prometheus query return 0 if no data

This means that Prometheus must check if theres already a time series with identical name and exact same set of labels present. Going back to our metric with error labels we could imagine a scenario where some operation returns a huge error message, or even stack trace with hundreds of lines. 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. Each chunk represents a series of samples for a specific time range. Variable of the type Query allows you to query Prometheus for a list of metrics, labels, or label values. Any other chunk holds historical samples and therefore is read-only. Setting label_limit provides some cardinality protection, but even with just one label name and huge number of values we can see high cardinality. 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. are going to make it Internet-scale applications efficiently, For Prometheus to collect this metric we need our application to run an HTTP server and expose our metrics there. for the same vector, making it a range vector: Note that an expression resulting in a range vector cannot be graphed directly, Using a query that returns "no data points found" in an expression. 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. 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. Connect and share knowledge within a single location that is structured and easy to search. Redoing the align environment with a specific formatting. 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. However, the queries you will see here are a baseline" audit. rate (http_requests_total [5m]) [30m:1m] Are there tables of wastage rates for different fruit and veg? 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. 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 what i can see on Query Inspector. Return the per-second rate for all time series with the http_requests_total The subquery for the deriv function uses the default resolution. The thing with a metric vector (a metric which has dimensions) is that only the series for it actually get exposed on /metrics which have been explicitly initialized. 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. For example, /api/v1/query?query=http_response_ok [24h]&time=t would return raw samples on the time range (t-24h . The Linux Foundation has registered trademarks and uses trademarks. The TSDB limit patch protects the entire Prometheus from being overloaded by too many time series. Next you will likely need to create recording and/or alerting rules to make use of your time series. In this query, you will find nodes that are intermittently switching between Ready" and NotReady" status continuously. 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. Asking for help, clarification, or responding to other answers. Better to simply ask under the single best category you think fits and see 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. To better handle problems with cardinality its best if we first get a better understanding of how Prometheus works and how time series consume memory. Prometheus does offer some options for dealing with high cardinality problems. But before that, lets talk about the main components of Prometheus. Run the following commands on the master node, only copy the kubeconfig and set up Flannel CNI. If we configure a sample_limit of 100 and our metrics response contains 101 samples, then Prometheus wont scrape anything at all. Returns a list of label values for the label in every metric. 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. job and handler labels: Return a whole range of time (in this case 5 minutes up to the query time) Please help improve it by filing issues or pull requests. The most basic layer of protection that we deploy are scrape limits, which we enforce on all configured scrapes. vishnur5217 May 31, 2020, 3:44am 1. Another reason is that trying to stay on top of your usage can be a challenging task. This works fine when there are data points for all queries in the expression. Passing sample_limit is the ultimate protection from high cardinality. Can airtags be tracked from an iMac desktop, with no iPhone? Both patches give us two levels of protection. Play with bool Blocks will eventually be compacted, which means that Prometheus will take multiple blocks and merge them together to form a single block that covers a bigger time range. Just add offset to the query. To avoid this its in general best to never accept label values from untrusted sources. Prometheus query check if value exist. Sign up and get Kubernetes tips delivered straight to your inbox. We have hundreds of data centers spread across the world, each with dedicated Prometheus servers responsible for scraping all metrics. 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. what error message are you getting to show that theres a problem? Time series scraped from applications are kept in memory. The text was updated successfully, but these errors were encountered: This is correct. Cardinality is the number of unique combinations of all labels. Is it possible to create a concave light? By setting this limit on all our Prometheus servers we know that it will never scrape more time series than we have memory for. No error message, it is just not showing the data while using the JSON file from that website. 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 Does a summoned creature play immediately after being summoned by a ready action? 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. PromQL allows you to write queries and fetch information from the metric data collected by Prometheus. This article covered a lot of ground. Our metrics are exposed as a HTTP response. attacks, keep By clicking Sign up for GitHub, you agree to our terms of service and To get a better idea of this problem lets adjust our example metric to track HTTP requests. Connect and share knowledge within a single location that is structured and easy to search. These will give you an overall idea about a clusters health. The result is a table of failure reason and its count. These flags are only exposed for testing and might have a negative impact on other parts of Prometheus server. Its not going to get you a quicker or better answer, and some people might Instead we count time series as we append them to TSDB. 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? 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. How do I align things in the following tabular environment? But I'm stuck now if I want to do something like apply a weight to alerts of a different severity level, e.g. 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. This is in contrast to a metric without any dimensions, which always gets exposed as exactly one present series and is initialized to 0. t]. Having a working monitoring setup is a critical part of the work we do for our clients. 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. Is there a solutiuon to add special characters from software and how to do it. With any monitoring system its important that youre able to pull out the right data. Making statements based on opinion; back them up with references or personal experience. 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. 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. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Of course, this article is not a primer on PromQL; you can browse through the PromQL documentation for more in-depth knowledge. VictoriaMetrics handles rate () function in the common sense way I described earlier! 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. If you look at the HTTP response of our example metric youll see that none of the returned entries have timestamps. our free app that makes your Internet faster and safer. If the total number of stored time series is below the configured limit then we append the sample as usual. There is a maximum of 120 samples each chunk can hold. Youve learned about the main components of Prometheus, and its query language, PromQL. Monitor the health of your cluster and troubleshoot issues faster with pre-built dashboards that just work. 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. 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. Im new at Grafan and Prometheus. Is a PhD visitor considered as a visiting scholar? 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. The simplest construct of a PromQL query is an instant vector selector. If the time series doesnt exist yet and our append would create it (a new memSeries instance would be created) then we skip this sample. Yeah, absent() is probably the way to go. Our HTTP response will now show more entries: As we can see we have an entry for each unique combination of labels. 