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. *) in region drops below 4. alert also has to fire if there are no (0) containers that match the pattern in region. For example, I'm using the metric to record durations for quantile reporting. Finally, please remember that some people read these postings as an email Thirdly Prometheus is written in Golang which is a language with garbage collection. For that lets follow all the steps in the life of a time series inside Prometheus. All regular expressions in Prometheus use RE2 syntax. By clicking Sign up for GitHub, you agree to our terms of service and 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). Is there a solutiuon to add special characters from software and how to do it. without any dimensional information. This is the standard Prometheus flow for a scrape that has the sample_limit option set: The entire scrape either succeeds or fails. The result is a table of failure reason and its count. Redoing the align environment with a specific formatting. The main motivation seems to be that dealing with partially scraped metrics is difficult and youre better off treating failed scrapes as incidents. One Head Chunk - containing up to two hours of the last two hour wall clock slot. Once theyre in TSDB its already too late. 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. The process of sending HTTP requests from Prometheus to our application is called scraping. I know prometheus has comparison operators but I wasn't able to apply them. Minimising the environmental effects of my dyson brain. Is a PhD visitor considered as a visiting scholar? attacks, keep 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. I used a Grafana transformation which seems to work. 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. 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. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Not the answer you're looking for? Internally all time series are stored inside a map on a structure called Head. @rich-youngkin Yes, the general problem is non-existent series. We will also signal back to the scrape logic that some samples were skipped. However, if i create a new panel manually with a basic commands then i can see the data on the dashboard. A metric is an observable property with some defined dimensions (labels). What is the point of Thrower's Bandolier? In this article, you will learn some useful PromQL queries to monitor the performance of Kubernetes-based systems. If we try to append a sample with a timestamp higher than the maximum allowed time for current Head Chunk, then TSDB will create a new Head Chunk and calculate a new maximum time for it based on the rate of appends. The Prometheus data source plugin provides the following functions you can use in the Query input field. Does Counterspell prevent from any further spells being cast on a given turn? This process is also aligned with the wall clock but shifted by one hour. gabrigrec September 8, 2021, 8:12am #8. but viewed in the tabular ("Console") view of the expression browser. Explanation: Prometheus uses label matching in expressions. 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. Once it has a memSeries instance to work with it will append our sample to the Head Chunk. In the same blog post we also mention one of the tools we use to help our engineers write valid Prometheus alerting rules. And this brings us to the definition of cardinality in the context of metrics. AFAIK it's not possible to hide them through Grafana. See these docs for details on how Prometheus calculates the returned results. You can run a variety of PromQL queries to pull interesting and actionable metrics from your Kubernetes cluster. This means that our memSeries still consumes some memory (mostly labels) but doesnt really do anything. Prometheus - exclude 0 values from query result, How Intuit democratizes AI development across teams through reusability. rev2023.3.3.43278. more difficult for those people to help. Making statements based on opinion; back them up with references or personal experience. Up until now all time series are stored entirely in memory and the more time series you have, the higher Prometheus memory usage youll see. Run the following commands in both nodes to install kubelet, kubeadm, and kubectl. 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 We also limit the length of label names and values to 128 and 512 characters, which again is more than enough for the vast majority of scrapes. The struct definition for memSeries is fairly big, but all we really need to know is that it has a copy of all the time series labels and chunks that hold all the samples (timestamp & value pairs). It doesnt get easier than that, until you actually try to do it. But the key to tackling high cardinality was better understanding how Prometheus works and what kind of usage patterns will be problematic. information which you think might be helpful for someone else to understand Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. The more any application does for you, the more useful it is, the more resources it might need. Managed Service for Prometheus Cloud Monitoring Prometheus # ! 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. node_cpu_seconds_total: This returns the total amount of CPU time. Theres only one chunk that we can append to, its called the Head Chunk. 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. Asking for help, clarification, or responding to other answers. Add field from calculation Binary operation. whether someone is able to help out. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Then you must configure Prometheus scrapes in the correct way and deploy that to the right Prometheus server. 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. One or more for historical ranges - these chunks are only for reading, Prometheus wont try to append anything here. to your account, What did you do? What does remote read means in Prometheus? 