These will give you an overall idea about a clusters health. By default we allow up to 64 labels on each time series, which is way more than most metrics would use. Have you fixed this issue? 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. The downside of all these limits is that breaching any of them will cause an error for the entire scrape. This is because the only way to stop time series from eating memory is to prevent them from being appended to TSDB. Managed Service for Prometheus https://goo.gle/3ZgeGxv 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. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? Is there a solutiuon to add special characters from software and how to do it. Since the default Prometheus scrape interval is one minute it would take two hours to reach 120 samples. 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. from and what youve done will help people to understand your problem. privacy statement. How is Jesus " " (Luke 1:32 NAS28) different from a prophet (, Luke 1:76 NAS28)? This means that our memSeries still consumes some memory (mostly labels) but doesnt really do anything. Next you will likely need to create recording and/or alerting rules to make use of your time series. Arithmetic binary operators The following binary arithmetic operators exist in Prometheus: + (addition) - (subtraction) * (multiplication) / (division) % (modulo) ^ (power/exponentiation) Use it to get a rough idea of how much memory is used per time series and dont assume its that exact number. To make things more complicated you may also hear about samples when reading Prometheus documentation. 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. your journey to Zero Trust. The simplest construct of a PromQL query is an instant vector selector. Also the link to the mailing list doesn't work for me. 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. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? Once configured, your instances should be ready for access. Both rules will produce new metrics named after the value of the record field. This is the last line of defense for us that avoids the risk of the Prometheus server crashing due to lack of memory. Prometheus will keep each block on disk for the configured retention period. For example, this expression 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. 1 Like. what does the Query Inspector show for the query you have a problem with? Cadvisors on every server provide container names. Finally we do, by default, set sample_limit to 200 - so each application can export up to 200 time series without any action. The main reason why we prefer graceful degradation is that we want our engineers to be able to deploy applications and their metrics with confidence without being subject matter experts in Prometheus. Instead we count time series as we append them to TSDB. 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. 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. rate (http_requests_total [5m]) [30m:1m] Other Prometheus components include a data model that stores the metrics, client libraries for instrumenting code, and PromQL for querying the metrics. which version of Grafana are you using? The more any application does for you, the more useful it is, the more resources it might need. 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? 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. The speed at which a vehicle is traveling. By default Prometheus will create a chunk per each two hours of wall clock. These are the sane defaults that 99% of application exporting metrics would never exceed. Asking for help, clarification, or responding to other answers. 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. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. We know that the more labels on a metric, the more time series it can create. binary operators to them and elements on both sides with the same label set 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 works well if errors that need to be handled are generic, for example Permission Denied: But if the error string contains some task specific information, for example the name of the file that our application didnt have access to, or a TCP connection error, then we might easily end up with high cardinality metrics this way: Once scraped all those time series will stay in memory for a minimum of one hour. The 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. and can help you on This works fine when there are data points for all queries in the expression. returns the unused memory in MiB for every instance (on a fictional cluster entire corporate networks, You saw how PromQL basic expressions can return important metrics, which can be further processed with operators and functions. rev2023.3.3.43278. The Graph tab allows you to graph a query expression over a specified range of time. Cadvisors on every server provide container names. Time arrow with "current position" evolving with overlay number. There is an open pull request which improves memory usage of labels by storing all labels as a single string. following for every instance: we could get the top 3 CPU users grouped by application (app) and process 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. Selecting data from Prometheus's TSDB forms the basis of almost any useful PromQL query before . Now comes the fun stuff. So the maximum number of time series we can end up creating is four (2*2). ***> wrote: You signed in with another tab or window. metric name, as measured over the last 5 minutes: Assuming that the http_requests_total time series all have the labels job However when one of the expressions returns no data points found the result of the entire expression is no data points found. For example, /api/v1/query?query=http_response_ok [24h]&time=t would return raw samples on the time range (t-24h . We use Prometheus to gain insight into all the different pieces of hardware and software that make up our global network. 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. I suggest you experiment more with the queries as you learn, and build a library of queries you can use for future projects. syntax. Explanation: Prometheus uses label matching in expressions. or Internet application, ward off DDoS notification_sender-. Run the following commands on the master node, only copy the kubeconfig and set up Flannel CNI. which Operating System (and version) are you running it under? This pod wont be able to run because we dont have a node that has the label disktype: ssd. What video game is Charlie playing in Poker Face S01E07? 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. Every time we add a new label to our metric we risk multiplying the number of time series that will be exported to Prometheus as the result. Visit 1.1.1.1 from any device to get started with See these docs for details on how Prometheus calculates the returned results. How Intuit democratizes AI development across teams through reusability. accelerate any Finally you will want to create a dashboard to visualize all your metrics and be able to spot trends. Internet-scale applications efficiently, The advantage of doing this is that memory-mapped chunks dont use memory unless TSDB needs to read them. 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. This gives us confidence that we wont overload any Prometheus server after applying changes. In order to make this possible, it's necessary to tell Prometheus explicitly to not trying to match any labels by . This page will guide you through how to install and connect Prometheus and Grafana. Which in turn will double the memory usage of our Prometheus server. 