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. 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. count(container_last_seen{name="container_that_doesn't_exist"}), What did you see instead? It will return 0 if the metric expression does not return anything. Is it suspicious or odd to stand by the gate of a GA airport watching the planes? Prometheus metrics can have extra dimensions in form of labels. Basically our labels hash is used as a primary key inside TSDB. or something like that. But you cant keep everything in memory forever, even with memory-mapping parts of data. PromQL queries the time series data and returns all elements that match the metric name, along with their values for a particular point in time (when the query runs). Thanks for contributing an answer to Stack Overflow! On the worker node, run the kubeadm joining command shown in the last step. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. @zerthimon The following expr works for me This doesnt capture all complexities of Prometheus but gives us a rough estimate of how many time series we can expect to have capacity for. Even Prometheus' own client libraries had bugs that could expose you to problems like this. Will this approach record 0 durations on every success? 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. For example, I'm using the metric to record durations for quantile reporting. Not the answer you're looking for? We know that the more labels on a metric, the more time series it can create. These queries will give you insights into node health, Pod health, cluster resource utilization, etc. Prometheus Authors 2014-2023 | Documentation Distributed under CC-BY-4.0. 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. want to sum over the rate of all instances, so we get fewer output time series, or Internet application, ward off DDoS This patchset consists of two main elements. Prometheus lets you query data in two different modes: The Console tab allows you to evaluate a query expression at the current time. There's also count_scalar(), Looking at memory usage of such Prometheus server we would see this pattern repeating over time: The important information here is that short lived time series are expensive. 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. 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. @rich-youngkin Yes, the general problem is non-existent series. - I am using this in windows 10 for testing, which Operating System (and version) are you running it under? Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. Those memSeries objects are storing all the time series information. The more labels you have, or the longer the names and values are, the more memory it will use. TSDB will try to estimate when a given chunk will reach 120 samples and it will set the maximum allowed time for current Head Chunk accordingly. Having good internal documentation that covers all of the basics specific for our environment and most common tasks is very important. To your second question regarding whether I have some other label on it, the answer is yes I do. I am always registering the metric as defined (in the Go client library) by prometheus.MustRegister(). If all the label values are controlled by your application you will be able to count the number of all possible label combinations. instance_memory_usage_bytes: This shows the current memory used. By default Prometheus will create a chunk per each two hours of wall clock. This works fine when there are data points for all queries in the expression. 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. I'm not sure what you mean by exposing a metric. Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. To set up Prometheus to monitor app metrics: Download and install Prometheus. There will be traps and room for mistakes at all stages of this process. Is that correct? which outputs 0 for an empty input vector, but that outputs a scalar A metric is an observable property with some defined dimensions (labels). Asking for help, clarification, or responding to other answers. Well be executing kubectl commands on the master node only. your journey to Zero Trust. 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. 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. Even i am facing the same issue Please help me on this. That response will have a list of, When Prometheus collects all the samples from our HTTP response it adds the timestamp of that collection and with all this information together we have a. 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. Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2. 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! 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. 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. 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. Lets adjust the example code to do this. Prometheus has gained a lot of market traction over the years, and when combined with other open-source tools like Grafana, it provides a robust monitoring solution. It might seem simple on the surface, after all you just need to stop yourself from creating too many metrics, adding too many labels or setting label values from untrusted sources. These are the sane defaults that 99% of application exporting metrics would never exceed. What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? Why are trials on "Law & Order" in the New York Supreme Court? 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. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. 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. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. Return all time series with the metric http_requests_total: Return all time series with the metric http_requests_total and the given To subscribe to this RSS feed, copy and paste this URL into your RSS reader. 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. To learn more, see our tips on writing great answers. However, if i create a new panel manually with a basic commands then i can see the data on the dashboard. 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. 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. To get a better understanding of the impact of a short lived time series on memory usage lets take a look at another example. Finally getting back to this. Find centralized, trusted content and collaborate around the technologies you use most. how have you configured the query which is causing problems? Both rules will produce new metrics named after the value of the record field. He has a Bachelor of Technology in Computer Science & Engineering from SRMS. which version of Grafana are you using? 2023 The Linux Foundation. Well occasionally send you account related emails. The advantage of doing this is that memory-mapped chunks dont use memory unless TSDB needs to read them. We know that time series will stay in memory for a while, even if they were scraped only once. Once we appended sample_limit number of samples we start to be selective. 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. If the time series already exists inside TSDB then we allow the append to continue. This garbage collection, among other things, will look for any time series without a single chunk and remove it from memory. 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? That's the query ( Counter metric): sum (increase (check_fail {app="monitor"} [20m])) by (reason) The result is a table of failure reason and its count. Going back to our time series - at this point Prometheus either creates a new memSeries instance or uses already existing memSeries. 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. I believe it's the logic that it's written, but is there any . more difficult for those people to help. Has 90% of ice around Antarctica disappeared in less than a decade? The main motivation seems to be that dealing with partially scraped metrics is difficult and youre better off treating failed scrapes as incidents. 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. Once configured, your instances should be ready for access. website I've created an expression that is intended to display percent-success for a given metric. In the same blog post we also mention one of the tools we use to help our engineers write valid Prometheus alerting rules. "no data". This means that our memSeries still consumes some memory (mostly labels) but doesnt really do anything. How Intuit democratizes AI development across teams through reusability. This process is also aligned with the wall clock but shifted by one hour. Youll be executing all these queries in the Prometheus expression browser, so lets get started.

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