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. instance_memory_usage_bytes: This shows the current memory used. Separate metrics for total and failure will work as expected. Even Prometheus' own client libraries had bugs that could expose you to problems like this. So when TSDB is asked to append a new sample by any scrape, it will first check how many time series are already present. Time series scraped from applications are kept in memory. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. 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. Well occasionally send you account related emails. 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. want to sum over the rate of all instances, so we get fewer output time series, notification_sender-. scheduler exposing these metrics about the instances it runs): The same expression, but summed by application, could be written like this: If the same fictional cluster scheduler exposed CPU usage metrics like the I'd expect to have also: Please use the prometheus-users mailing list for questions. Next, create a Security Group to allow access to the instances. If you do that, the line will eventually be redrawn, many times over. I.e., there's no way to coerce no datapoints to 0 (zero)? What happens when somebody wants to export more time series or use longer labels? 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. Once the last chunk for this time series is written into a block and removed from the memSeries instance we have no chunks left. 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. We protect Once we appended sample_limit number of samples we start to be selective. 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! So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 - 05:59, , 22:00 - 23:59. 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. You can use these queries in the expression browser, Prometheus HTTP API, or visualization tools like Grafana. Thats why what our application exports isnt really metrics or time series - its samples. 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. 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. This article covered a lot of ground. Thanks for contributing an answer to Stack Overflow! It saves these metrics as time-series data, which is used to create visualizations and alerts for IT teams. 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. Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2. Thank you for subscribing! Its the chunk responsible for the most recent time range, including the time of our scrape. 2023 The Linux Foundation. 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. Basically our labels hash is used as a primary key inside TSDB. 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. accelerate any So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . Is it possible to create a concave light? count(ALERTS) or (1-absent(ALERTS)), Alternatively, count(ALERTS) or vector(0). 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. Having a working monitoring setup is a critical part of the work we do for our clients. 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. In this blog post well cover some of the issues one might encounter when trying to collect many millions of time series per Prometheus instance. 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. Adding labels is very easy and all we need to do is specify their names. 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. Variable of the type Query allows you to query Prometheus for a list of metrics, labels, or label values. Use it to get a rough idea of how much memory is used per time series and dont assume its that exact number. Yeah, absent() is probably the way to go. 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. Improving your monitoring setup by integrating Cloudflares analytics data into Prometheus and Grafana Pint is a tool we developed to validate our Prometheus alerting rules and ensure they are always working website There is a maximum of 120 samples each chunk can hold. There is an open pull request which improves memory usage of labels by storing all labels as a single string. Chunks that are a few hours old are written to disk and removed from memory. 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? 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. The simplest construct of a PromQL query is an instant vector selector. Or maybe we want to know if it was a cold drink or a hot one? 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. The region and polygon don't match. To set up Prometheus to monitor app metrics: Download and install Prometheus. 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. 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. privacy statement. 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. The simplest way of doing this is by using functionality provided with client_python itself - see documentation here. Internet-scale applications efficiently, Using a query that returns "no data points found" in an expression. Comparing current data with historical 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. This single sample (data point) will create a time series instance that will stay in memory for over two and a half hours using resources, just so that we have a single timestamp & value pair. We know that the more labels on a metric, the more time series it can create. Well be executing kubectl commands on the master node only. To get a better understanding of the impact of a short lived time series on memory usage lets take a look at another example. 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? Second rule does the same but only sums time series with status labels equal to "500". 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. Better to simply ask under the single best category you think fits and see Please dont post the same question under multiple topics / subjects. I'm not sure what you mean by exposing a metric. This gives us confidence that we wont overload any Prometheus server after applying changes. Thanks for contributing an answer to Stack Overflow! Has 90% of ice around Antarctica disappeared in less than a decade? 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. 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.
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