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Of course there are many types of queries you can write, and other useful queries are freely available. Thirdly Prometheus is written in Golang which is a language with garbage collection. Thats why what our application exports isnt really metrics or time series - its samples. 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 use these to add more information to our metrics so that we can better understand whats going on. 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. No error message, it is just not showing the data while using the JSON file from that website. Is it a bug? Theres no timestamp anywhere actually. Thanks for contributing an answer to Stack Overflow! The Linux Foundation has registered trademarks and uses trademarks. That's the query (Counter metric): sum(increase(check_fail{app="monitor"}[20m])) by (reason). Finally you will want to create a dashboard to visualize all your metrics and be able to spot trends. 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. Do new devs get fired if they can't solve a certain bug? name match a certain pattern, in this case, all jobs that end with server: All regular expressions in Prometheus use RE2 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. Here are two examples of instant vectors: You can also use range vectors to select a particular time range. What sort of strategies would a medieval military use against a fantasy giant? Internet-scale applications efficiently, At this point, both nodes should be ready. Also the link to the mailing list doesn't work for me. 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. To learn more, see our tips on writing great answers. We know that time series will stay in memory for a while, even if they were scraped only once. 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. This pod wont be able to run because we dont have a node that has the label disktype: ssd. Is there a single-word adjective for "having exceptionally strong moral principles"? I made the changes per the recommendation (as I understood it) and defined separate success and fail metrics. it works perfectly if one is missing as count() then returns 1 and the rule fires. To make things more complicated you may also hear about samples when reading Prometheus documentation. information which you think might be helpful for someone else to understand Subscribe to receive notifications of new posts: Subscription confirmed. 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). type (proc) like this: Assuming this metric contains one time series per running instance, you could our free app that makes your Internet faster and safer. There is a single time series for each unique combination of metrics labels. To your second question regarding whether I have some other label on it, the answer is yes I do. 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. For example, /api/v1/query?query=http_response_ok [24h]&time=t would return raw samples on the time range (t-24h . Variable of the type Query allows you to query Prometheus for a list of metrics, labels, or label values. https://github.com/notifications/unsubscribe-auth/AAg1mPXncyVis81Rx1mIWiXRDe0E1Dpcks5rIXe6gaJpZM4LOTeb. Our metric will have a single label that stores the request path. rate (http_requests_total [5m]) [30m:1m] Are there tables of wastage rates for different fruit and veg? Returns a list of label names. or Internet application, ward off DDoS 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 subquery for the deriv function uses the default resolution. Internally all time series are stored inside a map on a structure called Head. I've created an expression that is intended to display percent-success for a given metric. It enables us to enforce a hard limit on the number of time series we can scrape from each application instance. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. 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. Has 90% of ice around Antarctica disappeared in less than a decade? See these docs for details on how Prometheus calculates the returned results. What video game is Charlie playing in Poker Face S01E07? Once we appended sample_limit number of samples we start to be selective. This works fine when there are data points for all queries in the expression. 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. The text was updated successfully, but these errors were encountered: This is correct. At this point we should know a few things about Prometheus: With all of that in mind we can now see the problem - a metric with high cardinality, especially one with label values that come from the outside world, can easily create a huge number of time series in a very short time, causing cardinality explosion. 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. A time series is an instance of that metric, with a unique combination of all the dimensions (labels), plus a series of timestamp & value pairs - hence the name time series. The Head Chunk is never memory-mapped, its always stored in memory. I'm displaying Prometheus query on a Grafana table. Please help improve it by filing issues or pull requests. Or maybe we want to know if it was a cold drink or a hot one? Timestamps here can be explicit or implicit. Now comes the fun stuff. Which in turn will double the memory usage of our Prometheus server. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . I'm still out of ideas here. For example, I'm using the metric to record durations for quantile reporting. Your needs or your customers' needs will evolve over time and so you cant just draw a line on how many bytes or cpu cycles it can consume. We will also signal back to the scrape logic that some samples were skipped. Its not difficult to accidentally cause cardinality problems and in the past weve dealt with a fair number of issues relating to it. If the time series already exists inside TSDB then we allow the append to continue. (fanout by job name) and instance (fanout by instance of the job), we might If so it seems like this will skew the results of the query (e.g., quantiles). Return all time series with the metric http_requests_total: Return all time series with the metric http_requests_total and the given Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? Using regular expressions, you could select time series only for jobs whose Well be executing kubectl commands on the master node only. Prometheus's query language supports basic logical and arithmetic operators. Making statements based on opinion; back them up with references or personal experience. 