Why is this sentence from The Great Gatsby grammatical? The more labels we have or the more distinct values they can have the more time series as a result. Sign in 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. Returns a list of label names. Is a PhD visitor considered as a visiting scholar? So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 - 05:59, , 22:00 - 23:59. A sample is something in between metric and time series - its a time series value for a specific timestamp. You can use these queries in the expression browser, Prometheus HTTP API, or visualization tools like Grafana. 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. 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. Hello, I'm new at Grafan and Prometheus. I made the changes per the recommendation (as I understood it) and defined separate success and fail metrics. Once configured, your instances should be ready for access. list, which does not convey images, so screenshots etc. Prometheus lets you query data in two different modes: The Console tab allows you to evaluate a query expression at the current time. 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. The Linux Foundation has registered trademarks and uses trademarks. 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. You can verify this by running the kubectl get nodes command on the master node. So it seems like I'm back to square one. To set up Prometheus to monitor app metrics: Download and install Prometheus. To do that, run the following command on the master node: Next, create an SSH tunnel between your local workstation and the master node by running the following command on your local machine: If everything is okay at this point, you can access the Prometheus console at http://localhost:9090. 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. attacks, keep Chunks that are a few hours old are written to disk and removed from memory. We know that each time series will be kept in memory. By default Prometheus will create a chunk per each two hours of wall clock. It would be easier if we could do this in the original query though. hackers at 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. but still preserve the job dimension: If we have two different metrics with the same dimensional labels, we can apply Lets adjust the example code to do this. This is an example of a nested subquery. I then hide the original query. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? Is it possible to rotate a window 90 degrees if it has the same length and width? Windows 10, how have you configured the query which is causing problems? Asking for help, clarification, or responding to other answers. This is one argument for not overusing labels, but often it cannot be avoided. 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. The way labels are stored internally by Prometheus also matters, but thats something the user has no control over. Prometheus simply counts how many samples are there in a scrape and if thats more than sample_limit allows it will fail the scrape. privacy statement. For a list of trademarks of The Linux Foundation, please see our Trademark Usage page. About an argument in Famine, Affluence and Morality. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. To learn more about our mission to help build a better Internet, start here. Connect and share knowledge within a single location that is structured and easy to search. This pod wont be able to run because we dont have a node that has the label disktype: ssd. 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. This gives us confidence that we wont overload any Prometheus server after applying changes. Now we should pause to make an important distinction between metrics and time series. 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 text was updated successfully, but these errors were encountered: This is correct. Find centralized, trusted content and collaborate around the technologies you use most. 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. positions. 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. result of a count() on a query that returns nothing should be 0 ? Run the following command on the master node: Once the command runs successfully, youll see joining instructions to add the worker node to the cluster. 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. 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. This selector is just a metric name. Select the query and do + 0. 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. 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. 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. Lets create a demo Kubernetes cluster and set up Prometheus to monitor it. Play with bool Every two hours Prometheus will persist chunks from memory onto the disk. This means that Prometheus must check if theres already a time series with identical name and exact same set of labels present. Use Prometheus to monitor app performance metrics. And this brings us to the definition of cardinality in the context of metrics. 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. Our metrics are exposed as a HTTP response. Prometheus does offer some options for dealing with high cardinality problems. Its not going to get you a quicker or better answer, and some people might 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. If you're looking for a are going to make it bay, Run the following commands on the master node, only copy the kubeconfig and set up Flannel CNI. Its very easy to keep accumulating time series in Prometheus until you run out of memory. 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. Thirdly Prometheus is written in Golang which is a language with garbage collection. Does a summoned creature play immediately after being summoned by a ready action? Prometheus metrics can have extra dimensions in form of labels. rate (http_requests_total [5m]) [30m:1m] With any monitoring system its important that youre able to pull out the right data. Of course there are many types of queries you can write, and other useful queries are freely available. 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. @zerthimon You might want to use 'bool' with your comparator If this query also returns a positive value, then our cluster has overcommitted the memory. syntax. Please open a new issue for related bugs. ncdu: What's going on with this second size column? Adding labels is very easy and all we need to do is specify their names. instance_memory_usage_bytes: This shows the current memory used. To learn more, see our tips on writing great answers. notification_sender-. For example, /api/v1/query?query=http_response_ok [24h]&time=t would return raw samples on the time range (t-24h . I've been using comparison operators in Grafana for a long while. Passing sample_limit is the ultimate protection from high cardinality. If the error message youre getting (in a log file or on screen) can be quoted 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? 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. Now comes the fun stuff. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. which version of Grafana are you using? 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? It will return 0 if the metric expression does not return anything. what does the Query Inspector show for the query you have a problem with? But the key to tackling high cardinality was better understanding how Prometheus works and what kind of usage patterns will be problematic. 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. What this means is that a single metric will create one or more time series. This article covered a lot of ground. 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. Managing the entire lifecycle of a metric from an engineering perspective is a complex process. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. This might require Prometheus to create a new chunk if needed. One Head Chunk - containing up to two hours of the last two hour wall clock slot. This helps Prometheus query data faster since all it needs to do is first locate the memSeries instance with labels matching our query and then find the chunks responsible for time range of the query. 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. Once it has a memSeries instance to work with it will append our sample to the Head Chunk. I believe it's the logic that it's written, but is there any . 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. 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. All rights reserved. In this article, you will learn some useful PromQL queries to monitor the performance of Kubernetes-based systems. If you need to obtain raw samples, then a range query must be sent to /api/v1/query. But you cant keep everything in memory forever, even with memory-mapping parts of data. website Looking to learn more? Thanks for contributing an answer to Stack Overflow! Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2, Prometheus promQL query is not showing 0 when metric data does not exists, PromQL - how to get an interval between result values, PromQL delta for each elment in values array, Trigger alerts according to the environment in alertmanger, Prometheus alertmanager includes resolved alerts in a new alert. Time series scraped from applications are kept in memory. Having good internal documentation that covers all of the basics specific for our environment and most common tasks is very important. This is because the Prometheus server itself is responsible for timestamps. how have you configured the query which is causing problems? notification_sender-. I am always registering the metric as defined (in the Go client library) by prometheus.MustRegister(). There's also count_scalar(), 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. 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 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. or Internet application, Here are two examples of instant vectors: You can also use range vectors to select a particular time range. Selecting data from Prometheus's TSDB forms the basis of almost any useful PromQL query before . Have a question about this project? How is Jesus " " (Luke 1:32 NAS28) different from a prophet (, Luke 1:76 NAS28)? 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. Second rule does the same but only sums time series with status labels equal to "500". In my case there haven't been any failures so rio_dashorigin_serve_manifest_duration_millis_count{Success="Failed"} returns no data points found. With our custom patch we dont care how many samples are in a scrape. I'm sure there's a proper way to do this, but in the end, I used label_replace to add an arbitrary key-value label to each sub-query that I wished to add to the original values, and then applied an or to each. 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! count(container_last_seen{name="container_that_doesn't_exist"}), What did you see instead? Prometheus query check if value exist. count the number of running instances per application like this: This documentation is open-source. job and handler labels: Return a whole range of time (in this case 5 minutes up to the query time) metric name, as measured over the last 5 minutes: Assuming that the http_requests_total time series all have the labels job The simplest construct of a PromQL query is an instant vector selector. The Prometheus data source plugin provides the following functions you can use in the Query input field. privacy statement. These will give you an overall idea about a clusters health. 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. 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.
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