Secondly this calculation is based on all memory used by Prometheus, not only time series data, so its just an approximation. 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). I've created an expression that is intended to display percent-success for a given metric. The more labels you have, or the longer the names and values are, the more memory it will use. Not the answer you're looking for? job and handler labels: Return a whole range of time (in this case 5 minutes up to the query time) Once TSDB knows if it has to insert new time series or update existing ones it can start the real work. At this point, both nodes should be ready. If both the nodes are running fine, you shouldnt get any result for this query. Internally all time series are stored inside a map on a structure called Head. He has a Bachelor of Technology in Computer Science & Engineering from SRMS. entire corporate networks, Since the default Prometheus scrape interval is one minute it would take two hours to reach 120 samples. Since labels are copied around when Prometheus is handling queries this could cause significant memory usage increase. 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. 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). Neither of these solutions seem to retain the other dimensional information, they simply produce a scaler 0. from and what youve done will help people to understand your problem. But I'm stuck now if I want to do something like apply a weight to alerts of a different severity level, e.g. Well occasionally send you account related emails. Return all time series with the metric http_requests_total: Return all time series with the metric http_requests_total and the given will get matched and propagated to the output. Or do you have some other label on it, so that the metric still only gets exposed when you record the first failued request it? 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. 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. With our custom patch we dont care how many samples are in a scrape. Windows 10, how have you configured the query which is causing problems? What sort of strategies would a medieval military use against a fantasy giant? There is an open pull request on the Prometheus repository. (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. Once the last chunk for this time series is written into a block and removed from the memSeries instance we have no chunks left. 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 more labels you have and the more values each label can take, the more unique combinations you can create and the higher the cardinality. 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. 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. 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. The region and polygon don't match. Its the chunk responsible for the most recent time range, including the time of our scrape. Of course, this article is not a primer on PromQL; you can browse through the PromQL documentation for more in-depth knowledge. Once it has a memSeries instance to work with it will append our sample to the Head Chunk. 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. 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. That map uses labels hashes as keys and a structure called memSeries as values. 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. 2023 The Linux Foundation. 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. Operating such a large Prometheus deployment doesnt come without challenges. Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, How Intuit democratizes AI development across teams through reusability. Theres only one chunk that we can append to, its called the Head Chunk. Prometheus metrics can have extra dimensions in form of labels. 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. website 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. Prometheus simply counts how many samples are there in a scrape and if thats more than sample_limit allows it will fail the scrape. 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. Stumbled onto this post for something else unrelated, just was +1-ing this :). 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? @zerthimon The following expr works for me 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. If a sample lacks any explicit timestamp then it means that the sample represents the most recent value - its the current value of a given time series, and the timestamp is simply the time you make your observation at. 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. These flags are only exposed for testing and might have a negative impact on other parts of Prometheus server. No error message, it is just not showing the data while using the JSON file from that website. AFAIK it's not possible to hide them through Grafana. 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. 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 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. Already on GitHub? We know what a metric, a sample and a time series is. 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. Monitoring Docker container metrics using cAdvisor, Use file-based service discovery to discover scrape targets, Understanding and using the multi-target exporter pattern, Monitoring Linux host metrics with the Node Exporter. If we configure a sample_limit of 100 and our metrics response contains 101 samples, then Prometheus wont scrape anything at all. You set up a Kubernetes cluster, installed Prometheus on it ,and ran some queries to check the clusters health. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. are going to make it For example, /api/v1/query?query=http_response_ok [24h]&time=t would return raw samples on the time range (t-24h . 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. Time series scraped from applications are kept in memory. Passing sample_limit is the ultimate protection from high cardinality. Instead we count time series as we append them to TSDB. 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. You're probably looking for the absent function. With this simple code Prometheus client library will create a single metric. You saw how PromQL basic expressions can return important metrics, which can be further processed with operators and functions. but viewed in the tabular ("Console") view of the expression browser. 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. The Graph tab allows you to graph a query expression over a specified range of time. 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. Of course there are many types of queries you can write, and other useful queries are freely available. About an argument in Famine, Affluence and Morality. What am I doing wrong here in the PlotLegends specification? 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. Play with bool If your expression returns anything with labels, it won't match the time series generated by vector(0). This process is also aligned with the wall clock but shifted by one hour. which outputs 0 for an empty input vector, but that outputs a scalar 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? What does remote read means in Prometheus? The second patch modifies how Prometheus handles sample_limit - with our patch instead of failing the entire scrape it simply ignores excess time series. 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. You signed in with another tab or window. which Operating System (and version) are you running it under? Is that correct? We will examine their use cases, the reasoning behind them, and some implementation details you should be aware of. metric name, as measured over the last 5 minutes: Assuming that the http_requests_total time series all have the labels job Already on GitHub? what does the Query Inspector show for the query you have a problem with? So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . Is it a bug? Knowing that it can quickly check if there are any time series already stored inside TSDB that have the same hashed value. count(ALERTS) or (1-absent(ALERTS)), Alternatively, count(ALERTS) or vector(0). Im new at Grafan and Prometheus. Finally, please remember that some people read these postings as an email Where does this (supposedly) Gibson quote come from? The number of time series depends purely on the number of labels and the number of all possible values these labels can take. Timestamps here can be explicit or implicit. 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. In order to make this possible, it's necessary to tell Prometheus explicitly to not trying to match any labels by . Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. The below posts may be helpful for you to learn more about Kubernetes and our company. positions. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. 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. Using a query that returns "no data points found" in an expression. The actual amount of physical memory needed by Prometheus will usually be higher as a result, since it will include unused (garbage) memory that needs to be freed by Go runtime. privacy statement. 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. rev2023.3.3.43278. 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. About an argument in Famine, Affluence and Morality. Has 90% of ice around Antarctica disappeared in less than a decade? This thread has been automatically locked since there has not been any recent activity after it was closed. 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. It will record the time it sends HTTP requests and use that later as the timestamp for all collected time series. result of a count() on a query that returns nothing should be 0 ? Subscribe to receive notifications of new posts: Subscription confirmed. Perhaps I misunderstood, but it looks like any defined metrics that hasn't yet recorded any values can be used in a larger expression. A metric is an observable property with some defined dimensions (labels). The more labels we have or the more distinct values they can have the more time series as a result. Connect and share knowledge within a single location that is structured and easy to search. 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. 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. If the total number of stored time series is below the configured limit then we append the sample as usual. The way labels are stored internally by Prometheus also matters, but thats something the user has no control over. Cardinality is the number of unique combinations of all labels. Also, providing a reasonable amount of information about where youre starting
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