Internally all time series are stored inside a map on a structure called Head. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 - 05:59, , 22:00 - 23:59. There are a number of options you can set in your scrape configuration block. These flags are only exposed for testing and might have a negative impact on other parts of Prometheus server. how have you configured the query which is causing problems? To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Prometheus does offer some options for dealing with high cardinality problems. 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. What am I doing wrong here in the PlotLegends specification? To learn more, see our tips on writing great answers. @zerthimon You might want to use 'bool' with your comparator Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, How Intuit democratizes AI development across teams through reusability. 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. website This is a deliberate design decision made by Prometheus developers. To learn more, see our tips on writing great answers. Internally time series names are just another label called __name__, so there is no practical distinction between name and labels. This is one argument for not overusing labels, but often it cannot be avoided. 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? hackers at accelerate any I've been using comparison operators in Grafana for a long while. Here are two examples of instant vectors: You can also use range vectors to select a particular time range. Having a working monitoring setup is a critical part of the work we do for our clients. 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. First is the patch that allows us to enforce a limit on the total number of time series TSDB can store at any time. We know that time series will stay in memory for a while, even if they were scraped only once. I.e., there's no way to coerce no datapoints to 0 (zero)? 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. 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. Connect and share knowledge within a single location that is structured and easy to search. Connect and share knowledge within a single location that is structured and easy to search. Sign in By setting this limit on all our Prometheus servers we know that it will never scrape more time series than we have memory for. count(container_last_seen{environment="prod",name="notification_sender.*",roles=".application-server."}) Extra fields needed by Prometheus internals. In the following steps, you will create a two-node Kubernetes cluster (one master and one worker) in AWS. 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. There's also count_scalar(), 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. For example, I'm using the metric to record durations for quantile reporting. Thirdly Prometheus is written in Golang which is a language with garbage collection. privacy statement. In Prometheus pulling data is done via PromQL queries and in this article we guide the reader through 11 examples that can be used for Kubernetes specifically. What does remote read means in Prometheus? Timestamps here can be explicit or implicit. Adding labels is very easy and all we need to do is specify their names. 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. rev2023.3.3.43278. Youve learned about the main components of Prometheus, and its query language, PromQL. This holds true for a lot of labels that we see are being used by engineers. https://grafana.com/grafana/dashboards/2129. Now, lets install Kubernetes on the master node using kubeadm. With our custom patch we dont care how many samples are in a scrape. VictoriaMetrics handles rate () function in the common sense way I described earlier! Thanks, We will also signal back to the scrape logic that some samples were skipped. On the worker node, run the kubeadm joining command shown in the last step. notification_sender-. We can use these to add more information to our metrics so that we can better understand whats going on. 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. without any dimensional information. We know what a metric, a sample and a time series is. Combined thats a lot of different metrics. These queries are a good starting point. 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. In both nodes, edit the /etc/hosts file to add the private IP of the nodes. How to show that an expression of a finite type must be one of the finitely many possible values? Has 90% of ice around Antarctica disappeared in less than a decade? Thank you for subscribing! 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. 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. Monitoring Docker container metrics using cAdvisor, Use file-based service discovery to discover scrape targets, Understanding and using the multi-target exporter pattern, Monitoring Linux host metrics with the Node Exporter. Since labels are copied around when Prometheus is handling queries this could cause significant memory usage increase. or Internet application, Have a question about this project? 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. To this end, I set up the query to instant so that the very last data point is returned but, when the query does not return a value - say because the server is down and/or no scraping took place - the stat panel produces no data. vishnur5217 May 31, 2020, 3:44am 1. Once you cross the 200 time series mark, you should start thinking about your metrics more. and can help you on 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. notification_sender-. If we let Prometheus consume more memory than it can physically use then it will crash. The idea is that if done as @brian-brazil mentioned, there would always be a fail and success metric, because they are not distinguished by a label, but always are exposed. Each time series stored inside Prometheus (as a memSeries instance) consists of: The amount of memory needed for labels will depend on the number and length of these. Play with bool 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. 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. 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. Of course there are many types of queries you can write, and other useful queries are freely available. Then you must configure Prometheus scrapes in the correct way and deploy that to the right Prometheus server. The second patch modifies how Prometheus handles sample_limit - with our patch instead of failing the entire scrape it simply ignores excess time series. At this point, both nodes should be ready. Perhaps I misunderstood, but it looks like any defined metrics that hasn't yet recorded any values can be used in a larger expression. Already on GitHub? 