has other advantages compared to Prometheus, ranging from massively parallel operation for scalability, better performance, and better data compression, though what we focus on for this blog post is a rate () function handling. Not the answer you're looking for? By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. By default we allow up to 64 labels on each time series, which is way more than most metrics would use. The second patch modifies how Prometheus handles sample_limit - with our patch instead of failing the entire scrape it simply ignores excess time series. Simple, clear and working - thanks a lot. without any dimensional information. instance_memory_usage_bytes: This shows the current memory used. windows. Secondly this calculation is based on all memory used by Prometheus, not only time series data, so its just an approximation. One of the first problems youre likely to hear about when you start running your own Prometheus instances is cardinality, with the most dramatic cases of this problem being referred to as cardinality explosion. prometheus promql Share Follow edited Nov 12, 2020 at 12:27 So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 - 05:59, , 22:00 - 23:59. Do new devs get fired if they can't solve a certain bug? Prometheus provides a functional query language called PromQL (Prometheus Query Language) that lets the user select and aggregate time series data in real time. Heres a screenshot that shows exact numbers: Thats an average of around 5 million time series per instance, but in reality we have a mixture of very tiny and very large instances, with the biggest instances storing around 30 million time series each. This helps us avoid a situation where applications are exporting thousands of times series that arent really needed. If the error message youre getting (in a log file or on screen) can be quoted To avoid this its in general best to never accept label values from untrusted sources. for the same vector, making it a range vector: Note that an expression resulting in a range vector cannot be graphed directly, This pod wont be able to run because we dont have a node that has the label disktype: ssd. Prometheus simply counts how many samples are there in a scrape and if thats more than sample_limit allows it will fail the scrape. A simple request for the count (e.g., rio_dashorigin_memsql_request_fail_duration_millis_count) returns no datapoints). In AWS, create two t2.medium instances running CentOS. This is an example of a nested subquery. attacks, keep That response will have a list of, When Prometheus collects all the samples from our HTTP response it adds the timestamp of that collection and with all this information together we have a. Find centralized, trusted content and collaborate around the technologies you use most. We will also signal back to the scrape logic that some samples were skipped. 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. Run the following commands in both nodes to disable SELinux and swapping: Also, change SELINUX=enforcing to SELINUX=permissive in the /etc/selinux/config file. 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. What sort of strategies would a medieval military use against a fantasy giant? - I am using this in windows 10 for testing, which Operating System (and version) are you running it under? Prometheus will keep each block on disk for the configured retention period. In order to make this possible, it's necessary to tell Prometheus explicitly to not trying to match any labels by . Before running the query, create a Pod with the following specification: Before running the query, create a PersistentVolumeClaim with the following specification: This will get stuck in Pending state as we dont have a storageClass called manual" in our cluster. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. PromQL allows you to write queries and fetch information from the metric data collected by Prometheus. Lets adjust the example code to do this. Not the answer you're looking for? what error message are you getting to show that theres a problem? by (geo_region) < bool 4 Extra metrics exported by Prometheus itself tell us if any scrape is exceeding the limit and if that happens we alert the team responsible for it. If so it seems like this will skew the results of the query (e.g., quantiles). Lets pick client_python for simplicity, but the same concepts will apply regardless of the language you use. Better to simply ask under the single best category you think fits and see 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. 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. You signed in with another tab or window. ncdu: What's going on with this second size column? to get notified when one of them is not mounted anymore. 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. I can't work out how to add the alerts to the deployments whilst retaining the deployments for which there were no alerts returned: If I use sum with or, then I get this, depending on the order of the arguments to or: If I reverse the order of the parameters to or, I get what I am after: But I'm stuck now if I want to do something like apply a weight to alerts of a different severity level, e.g. We protect PromQL allows querying historical data and combining / comparing it to the current data. 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. How is Jesus " " (Luke 1:32 NAS28) different from a prophet (, Luke 1:76 NAS28)? What sort of strategies would a medieval military use against a fantasy giant? I don't know how you tried to apply the comparison operators, but if I use this very similar query: I get a result of zero for all jobs that have not restarted over the past day and a non-zero result for jobs that have had instances restart. Asking for help, clarification, or responding to other answers. or something like that. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. This is a deliberate design decision made by Prometheus developers. We use Prometheus to gain insight into all the different pieces of hardware and software that make up our global network. The simplest way of doing this is by using functionality provided with client_python itself - see documentation here. I've been using comparison operators in Grafana for a long while. 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. which outputs 0 for an empty input vector, but that outputs a scalar Stumbled onto this post for something else unrelated, just was +1-ing this :). While the sample_limit patch stops individual scrapes from using too much Prometheus capacity, which could lead to creating too many time series in total and exhausting total Prometheus capacity (enforced by the first patch), which would in turn affect all other scrapes since some new time series would have to be ignored. About an argument in Famine, Affluence and Morality. job and handler labels: Return a whole range of time (in this case 5 minutes up to the query time) are going to make it Use Prometheus to monitor app performance metrics. Are you not exposing the fail metric when there hasn't been a failure yet? Object, url:api/datasources/proxy/2/api/v1/query_range?query=wmi_logical_disk_free_bytes%7Binstance%3D~%22%22%2C%20volume%20!