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. If so I'll need to figure out a way to pre-initialize the metric which may be difficult since the label values may not be known a priori. 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. 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. You can run a variety of PromQL queries to pull interesting and actionable metrics from your Kubernetes cluster. Run the following commands in both nodes to disable SELinux and swapping: Also, change SELINUX=enforcing to SELINUX=permissive in the /etc/selinux/config file. PROMQL: how to add values when there is no data returned? What video game is Charlie playing in Poker Face S01E07? What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? 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. Especially when dealing with big applications maintained in part by multiple different teams, each exporting some metrics from their part of the stack. node_cpu_seconds_total: This returns the total amount of CPU time. For example, this expression If both the nodes are running fine, you shouldnt get any result for this query. The most basic layer of protection that we deploy are scrape limits, which we enforce on all configured scrapes. What does remote read means in Prometheus? Combined thats a lot of different metrics. website information which you think might be helpful for someone else to understand Of course, this article is not a primer on PromQL; you can browse through the PromQL documentation for more in-depth knowledge. If this query also returns a positive value, then our cluster has overcommitted the memory. By default we allow up to 64 labels on each time series, which is way more than most metrics would use. To select all HTTP status codes except 4xx ones, you could run: Return the 5-minute rate of the http_requests_total metric for the past 30 minutes, with a resolution of 1 minute. Here is the extract of the relevant options from Prometheus documentation: Setting all the label length related limits allows you to avoid a situation where extremely long label names or values end up taking too much memory. I've been using comparison operators in Grafana for a long while. 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. It would be easier if we could do this in the original query though. 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. At the moment of writing this post we run 916 Prometheus instances with a total of around 4.9 billion time series. 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. 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 which Operating System (and version) are you running it under? Please see data model and exposition format pages for more details. In the same blog post we also mention one of the tools we use to help our engineers write valid Prometheus alerting rules. binary operators to them and elements on both sides with the same label set Lets adjust the example code to do this. 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. A simple request for the count (e.g., rio_dashorigin_memsql_request_fail_duration_millis_count) returns no datapoints). We can add more metrics if we like and they will all appear in the HTTP response to the metrics endpoint. To get rid of such time series Prometheus will run head garbage collection (remember that Head is the structure holding all memSeries) right after writing a block. Why are trials on "Law & Order" in the New York Supreme Court? Can airtags be tracked from an iMac desktop, with no iPhone? Now we should pause to make an important distinction between metrics and time series. 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. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. How to show that an expression of a finite type must be one of the finitely many possible values? 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 default Prometheus will create a chunk per each two hours of wall clock. Please dont post the same question under multiple topics / subjects. This means that looking at how many time series an application could potentially export, and how many it actually exports, gives us two completely different numbers, which makes capacity planning a lot harder. Comparing current data with historical data. This means that Prometheus must check if theres already a time series with identical name and exact same set of labels present. 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. By setting this limit on all our Prometheus servers we know that it will never scrape more time series than we have memory for. feel that its pushy or irritating and therefore ignore it. To learn more, see our tips on writing great answers. To your second question regarding whether I have some other label on it, the answer is yes I do. 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. Its the chunk responsible for the most recent time range, including the time of our scrape. The Head Chunk is never memory-mapped, its always stored in memory. Prometheus will keep each block on disk for the configured retention period. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. How is Jesus " " (Luke 1:32 NAS28) different from a prophet (, Luke 1:76 NAS28)? In order to make this possible, it's necessary to tell Prometheus explicitly to not trying to match any labels by . Sign up for a free GitHub account to open an issue and contact its maintainers and the community. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . are going to make it Why is there a voltage on my HDMI and coaxial cables? what does the Query Inspector show for the query you have a problem with? 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). It doesnt get easier than that, until you actually try to do it. See this article for details. name match a certain pattern, in this case, all jobs that end with server: All regular expressions in Prometheus use RE2 source, what your query is, what the query inspector shows, and any other This is because the Prometheus server itself is responsible for timestamps. So it seems like I'm back to square one. group by returns a value of 1, so we subtract 1 to get 0 for each deployment and I now wish to add to this the number of alerts that are applicable to each deployment. 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. Well occasionally send you account related emails. Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. 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. Prometheus allows us to measure health & performance over time and, if theres anything wrong with any service, let our team know before it becomes a problem. Returns a list of label values for the label in every metric. There are a number of options you can set in your scrape configuration block. Lets create a demo Kubernetes cluster and set up Prometheus to monitor it. 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. In reality though this is as simple as trying to ensure your application doesnt use too many resources, like CPU or memory - you can achieve this by simply allocating less memory and doing fewer computations. Where does this (supposedly) Gibson quote come from? So when TSDB is asked to append a new sample by any scrape, it will first check how many time series are already present. Any other chunk holds historical samples and therefore is read-only. 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. If we let Prometheus consume more memory than it can physically use then it will crash. 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. Has 90% of ice around Antarctica disappeared in less than a decade? This is the standard Prometheus flow for a scrape that has the sample_limit option set: The entire scrape either succeeds or fails. Prometheus does offer some options for dealing with high cardinality problems. Simple, clear and working - thanks a lot. 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. syntax. Once theyre in TSDB its already too late. 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! 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. Now, lets install Kubernetes on the master node using kubeadm. 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). 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. You're probably looking for the absent function. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, Simple succinct answer. 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. 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. 