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. Will this approach record 0 durations on every success? Where does this (supposedly) Gibson quote come from? There is a single time series for each unique combination of metrics labels. The advantage of doing this is that memory-mapped chunks dont use memory unless TSDB needs to read them. Selecting data from Prometheus's TSDB forms the basis of almost any useful PromQL query before . See this article for details. count(container_last_seen{name="container_that_doesn't_exist"}), What did you see instead? What sort of strategies would a medieval military use against a fantasy giant? Why is there a voltage on my HDMI and coaxial cables? Is it a bug? Connect and share knowledge within a single location that is structured and easy to search. Having good internal documentation that covers all of the basics specific for our environment and most common tasks is very important. The TSDB limit patch protects the entire Prometheus from being overloaded by too many time series. The result is a table of failure reason and its count. All rights reserved. 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. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. One Head Chunk - containing up to two hours of the last two hour wall clock slot. ncdu: What's going on with this second size column? 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. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. *) in region drops below 4. These are the sane defaults that 99% of application exporting metrics would never exceed. Every two hours Prometheus will persist chunks from memory onto the disk. for the same vector, making it a range vector: Note that an expression resulting in a range vector cannot be graphed directly, At the moment of writing this post we run 916 Prometheus instances with a total of around 4.9 billion time series. If both the nodes are running fine, you shouldnt get any result for this query. 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. A metric can be anything that you can express as a number, for example: To create metrics inside our application we can use one of many Prometheus client libraries. 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. Having better insight into Prometheus internals allows us to maintain a fast and reliable observability platform without too much red tape, and the tooling weve developed around it, some of which is open sourced, helps our engineers avoid most common pitfalls and deploy with confidence. Today, let's look a bit closer at the two ways of selecting data in PromQL: instant vector selectors and range vector selectors. What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? The region and polygon don't match. For that lets follow all the steps in the life of a time series inside Prometheus. 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. Returns a list of label names. To better handle problems with cardinality its best if we first get a better understanding of how Prometheus works and how time series consume memory. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . We will examine their use cases, the reasoning behind them, and some implementation details you should be aware of. what does the Query Inspector show for the query you have a problem with? This is in contrast to a metric without any dimensions, which always gets exposed as exactly one present series and is initialized to 0. Add field from calculation Binary operation. In this query, you will find nodes that are intermittently switching between Ready" and NotReady" status continuously. 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 Both rules will produce new metrics named after the value of the record field. following for every instance: we could get the top 3 CPU users grouped by application (app) and process 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. 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. There is an open pull request which improves memory usage of labels by storing all labels as a single string. are going to make it Ive deliberately kept the setup simple and accessible from any address for demonstration. 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. Now we should pause to make an important distinction between metrics and time series. About an argument in Famine, Affluence and Morality. 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. @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). All regular expressions in Prometheus use RE2 syntax. 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. Instead we count time series as we append them to TSDB. what error message are you getting to show that theres a problem? What this means is that a single metric will create one or more time series. This works fine when there are data points for all queries in the expression. Sign in 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. count the number of running instances per application like this: This documentation is open-source. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Making statements based on opinion; back them up with references or personal experience. Also, providing a reasonable amount of information about where youre starting 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? Run the following commands on the master node to set up Prometheus on the Kubernetes cluster: Next, run this command on the master node to check the Pods status: Once all the Pods are up and running, you can access the Prometheus console using kubernetes port forwarding. 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. 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. TSDB used in Prometheus is a special kind of database that was highly optimized for a very specific workload: This means that Prometheus is most efficient when continuously scraping the same time series over and over again. will get matched and propagated to the output. You're probably looking for the absent function. The text was updated successfully, but these errors were encountered: This is correct. Here at Labyrinth Labs, we put great emphasis on monitoring. I then hide the original query. 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. Labels are stored once per each memSeries instance. 