We can add more metrics if we like and they will all appear in the HTTP response to the metrics endpoint. 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. Why are physically impossible and logically impossible concepts considered separate in terms of probability? list, which does not convey images, so screenshots etc. 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 . @zerthimon The following expr works for me Both patches give us two levels of protection. Well be executing kubectl commands on the master node only. And then there is Grafana, which comes with a lot of built-in dashboards for Kubernetes monitoring. The below posts may be helpful for you to learn more about Kubernetes and our company. Samples are stored inside chunks using "varbit" encoding which is a lossless compression scheme optimized for time series data. We will also signal back to the scrape logic that some samples were skipped. These queries will give you insights into node health, Pod health, cluster resource utilization, etc. You're probably looking for the absent function. Vinayak is an experienced cloud consultant with a knack of automation, currently working with Cognizant Singapore. 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. Those memSeries objects are storing all the time series information. With this simple code Prometheus client library will create a single metric. Is there a single-word adjective for "having exceptionally strong moral principles"? 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 So it seems like I'm back to square one. Does a summoned creature play immediately after being summoned by a ready action? 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. Please help improve it by filing issues or pull requests. 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. Stumbled onto this post for something else unrelated, just was +1-ing this :). Since labels are copied around when Prometheus is handling queries this could cause significant memory usage increase. I've added a data source (prometheus) in Grafana. You can query Prometheus metrics directly with its own query language: PromQL. Once it has a memSeries instance to work with it will append our sample to the Head Chunk. Using regular expressions, you could select time series only for jobs whose This means that our memSeries still consumes some memory (mostly labels) but doesnt really do anything. Each Prometheus is scraping a few hundred different applications, each running on a few hundred servers. This works fine when there are data points for all queries in the expression. Labels are stored once per each memSeries instance. Lets see what happens if we start our application at 00:25, allow Prometheus to scrape it once while it exports: And then immediately after the first scrape we upgrade our application to a new version: At 00:25 Prometheus will create our memSeries, but we will have to wait until Prometheus writes a block that contains data for 00:00-01:59 and runs garbage collection before that memSeries is removed from memory, which will happen at 03:00. Theres no timestamp anywhere actually. Next, create a Security Group to allow access to the instances. Since this happens after writing a block, and writing a block happens in the middle of the chunk window (two hour slices aligned to the wall clock) the only memSeries this would find are the ones that are orphaned - they received samples before, but not anymore. Can I tell police to wait and call a lawyer when served with a search warrant? I suggest you experiment more with the queries as you learn, and build a library of queries you can use for future projects. Im new at Grafan and Prometheus. 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. But before that, lets talk about the main components of Prometheus. I know prometheus has comparison operators but I wasn't able to apply them. node_cpu_seconds_total: This returns the total amount of CPU time. This is what i can see on Query Inspector. 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 install kubelet, kubeadm, and kubectl. 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. 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. Our HTTP response will now show more entries: As we can see we have an entry for each unique combination of labels. Once configured, your instances should be ready for access. 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. @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). Ive added a data source(prometheus) in Grafana. Is it possible to create a concave light? I'm displaying Prometheus query on a Grafana table. The subquery for the deriv function uses the default resolution. Lets adjust the example code to do this. 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. All chunks must be aligned to those two hour slots of wall clock time, so if TSDB was building a chunk for 10:00-11:59 and it was already full at 11:30 then it would create an extra chunk for the 11:30-11:59 time range. That map uses labels hashes as keys and a structure called memSeries as values. Find centralized, trusted content and collaborate around the technologies you use most. Lets pick client_python for simplicity, but the same concepts will apply regardless of the language you use. Please dont post the same question under multiple topics / subjects. Basically our labels hash is used as a primary key inside TSDB. Making statements based on opinion; back them up with references or personal experience. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . PromQL allows querying historical data and combining / comparing it to the current data. Youll be executing all these queries in the Prometheus expression browser, so lets get started. One of the most important layers of protection is a set of patches we maintain on top of Prometheus. This process helps to reduce disk usage since each block has an index taking a good chunk of disk space. Use it to get a rough idea of how much memory is used per time series and dont assume its that exact number. To avoid this its in general best to never accept label values from untrusted sources. So the maximum number of time series we can end up creating is four (2*2). (pseudocode): This gives the same single value series, or no data if there are no alerts. Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. We know that time series will stay in memory for a while, even if they were scraped only once. Any other chunk holds historical samples and therefore is read-only. 