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. You're probably looking for the absent function. Once the last chunk for this time series is written into a block and removed from the memSeries instance we have no chunks left. This article covered a lot of ground. 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. by (geo_region) < bool 4 Have a question about this project? About an argument in Famine, Affluence and Morality. Now, lets install Kubernetes on the master node using kubeadm. This is in contrast to a metric without any dimensions, which always gets exposed as exactly one present series and is initialized to 0. help customers build I'm displaying Prometheus query on a Grafana table. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. For example, if someone wants to modify sample_limit, lets say by changing existing limit of 500 to 2,000, for a scrape with 10 targets, thats an increase of 1,500 per target, with 10 targets thats 10*1,500=15,000 extra time series that might be scraped. 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. Already on GitHub? https://grafana.com/grafana/dashboards/2129. The more labels you have and the more values each label can take, the more unique combinations you can create and the higher the cardinality. Simply adding a label with two distinct values to all our metrics might double the number of time series we have to deal with. Is that correct? That way even the most inexperienced engineers can start exporting metrics without constantly wondering Will this cause an incident?. Knowing that it can quickly check if there are any time series already stored inside TSDB that have the same hashed value. 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. There's also count_scalar(), How is Jesus " " (Luke 1:32 NAS28) different from a prophet (, Luke 1:76 NAS28)? Does Counterspell prevent from any further spells being cast on a given turn? Sign up and get Kubernetes tips delivered straight to your inbox. Is it plausible for constructed languages to be used to affect thought and control or mold people towards desired outcomes? Under which circumstances? accelerate any 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. Not the answer you're looking for? Theres only one chunk that we can append to, its called the Head Chunk. Better to simply ask under the single best category you think fits and see One or more for historical ranges - these chunks are only for reading, Prometheus wont try to append anything here. 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. You set up a Kubernetes cluster, installed Prometheus on it ,and ran some queries to check the clusters health. Managed Service for Prometheus Cloud Monitoring Prometheus # ! This is because the Prometheus server itself is responsible for timestamps. Having a working monitoring setup is a critical part of the work we do for our clients. 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 . Once TSDB knows if it has to insert new time series or update existing ones it can start the real work. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 - 05:59, , 22:00 - 23:59. 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. What happens when somebody wants to export more time series or use longer labels? The speed at which a vehicle is traveling. Examples 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. Passing sample_limit is the ultimate protection from high cardinality. One thing you could do though to ensure at least the existence of failure series for the same series which have had successes, you could just reference the failure metric in the same code path without actually incrementing it, like so: That way, the counter for that label value will get created and initialized to 0. hackers at Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2, Show or hide query result depending on variable value in Grafana, Understanding the CPU Busy Prometheus query, Group Label value prefixes by Delimiter in Prometheus, Why time duration needs double dot for Prometheus but not for Victoria metrics, Using a Grafana Histogram with Prometheus Buckets. Here at Labyrinth Labs, we put great emphasis on monitoring. Will this approach record 0 durations on every success? Our CI would check that all Prometheus servers have spare capacity for at least 15,000 time series before the pull request is allowed to be merged. *) in region drops below 4. alert also has to fire if there are no (0) containers that match the pattern in region. Making statements based on opinion; back them up with references or personal experience. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. In both nodes, edit the /etc/sysctl.d/k8s.conf file to add the following two lines: Then reload the IPTables config using the sudo sysctl --system command. attacks. What sort of strategies would a medieval military use against a fantasy giant? One of the most important layers of protection is a set of patches we maintain on top of Prometheus. 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. The more any application does for you, the more useful it is, the more resources it might need. The below posts may be helpful for you to learn more about Kubernetes and our company. Our metrics are exposed as a HTTP response. Making statements based on opinion; back them up with references or personal experience. 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. to your account, What did you do? notification_sender-. 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. For Prometheus to collect this metric we need our application to run an HTTP server and expose our metrics there. Add field from calculation Binary operation. Are there tables of wastage rates for different fruit and veg? your journey to Zero Trust. So I still can't use that metric in calculations ( e.g., success / (success + fail) ) as those calculations will return no datapoints. Samples are stored inside chunks using "varbit" encoding which is a lossless compression scheme optimized for time series data. 2023 The Linux Foundation. If you need to obtain raw samples, then a range query must be sent to /api/v1/query. However, if i create a new panel manually with a basic commands then i can see the data on the dashboard. 