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. I'm not sure what you mean by exposing a metric. I've created an expression that is intended to display percent-success for a given metric. How to react to a students panic attack in an oral exam? 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. And then there is Grafana, which comes with a lot of built-in dashboards for Kubernetes monitoring. The text was updated successfully, but these errors were encountered: It's recommended not to expose data in this way, partially for this reason. This is one argument for not overusing labels, but often it cannot be avoided. 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. Prometheus - exclude 0 values from query result, How Intuit democratizes AI development across teams through reusability. 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. 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. or Internet application, These queries will give you insights into node health, Pod health, cluster resource utilization, etc. This would happen if any time series was no longer being exposed by any application and therefore there was no scrape that would try to append more samples to it. By clicking Sign up for GitHub, you agree to our terms of service and I've added a data source (prometheus) in Grafana. 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 . 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. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. 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). 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 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. Prometheus metrics can have extra dimensions in form of labels. This thread has been automatically locked since there has not been any recent activity after it was closed. 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? Please open a new issue for related bugs. Why is this sentence from The Great Gatsby grammatical? 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. Is there a single-word adjective for "having exceptionally strong moral principles"? 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. You saw how PromQL basic expressions can return important metrics, which can be further processed with operators and functions. Is there a solutiuon to add special characters from software and how to do it. Although you can tweak some of Prometheus' behavior and tweak it more for use with short lived time series, by passing one of the hidden flags, its generally discouraged to do so. Operating such a large Prometheus deployment doesnt come without challenges. job and handler labels: Return a whole range of time (in this case 5 minutes up to the query time) Arithmetic binary operators The following binary arithmetic operators exist in Prometheus: + (addition) - (subtraction) * (multiplication) / (division) % (modulo) ^ (power/exponentiation) Since labels are copied around when Prometheus is handling queries this could cause significant memory usage increase. Being able to answer How do I X? yourself without having to wait for a subject matter expert allows everyone to be more productive and move faster, while also avoiding Prometheus experts from answering the same questions over and over again. Variable of the type Query allows you to query Prometheus for a list of metrics, labels, or label values. You can verify this by running the kubectl get nodes command on the master node. privacy statement. That map uses labels hashes as keys and a structure called memSeries as values. what does the Query Inspector show for the query you have a problem with? Finally we maintain a set of internal documentation pages that try to guide engineers through the process of scraping and working with metrics, with a lot of information thats specific to our environment. Time arrow with "current position" evolving with overlay number. Better to simply ask under the single best category you think fits and see The Linux Foundation has registered trademarks and uses trademarks. but viewed in the tabular ("Console") view of the expression browser. How to follow the signal when reading the schematic? 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. Not the answer you're looking for? Finally, please remember that some people read these postings as an email Connect and share knowledge within a single location that is structured and easy to search. This might require Prometheus to create a new chunk if needed. Ive added a data source(prometheus) in Grafana. ***> wrote: You signed in with another tab or window. 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. 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. Often it doesnt require any malicious actor to cause cardinality related problems. I'm still out of ideas here. The region and polygon don't match. returns the unused memory in MiB for every instance (on a fictional cluster Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. which outputs 0 for an empty input vector, but that outputs a scalar 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. Use it to get a rough idea of how much memory is used per time series and dont assume its that exact number. Neither of these solutions seem to retain the other dimensional information, they simply produce a scaler 0. If we configure a sample_limit of 100 and our metrics response contains 101 samples, then Prometheus wont scrape anything at all. This scenario is often described as cardinality explosion - some metric suddenly adds a huge number of distinct label values, creates a huge number of time series, causes Prometheus to run out of memory and you lose all observability as a result. In my case there haven't been any failures so rio_dashorigin_serve_manifest_duration_millis_count{Success="Failed"} returns no data points found. That's the query (Counter metric): sum(increase(check_fail{app="monitor"}[20m])) by (reason). Are there tables of wastage rates for different fruit and veg? There is a single time series for each unique combination of metrics labels. 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. A sample is something in between metric and time series - its a time series value for a specific timestamp. 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. Which in turn will double the memory usage of our Prometheus server. 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. First is the patch that allows us to enforce a limit on the total number of time series TSDB can store at any time. Monitor the health of your cluster and troubleshoot issues faster with pre-built dashboards that just work. result of a count() on a query that returns nothing should be 0 ? That way even the most inexperienced engineers can start exporting metrics without constantly wondering Will this cause an incident?. We know that time series will stay in memory for a while, even if they were scraped only once. Just add offset to the query. 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. Asking for help, clarification, or responding to other answers. privacy statement. 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. 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. Separate metrics for total and failure will work as expected. Yeah, absent() is probably the way to go. 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. 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. without any dimensional information. Knowing that it can quickly check if there are any time series already stored inside TSDB that have the same hashed value. 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. 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. The TSDB limit patch protects the entire Prometheus from being overloaded by too many time series. an EC2 regions with application servers running docker containers. and can help you on Setting label_limit provides some cardinality protection, but even with just one label name and huge number of values we can see high cardinality. Since the default Prometheus scrape interval is one minute it would take two hours to reach 120 samples. Even Prometheus' own client libraries had bugs that could expose you to problems like this. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. This helps us avoid a situation where applications are exporting thousands of times series that arent really needed. 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. or Internet application, ward off DDoS If you're looking for a All rights reserved. Is a PhD visitor considered as a visiting scholar? 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.
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