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. This is true both for client libraries and Prometheus server, but its more of an issue for Prometheus itself, since a single Prometheus server usually collects metrics from many applications, while an application only keeps its own metrics. For example, /api/v1/query?query=http_response_ok [24h]&time=t would return raw samples on the time range (t-24h . Other Prometheus components include a data model that stores the metrics, client libraries for instrumenting code, and PromQL for querying the metrics. But the real risk is when you create metrics with label values coming from the outside world. Prometheus Authors 2014-2023 | Documentation Distributed under CC-BY-4.0. 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. How can I group labels in a Prometheus query? 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. 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. notification_sender-. Under which circumstances? 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 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. ward off DDoS 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. Short story taking place on a toroidal planet or moon involving flying, How to handle a hobby that makes income in US, Doubling the cube, field extensions and minimal polynoms, Follow Up: struct sockaddr storage initialization by network format-string. On the worker node, run the kubeadm joining command shown in the last step. Has 90% of ice around Antarctica disappeared in less than a decade? Heres a screenshot that shows exact numbers: Thats an average of around 5 million time series per instance, but in reality we have a mixture of very tiny and very large instances, with the biggest instances storing around 30 million time series each. it works perfectly if one is missing as count() then returns 1 and the rule fires. So I still can't use that metric in calculations ( e.g., success / (success + fail) ) as those calculations will return no datapoints. The second patch modifies how Prometheus handles sample_limit - with our patch instead of failing the entire scrape it simply ignores excess time series. 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. After sending a request it will parse the response looking for all the samples exposed there. 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. If you look at the HTTP response of our example metric youll see that none of the returned entries have timestamps. If so it seems like this will skew the results of the query (e.g., quantiles). In our example we have two labels, content and temperature, and both of them can have two different values. Connect and share knowledge within a single location that is structured and easy to search. 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. 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. Once we do that we need to pass label values (in the same order as label names were specified) when incrementing our counter to pass this extra information. 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. Have a question about this project? 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. Its the chunk responsible for the most recent time range, including the time of our scrape. A common class of mistakes is to have an error label on your metrics and pass raw error objects as values. 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. Often it doesnt require any malicious actor to cause cardinality related problems. 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. 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. The Linux Foundation has registered trademarks and uses trademarks. Please open a new issue for related bugs. This is one argument for not overusing labels, but often it cannot be avoided. what does the Query Inspector show for the query you have a problem with? To your second question regarding whether I have some other label on it, the answer is yes I do. This article covered a lot of ground. How to show that an expression of a finite type must be one of the finitely many possible values? count(container_last_seen{name="container_that_doesn't_exist"}), What did you see instead? What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? Add field from calculation Binary operation. To make things more complicated you may also hear about samples when reading Prometheus documentation. 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. 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. returns the unused memory in MiB for every instance (on a fictional cluster Now comes the fun stuff. Is there a solutiuon to add special characters from software and how to do it. Have a question about this project? the problem you have. The more labels you have, or the longer the names and values are, the more memory it will use. 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? Managed Service for Prometheus https://goo.gle/3ZgeGxv To learn more about our mission to help build a better Internet, start here. Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. Thats why what our application exports isnt really metrics or time series - its samples. 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. See these docs for details on how Prometheus calculates the returned results. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, Simple succinct answer. If all the label values are controlled by your application you will be able to count the number of all possible label combinations. Adding labels is very easy and all we need to do is specify their names. All rights reserved. This would inflate Prometheus memory usage, which can cause Prometheus server to crash, if it uses all available physical memory. This pod wont be able to run because we dont have a node that has the label disktype: ssd. By default Prometheus will create a chunk per each two hours of wall clock. In my case there haven't been any failures so rio_dashorigin_serve_manifest_duration_millis_count{Success="Failed"} returns no data points found. I made the changes per the recommendation (as I understood it) and defined separate success and fail metrics. which version of Grafana are you using? This is optional, but may be useful if you don't already have an APM, or would like to use our templates and sample queries. For that lets follow all the steps in the life of a time series inside Prometheus. 