~%22HarddiskVolume.%2B%22%7D&start=1593750660&end=1593761460&step=20&timeout=60s, Powered by Discourse, best viewed with JavaScript enabled, 1 Node Exporter for Prometheus Dashboard EN 20201010 | Grafana Labs, https://grafana.com/grafana/dashboards/2129. Thirdly Prometheus is written in Golang which is a language with garbage collection. These flags are only exposed for testing and might have a negative impact on other parts of Prometheus server. What does remote read means in Prometheus? 11 Queries | Kubernetes Metric Data with PromQL, wide variety of applications, infrastructure, APIs, databases, and other sources. @juliusv Thanks for clarifying that. feel that its pushy or irritating and therefore ignore it. Now comes the fun stuff. But before that, lets talk about the main components of Prometheus. So perhaps the behavior I'm running into applies to any metric with a label, whereas a metric without any labels would behave as @brian-brazil indicated? Every two hours Prometheus will persist chunks from memory onto the disk. Run the following commands in both nodes to install kubelet, kubeadm, and kubectl. All chunks must be aligned to those two hour slots of wall clock time, so if TSDB was building a chunk for 10:00-11:59 and it was already full at 11:30 then it would create an extra chunk for the 11:30-11:59 time range. 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. This page will guide you through how to install and connect Prometheus and Grafana. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. In both nodes, edit the /etc/hosts file to add the private IP of the nodes. Blocks will eventually be compacted, which means that Prometheus will take multiple blocks and merge them together to form a single block that covers a bigger time range. At this point, both nodes should be ready. @zerthimon The following expr works for me 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. You must define your metrics in your application, with names and labels that will allow you to work with resulting time series easily. The result is a table of failure reason and its count. Once it has a memSeries instance to work with it will append our sample to the Head Chunk. 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. To learn more, see our tips on writing great answers. 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. 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. 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. Why is this sentence from The Great Gatsby grammatical? Is a PhD visitor considered as a visiting scholar? count the number of running instances per application like this: This documentation is open-source. Second rule does the same but only sums time series with status labels equal to "500". Having a working monitoring setup is a critical part of the work we do for our clients. Are there tables of wastage rates for different fruit and veg? We had a fair share of problems with overloaded Prometheus instances in the past and developed a number of tools that help us deal with them, including custom patches. If you're looking for a 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. Next you will likely need to create recording and/or alerting rules to make use of your time series. Its not difficult to accidentally cause cardinality problems and in the past weve dealt with a fair number of issues relating to it. Can airtags be tracked from an iMac desktop, with no iPhone? Yeah, absent() is probably the way to go. We know what a metric, a sample and a time series is. result of a count() on a query that returns nothing should be 0 ? Sign in To select all HTTP status codes except 4xx ones, you could run: http_requests_total {status!~"4.."} Subquery Return the 5-minute rate of the http_requests_total metric for the past 30 minutes, with a resolution of 1 minute. Our HTTP response will now show more entries: As we can see we have an entry for each unique combination of labels. In this query, you will find nodes that are intermittently switching between Ready" and NotReady" status continuously. I.e., there's no way to coerce no datapoints to 0 (zero)? It enables us to enforce a hard limit on the number of time series we can scrape from each application instance. Im new at Grafan and Prometheus. 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. 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. syntax. Hello, I'm new at Grafan and Prometheus. To your second question regarding whether I have some other label on it, the answer is yes I do. entire corporate networks, The nature of simulating nature: A Q&A with IBM Quantum researcher Dr. Jamie We've added a "Necessary cookies only" option to the cookie consent popup. PROMQL: how to add values when there is no data returned? 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. 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 only exception are memory-mapped chunks which are offloaded to disk, but will be read into memory if needed by queries. Ive deliberately kept the setup simple and accessible from any address for demonstration. Using a query that returns "no data points found" in an expression. This would inflate Prometheus memory usage, which can cause Prometheus server to crash, if it uses all available physical memory. I'm displaying Prometheus query on a Grafana table. We know that each time series will be kept in memory. With our custom patch we dont care how many samples are in a scrape. Those memSeries objects are storing all the time series information. Already on GitHub? I suggest you experiment more with the queries as you learn, and build a library of queries you can use for future projects. bay, When using Prometheus defaults and assuming we have a single chunk for each two hours of wall clock we would see this: Once a chunk is written into a block it is removed from memSeries and thus from memory. Here are two examples of instant vectors: You can also use range vectors to select a particular time range. However, if i create a new panel manually with a basic commands then i can see the data on the dashboard. Connect and share knowledge within a single location that is structured and easy to search. I then hide the original query. Add field from calculation Binary operation. Where does this (supposedly) Gibson quote come from? Our metrics are exposed as a HTTP response. Since this happens after writing a block, and writing a block happens in the middle of the chunk window (two hour slices aligned to the wall clock) the only memSeries this would find are the ones that are orphaned - they received samples before, but not anymore. will get matched and propagated to the output. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. name match a certain pattern, in this case, all jobs that end with server: All regular expressions in Prometheus use RE2 Have a question about this project? Cadvisors on every server provide container names. 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 This garbage collection, among other things, will look for any time series without a single chunk and remove it from memory. to your account. What am I doing wrong here in the PlotLegends specification? 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. There will be traps and room for mistakes at all stages of this process. Good to know, thanks for the quick response! It doesnt get easier than that, until you actually try to do it. Simply adding a label with two distinct values to all our metrics might double the number of time series we have to deal with. attacks. 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. Both patches give us two levels of protection. First is the patch that allows us to enforce a limit on the total number of time series TSDB can store at any time. Prometheus's query language supports basic logical and arithmetic operators. @rich-youngkin Yes, the general problem is non-existent series. I'm displaying Prometheus query on a Grafana table. There are a number of options you can set in your scrape configuration block. If all the label values are controlled by your application you will be able to count the number of all possible label combinations. 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. Each time series will cost us resources since it needs to be kept in memory, so the more time series we have, the more resources metrics will consume. Sign in What video game is Charlie playing in Poker Face S01E07? There is a maximum of 120 samples each chunk can hold. Under which circumstances? Lets create a demo Kubernetes cluster and set up Prometheus to monitor it. 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. With any monitoring system its important that youre able to pull out the right data. it works perfectly if one is missing as count() then returns 1 and the rule fires. In this article, you will learn some useful PromQL queries to monitor the performance of Kubernetes-based systems. For that lets follow all the steps in the life of a time series inside Prometheus. Connect and share knowledge within a single location that is structured and easy to search. There is an open pull request on the Prometheus repository. Explanation: Prometheus uses label matching in expressions. But the key to tackling high cardinality was better understanding how Prometheus works and what kind of usage patterns will be problematic. How to tell which packages are held back due to phased updates. That way even the most inexperienced engineers can start exporting metrics without constantly wondering Will this cause an incident?. what does the Query Inspector show for the query you have a problem with? Does Counterspell prevent from any further spells being cast on a given turn? What is the point of Thrower's Bandolier? With this simple code Prometheus client library will create a single metric. 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 . We know that the more labels on a metric, the more time series it can create. 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. Is there a single-word adjective for "having exceptionally strong moral principles"? If we let Prometheus consume more memory than it can physically use then it will crash. The process of sending HTTP requests from Prometheus to our application is called scraping. The number of times some specific event occurred. from and what youve done will help people to understand your problem. 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. Note that using subqueries unnecessarily is unwise. what error message are you getting to show that theres a problem? an EC2 regions with application servers running docker containers. Please open a new issue for related bugs. Finally we do, by default, set sample_limit to 200 - so each application can export up to 200 time series without any action. rate (http_requests_total [5m]) [30m:1m] 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 had the effect of merging the series without overwriting any values. This is the standard Prometheus flow for a scrape that has the sample_limit option set: The entire scrape either succeeds or fails. Thanks for contributing an answer to Stack Overflow! We can use these to add more information to our metrics so that we can better understand whats going on. A metric is an observable property with some defined dimensions (labels). 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. If you look at the HTTP response of our example metric youll see that none of the returned entries have timestamps. How do I align things in the following tabular environment? 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. rev2023.3.3.43278. I cant see how absent() may help me here @juliusv yeah, I tried count_scalar() but I can't use aggregation with it. 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. Youve learned about the main components of Prometheus, and its query language, PromQL. We covered some of the most basic pitfalls in our previous blog post on Prometheus - Monitoring our monitoring. notification_sender-. 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 number of time series depends purely on the number of labels and the number of all possible values these labels can take. If we configure a sample_limit of 100 and our metrics response contains 101 samples, then Prometheus wont scrape anything at all. Before running this query, create a Pod with the following specification: If this query returns a positive value, then the cluster has overcommitted the CPU. Or maybe we want to know if it was a cold drink or a hot one? And this brings us to the definition of cardinality in the context of metrics. count(container_last_seen{environment="prod",name="notification_sender.*",roles=".application-server."}) After a few hours of Prometheus running and scraping metrics we will likely have more than one chunk on our time series: Since all these chunks are stored in memory Prometheus will try to reduce memory usage by writing them to disk and memory-mapping. 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. This article covered a lot of ground. If we try to visualize how the perfect type of data Prometheus was designed for looks like well end up with this: A few continuous lines describing some observed properties. more difficult for those people to help. You're probably looking for the absent function. 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! or Internet application,
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