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. 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. The result is a table of failure reason and its count. 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. Lets create a demo Kubernetes cluster and set up Prometheus to monitor it. After running the query, a table will show the current value of each result time series (one table row per output series). The difference with standard Prometheus starts when a new sample is about to be appended, but TSDB already stores the maximum number of time series its allowed to have. 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. Is a PhD visitor considered as a visiting scholar? 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. *) in region drops below 4. 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. The TSDB limit patch protects the entire Prometheus from being overloaded by too many time series. If both the nodes are running fine, you shouldnt get any result for this query. It would be easier if we could do this in the original query though. Samples are compressed using encoding that works best if there are continuous updates. Good to know, thanks for the quick response! Monitor the health of your cluster and troubleshoot issues faster with pre-built dashboards that just work. Please open a new issue for related bugs. Thanks for contributing an answer to Stack Overflow! Once configured, your instances should be ready for access. Prometheus query check if value exist. Lets adjust the example code to do this. 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. Even i am facing the same issue Please help me on this. notification_sender-. This patchset consists of two main elements. Next you will likely need to create recording and/or alerting rules to make use of your time series. I have a data model where some metrics are namespaced by client, environment and deployment name. 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. For that lets follow all the steps in the life of a time series inside Prometheus. There is an open pull request which improves memory usage of labels by storing all labels as a single string. 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. Today, let's look a bit closer at the two ways of selecting data in PromQL: instant vector selectors and range vector selectors. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. an EC2 regions with application servers running docker containers. rev2023.3.3.43278. 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. Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. I suggest you experiment more with the queries as you learn, and build a library of queries you can use for future projects. To learn more, see our tips on writing great answers. will get matched and propagated to the output. Comparing current data with historical data. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. @juliusv Thanks for clarifying that. Sign in So, specifically in response to your question: I am facing the same issue - please explain how you configured your data 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. Once theyre in TSDB its already too late. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. what error message are you getting to show that theres a problem? rev2023.3.3.43278. 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. Note that using subqueries unnecessarily is unwise. from and what youve done will help people to understand your problem. following for every instance: we could get the top 3 CPU users grouped by application (app) and process Has 90% of ice around Antarctica disappeared in less than a decade? You signed in with another tab or window. Sign in What this means is that a single metric will create one or more time series. Ive added a data source(prometheus) in Grafana. On Thu, Dec 15, 2016 at 6:24 PM, Lior Goikhburg ***@***. what does the Query Inspector show for the query you have a problem with? 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. This is a deliberate design decision made by Prometheus developers. Instead we count time series as we append them to TSDB. In this query, you will find nodes that are intermittently switching between Ready" and NotReady" status continuously. 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. for the same vector, making it a range vector: Note that an expression resulting in a range vector cannot be graphed directly, To learn more about our mission to help build a better Internet, start here. 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. This process is also aligned with the wall clock but shifted by one hour. These flags are only exposed for testing and might have a negative impact on other parts of Prometheus server. He has a Bachelor of Technology in Computer Science & Engineering from SRMS. more difficult for those people to help. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. which version of Grafana are you using? 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. 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. Thank you for subscribing! Using a query that returns "no data points found" in an expression. SSH into both servers and run the following commands to install Docker. These queries are a good starting point. 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. Since labels are copied around when Prometheus is handling queries this could cause significant memory usage increase. metric name, as measured over the last 5 minutes: Assuming that the http_requests_total time series all have the labels job When Prometheus collects metrics it records the time it started each collection and then it will use it to write timestamp & value pairs for each time series. and can help you on Connect and share knowledge within a single location that is structured and easy to search. Any excess samples (after reaching sample_limit) will only be appended if they belong to time series that are already stored inside TSDB. Redoing the align environment with a specific formatting. attacks, keep Of course, this article is not a primer on PromQL; you can browse through the PromQL documentation for more in-depth knowledge. A common class of mistakes is to have an error label on your metrics and pass raw error objects as values. Yeah, absent() is probably the way to go. 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? This selector is just a metric name.