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). privacy statement. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. These queries are a good starting point. Sign in 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. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. This is the last line of defense for us that avoids the risk of the Prometheus server crashing due to lack of memory. By setting this limit on all our Prometheus servers we know that it will never scrape more time series than we have memory for. We have hundreds of data centers spread across the world, each with dedicated Prometheus servers responsible for scraping all metrics. For operations between two instant vectors, the matching behavior can be modified. 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. how have you configured the query which is causing problems? This holds true for a lot of labels that we see are being used by engineers. What sort of strategies would a medieval military use against a fantasy giant? You can use these queries in the expression browser, Prometheus HTTP API, or visualization tools like Grafana. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. How Intuit democratizes AI development across teams through reusability. I'm still out of ideas here. Is it plausible for constructed languages to be used to affect thought and control or mold people towards desired outcomes? As we mentioned before a time series is generated from metrics. Returns a list of label names. Not the answer you're looking for? Minimising the environmental effects of my dyson brain. hackers at 2023 The Linux Foundation. Hmmm, upon further reflection, I'm wondering if this will throw the metrics off. 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. PromQL allows you to write queries and fetch information from the metric data collected by Prometheus. 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? Do new devs get fired if they can't solve a certain bug? All they have to do is set it explicitly in their scrape configuration. Youve learned about the main components of Prometheus, and its query language, PromQL. Here are two examples of instant vectors: You can also use range vectors to select a particular time range. Especially when dealing with big applications maintained in part by multiple different teams, each exporting some metrics from their part of the stack. Asking for help, clarification, or responding to other answers. Does Counterspell prevent from any further spells being cast on a given turn? What sort of strategies would a medieval military use against a fantasy giant? Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. following for every instance: we could get the top 3 CPU users grouped by application (app) and process Separate metrics for total and failure will work as expected. Managing the entire lifecycle of a metric from an engineering perspective is a complex process. How to follow the signal when reading the schematic? to your account. This is the standard Prometheus flow for a scrape that has the sample_limit option set: The entire scrape either succeeds or fails. result of a count() on a query that returns nothing should be 0 ? 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. 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. Perhaps I misunderstood, but it looks like any defined metrics that hasn't yet recorded any values can be used in a larger expression. 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. So when TSDB is asked to append a new sample by any scrape, it will first check how many time series are already present. 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). Is a PhD visitor considered as a visiting scholar? It enables us to enforce a hard limit on the number of time series we can scrape from each application instance. If both the nodes are running fine, you shouldnt get any result for this query. 11 Queries | Kubernetes Metric Data with PromQL, wide variety of applications, infrastructure, APIs, databases, and other sources. Our metric will have a single label that stores the request path. The text was updated successfully, but these errors were encountered: It's recommended not to expose data in this way, partially for this reason. There's also count_scalar(), In our example case its a Counter class object. 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. What this means is that a single metric will create one or more time series. 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. 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. but still preserve the job dimension: If we have two different metrics with the same dimensional labels, we can apply This is in contrast to a metric without any dimensions, which always gets exposed as exactly one present series and is initialized to 0. The containers are named with a specific pattern: I need an alert when the number of container of the same pattern (eg. t]. Have you fixed this issue? 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. 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 . 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. Making statements based on opinion; back them up with references or personal experience. which outputs 0 for an empty input vector, but that outputs a scalar 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. 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. 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. 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. instance_memory_usage_bytes: This shows the current memory used. 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. I can't work out how to add the alerts to the deployments whilst retaining the deployments for which there were no alerts returned: If I use sum with or, then I get this, depending on the order of the arguments to or: If I reverse the order of the parameters to or, I get what I am after: But I'm stuck now if I want to do something like apply a weight to alerts of a different severity level, e.g. count the number of running instances per application like this: This documentation is open-source. Variable of the type Query allows you to query Prometheus for a list of metrics, labels, or label values. 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.