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. 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. 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). 2023 The Linux Foundation. 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. 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. No error message, it is just not showing the data while using the JSON file from that website. So I still can't use that metric in calculations ( e.g., success / (success + fail) ) as those calculations will return no datapoints. Making statements based on opinion; back them up with references or personal experience. Subscribe to receive notifications of new posts: Subscription confirmed. rev2023.3.3.43278. However when one of the expressions returns no data points found the result of the entire expression is no data points found.In my case there haven't been any failures so rio_dashorigin_serve_manifest_duration_millis_count{Success="Failed"} returns no data points found.Is there a way to write the query so that a . To do that, run the following command on the master node: Next, create an SSH tunnel between your local workstation and the master node by running the following command on your local machine: If everything is okay at this point, you can access the Prometheus console at http://localhost:9090. new career direction, check out our open Next, create a Security Group to allow access to the instances. This is because the Prometheus server itself is responsible for timestamps. What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? 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. Cadvisors on every server provide container names. 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 . You can run a variety of PromQL queries to pull interesting and actionable metrics from your Kubernetes cluster. 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? from and what youve done will help people to understand your problem. Even Prometheus' own client libraries had bugs that could expose you to problems like this. 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. First rule will tell Prometheus to calculate per second rate of all requests and sum it across all instances of our server. So the maximum number of time series we can end up creating is four (2*2). Better to simply ask under the single best category you think fits and see Passing sample_limit is the ultimate protection from high cardinality. What is the point of Thrower's Bandolier? Run the following commands in both nodes to configure the Kubernetes repository. 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. But you cant keep everything in memory forever, even with memory-mapping parts of data. It would be easier if we could do this in the original query though. 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. 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. Lets say we have an application which we want to instrument, which means add some observable properties in the form of metrics that Prometheus can read from our application. Managing the entire lifecycle of a metric from an engineering perspective is a complex process. 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). This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. 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. 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. Not the answer you're looking for? positions. Since the default Prometheus scrape interval is one minute it would take two hours to reach 120 samples. Which in turn will double the memory usage of our Prometheus server. Is it suspicious or odd to stand by the gate of a GA airport watching the planes? Please dont post the same question under multiple topics / subjects. 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. Name the nodes as Kubernetes Master and Kubernetes Worker. Simply adding a label with two distinct values to all our metrics might double the number of time series we have to deal with. prometheus-promql query based on label value, Select largest label value in Prometheus query, Prometheus Query Overall average under a time interval, Prometheus endpoint of all available metrics. As we mentioned before a time series is generated from metrics. Our metric will have a single label that stores the request path. Is that correct? How do you get out of a corner when plotting yourself into a corner, Partner is not responding when their writing is needed in European project application. You signed in with another tab or window. Finally, please remember that some people read these postings as an email The Graph tab allows you to graph a query expression over a specified range of time. Those memSeries objects are storing all the time series information. Cardinality is the number of unique combinations of all labels. If we have a scrape with sample_limit set to 200 and the application exposes 201 time series, then all except one final time series will be accepted. He has a Bachelor of Technology in Computer Science & Engineering from SRMS. This is the standard Prometheus flow for a scrape that has the sample_limit option set: The entire scrape either succeeds or fails. I am always registering the metric as defined (in the Go client library) by prometheus.MustRegister(). Youll be executing all these queries in the Prometheus expression browser, so lets get started. Often it doesnt require any malicious actor to cause cardinality related problems. However when one of the expressions returns no data points found the result of the entire expression is no data points found. We have hundreds of data centers spread across the world, each with dedicated Prometheus servers responsible for scraping all metrics. Use Prometheus to monitor app performance metrics. However, the queries you will see here are a baseline" audit. What is the point of Thrower's Bandolier? It saves these metrics as time-series data, which is used to create visualizations and alerts for IT teams. 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. Run the following commands on the master node, only copy the kubeconfig and set up Flannel CNI. Our patched logic will then check if the sample were about to append belongs to a time series thats already stored inside TSDB or is it a new time series that needs to be created. A common class of mistakes is to have an error label on your metrics and pass raw error objects as values. Theres no timestamp anywhere actually. The more labels we have or the more distinct values they can have the more time series as a result.