prometheus query return 0 if no data

These queries are a good starting point. 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. This page will guide you through how to install and connect Prometheus and Grafana. This is because the only way to stop time series from eating memory is to prevent them from being appended to TSDB. 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. 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. It's worth to add that if using Grafana you should set 'Connect null values' proeprty to 'always' in order to get rid of blank spaces in the graph. This gives us confidence that we wont overload any Prometheus server after applying changes. If the error message youre getting (in a log file or on screen) can be quoted 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. Already on GitHub? Once theyre in TSDB its already too late. Returns a list of label values for the label in every metric. 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. The TSDB limit patch protects the entire Prometheus from being overloaded by too many time series. Are there tables of wastage rates for different fruit and veg? There are a number of options you can set in your scrape configuration block. I've added a data source (prometheus) in Grafana. However when one of the expressions returns no data points found the result of the entire expression is no data points found. 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. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. positions. what does the Query Inspector show for the query you have a problem with? 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. To learn more, see our tips on writing great answers. It enables us to enforce a hard limit on the number of time series we can scrape from each application instance. I'm displaying Prometheus query on a Grafana table. We also limit the length of label names and values to 128 and 512 characters, which again is more than enough for the vast majority of scrapes. We know that the more labels on a metric, the more time series it can create. 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. Is it possible to create a concave light? One or more for historical ranges - these chunks are only for reading, Prometheus wont try to append anything here. This article covered a lot of ground. 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. what error message are you getting to show that theres a problem? You can run a variety of PromQL queries to pull interesting and actionable metrics from your Kubernetes cluster. 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. 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. 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. This means that Prometheus must check if theres already a time series with identical name and exact same set of labels present. This is a deliberate design decision made by Prometheus developers. To set up Prometheus to monitor app metrics: Download and install Prometheus. The text was updated successfully, but these errors were encountered: It's recommended not to expose data in this way, partially for this reason. privacy statement. If your expression returns anything with labels, it won't match the time series generated by vector(0). 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. Simply adding a label with two distinct values to all our metrics might double the number of time series we have to deal with. @zerthimon You might want to use 'bool' with your comparator 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 patchset consists of two main elements. To get a better understanding of the impact of a short lived time series on memory usage lets take a look at another example. First is the patch that allows us to enforce a limit on the total number of time series TSDB can store at any time. 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. 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. Are you not exposing the fail metric when there hasn't been a failure yet? what does the Query Inspector show for the query you have a problem with? 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. Asking for help, clarification, or responding to other answers. When you add dimensionality (via labels to a metric), you either have to pre-initialize all the possible label combinations, which is not always possible, or live with missing metrics (then your PromQL computations become more cumbersome). If we configure a sample_limit of 100 and our metrics response contains 101 samples, then Prometheus wont scrape anything at all. You must define your metrics in your application, with names and labels that will allow you to work with resulting time series easily. Even Prometheus' own client libraries had bugs that could expose you to problems like this. A sample is something in between metric and time series - its a time series value for a specific timestamp. It will record the time it sends HTTP requests and use that later as the timestamp for all collected time series. rate (http_requests_total [5m]) [30m:1m] How to follow the signal when reading the schematic? If you do that, the line will eventually be redrawn, many times over. Samples are compressed using encoding that works best if there are continuous updates. But the key to tackling high cardinality was better understanding how Prometheus works and what kind of usage patterns will be problematic. A simple request for the count (e.g., rio_dashorigin_memsql_request_fail_duration_millis_count) returns no datapoints). Neither of these solutions seem to retain the other dimensional information, they simply produce a scaler 0. Monitor the health of your cluster and troubleshoot issues faster with pre-built dashboards that just work. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Well be executing kubectl commands on the master node only. Redoing the align environment with a specific formatting. Just add offset to the query. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . In our example we have two labels, content and temperature, and both of them can have two different values. the problem you have. Not the answer you're looking for? On the worker node, run the kubeadm joining command shown in the last step. What is the point of Thrower's Bandolier? rev2023.3.3.43278. The more any application does for you, the more useful it is, the more resources it might need. Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. - grafana-7.1.0-beta2.windows-amd64, how did you install it? which Operating System (and version) are you running it under? Second rule does the same but only sums time series with status labels equal to "500". Once we appended sample_limit number of samples we start to be selective. There's also count_scalar(), Cadvisors on every server provide container names. Does a summoned creature play immediately after being summoned by a ready action? It doesnt get easier than that, until you actually try to do it. *) in region drops below 4. For a list of trademarks of The Linux Foundation, please see our Trademark Usage page. I'd expect to have also: Please use the prometheus-users mailing list for questions. I.e., there's no way to coerce no datapoints to 0 (zero)? I know prometheus has comparison operators but I wasn't able to apply them. AFAIK it's not possible to hide them through Grafana. 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. The simplest construct of a PromQL query is an instant vector selector. list, which does not convey images, so screenshots etc. Every two hours Prometheus will persist chunks from memory onto the disk. Doubling the cube, field extensions and minimal polynoms. 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. 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. Once the last chunk for this time series is written into a block and removed from the memSeries instance we have no chunks left. Even i am facing the same issue Please help me on this. 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. accelerate any Has 90% of ice around Antarctica disappeared in less than a decade? Can I tell police to wait and call a lawyer when served with a search warrant? Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, How Intuit democratizes AI development across teams through reusability. 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. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. 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. 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. 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. I cant see how absent() may help me here @juliusv yeah, I tried count_scalar() but I can't use aggregation with it. Internally all time series are stored inside a map on a structure called Head. 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. Its not difficult to accidentally cause cardinality problems and in the past weve dealt with a fair number of issues relating to it. This works fine when there are data points for all queries in the expression. 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. following for every instance: we could get the top 3 CPU users grouped by application (app) and process Hello, I'm new at Grafan and Prometheus. The subquery for the deriv function uses the default resolution. Can airtags be tracked from an iMac desktop, with no iPhone? 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. notification_sender-. The text was updated successfully, but these errors were encountered: This is correct. website As we mentioned before a time series is generated from metrics. rev2023.3.3.43278. hackers at This process is also aligned with the wall clock but shifted by one hour. Now, lets install Kubernetes on the master node using kubeadm. 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. Bulk update symbol size units from mm to map units in rule-based symbology. I've been using comparison operators in Grafana for a long while. (pseudocode): summary = 0 + sum (warning alerts) + 2*sum (alerts (critical alerts)) This gives the same single value series, or no data if there are no alerts. Now comes the fun stuff. 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. You're probably looking for the absent function. This holds true for a lot of labels that we see are being used by engineers. What video game is Charlie playing in Poker Face S01E07? 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. We use Prometheus to gain insight into all the different pieces of hardware and software that make up our global network. Ive added a data source(prometheus) in Grafana. It saves these metrics as time-series data, which is used to create visualizations and alerts for IT teams. VictoriaMetrics handles rate () function in the common sense way I described earlier! Return all time series with the metric http_requests_total: Return all time series with the metric http_requests_total and the given 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. Here are two examples of instant vectors: You can also use range vectors to select a particular time range. 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. The below posts may be helpful for you to learn more about Kubernetes and our company. Subscribe to receive notifications of new posts: Subscription confirmed. 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. 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. The simplest way of doing this is by using functionality provided with client_python itself - see documentation here. 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 . Both of the representations below are different ways of exporting the same time series: Since everything is a label Prometheus can simply hash all labels using sha256 or any other algorithm to come up with a single ID that is unique for each time series. Have a question about this project? Cardinality is the number of unique combinations of all labels. it works perfectly if one is missing as count() then returns 1 and the rule fires. This helps us avoid a situation where applications are exporting thousands of times series that arent really needed. It will return 0 if the metric expression does not return anything. Managed Service for Prometheus https://goo.gle/3ZgeGxv About an argument in Famine, Affluence and Morality. 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. 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. 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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