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. Find centralized, trusted content and collaborate around the technologies you use most. Sign in 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. what error message are you getting to show that theres a problem? With 1,000 random requests we would end up with 1,000 time series in Prometheus. 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. Windows 10, how have you configured the query which is causing problems? new career direction, check out our open I'm still out of ideas here. Theres only one chunk that we can append to, its called the Head Chunk. type (proc) like this: Assuming this metric contains one time series per running instance, you could Hello, I'm new at Grafan and Prometheus. Samples are stored inside chunks using "varbit" encoding which is a lossless compression scheme optimized for time series data. He has a Bachelor of Technology in Computer Science & Engineering from SRMS. 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. On the worker node, run the kubeadm joining command shown in the last step. Why are physically impossible and logically impossible concepts considered separate in terms of probability? This means that Prometheus must check if theres already a time series with identical name and exact same set of labels present. But you cant keep everything in memory forever, even with memory-mapping parts of data. In the same blog post we also mention one of the tools we use to help our engineers write valid Prometheus alerting rules. At this point, both nodes should be ready. 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. 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. but viewed in the tabular ("Console") view of the expression browser. 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. What happens when somebody wants to export more time series or use longer labels? The containers are named with a specific pattern: I need an alert when the number of container of the same pattern (eg. If your expression returns anything with labels, it won't match the time series generated by vector(0). To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Of course there are many types of queries you can write, and other useful queries are freely available. Prometheus metrics can have extra dimensions in form of labels. 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? Prometheus does offer some options for dealing with high cardinality problems. In this query, you will find nodes that are intermittently switching between Ready" and NotReady" status continuously. 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? Are there tables of wastage rates for different fruit and veg? Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. How can I group labels in a Prometheus query? 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. After sending a request it will parse the response looking for all the samples exposed there. Chunks that are a few hours old are written to disk and removed from memory. I.e., there's no way to coerce no datapoints to 0 (zero)? All rights reserved. About an argument in Famine, Affluence and Morality. 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. If you're looking for a to your account. A metric is an observable property with some defined dimensions (labels). You can use these queries in the expression browser, Prometheus HTTP API, or visualization tools like Grafana. 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. 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. Play with bool This is a deliberate design decision made by Prometheus developers. Its also worth mentioning that without our TSDB total limit patch we could keep adding new scrapes to Prometheus and that alone could lead to exhausting all available capacity, even if each scrape had sample_limit set and scraped fewer time series than this limit allows. Is there a single-word adjective for "having exceptionally strong moral principles"? Simple, clear and working - thanks a lot. Internally time series names are just another label called __name__, so there is no practical distinction between name and labels. Knowing that it can quickly check if there are any time series already stored inside TSDB that have the same hashed value. 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. result of a count() on a query that returns nothing should be 0 ? Cardinality is the number of unique combinations of all labels. 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). Please see data model and exposition format pages for more details. Has 90% of ice around Antarctica disappeared in less than a decade? By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Extra fields needed by Prometheus internals. 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. To get a better understanding of the impact of a short lived time series on memory usage lets take a look at another example. privacy statement. These queries will give you insights into node health, Pod health, cluster resource utilization, etc. Finally getting back to this. 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. 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 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. 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. source, what your query is, what the query inspector shows, and any other If you look at the HTTP response of our example metric youll see that none of the returned entries have timestamps. This is the standard Prometheus flow for a scrape that has the sample_limit option set: The entire scrape either succeeds or fails. Returns a list of label values for the label in every metric. What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? First rule will tell Prometheus to calculate per second rate of all requests and sum it across all instances of our server. 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. Lets adjust the example code to do this. Thanks, How to filter prometheus query by label value using greater-than, PromQL - Prometheus - query value as label, Why time duration needs double dot for Prometheus but not for Victoria metrics, How do you get out of a corner when plotting yourself into a corner. 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. What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? A simple request for the count (e.g., rio_dashorigin_memsql_request_fail_duration_millis_count) returns no datapoints). Find centralized, trusted content and collaborate around the technologies you use most. 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. Thanks for contributing an answer to Stack Overflow! Operating such a large Prometheus deployment doesnt come without challenges. You must define your metrics in your application, with names and labels that will allow you to work with resulting time series easily. Lets create a demo Kubernetes cluster and set up Prometheus to monitor it. Its the chunk responsible for the most recent time range, including the time of our scrape. 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. Thank you for subscribing! If so it seems like this will skew the results of the query (e.g., quantiles). t]. We can add more metrics if we like and they will all appear in the HTTP response to the metrics endpoint. The Prometheus data source plugin provides the following functions you can use in the Query input field. 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. I used a Grafana transformation which seems to work. I'm not sure what you mean by exposing a metric. Thanks for contributing an answer to Stack Overflow! 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.