how have you configured the query which is causing problems? Find centralized, trusted content and collaborate around the technologies you use most. 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. Please help improve it by filing issues or pull requests. To learn more, see our tips on writing great answers. 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. So when TSDB is asked to append a new sample by any scrape, it will first check how many time series are already present. These checks are designed to ensure that we have enough capacity on all Prometheus servers to accommodate extra time series, if that change would result in extra time series being collected. Is a PhD visitor considered as a visiting scholar? As we mentioned before a time series is generated from metrics. In AWS, create two t2.medium instances running CentOS. If we have a scrape with sample_limit set to 200 and the application exposes 201 time series, then all except one final time series will be accepted. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. and can help you on 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. Are you not exposing the fail metric when there hasn't been a failure yet? 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. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. Is that correct? 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. Using regular expressions, you could select time series only for jobs whose The second patch modifies how Prometheus handles sample_limit - with our patch instead of failing the entire scrape it simply ignores excess 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. Combined thats a lot of different metrics. Is there a single-word adjective for "having exceptionally strong moral principles"? Play with bool 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 patchset consists of two main elements. 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. Are there tables of wastage rates for different fruit and veg? Have a question about this project? 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. We protect 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. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 . For example, this expression Next, create a Security Group to allow access to the instances. But I'm stuck now if I want to do something like apply a weight to alerts of a different severity level, e.g. 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. Since the default Prometheus scrape interval is one minute it would take two hours to reach 120 samples. I believe it's the logic that it's written, but is there any . 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. What does remote read means in Prometheus? 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. 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. After running the query, a table will show the current value of each result time series (one table row per output series). For Prometheus to collect this metric we need our application to run an HTTP server and expose our metrics there. That's the query (Counter metric): sum(increase(check_fail{app="monitor"}[20m])) by (reason). 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. This is because the only way to stop time series from eating memory is to prevent them from being appended to TSDB. without any dimensional information. Second rule does the same but only sums time series with status labels equal to "500". (pseudocode): This gives the same single value series, or no data if there are no alerts. 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. The more any application does for you, the more useful it is, the more resources it might need. 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. 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. 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. If we configure a sample_limit of 100 and our metrics response contains 101 samples, then Prometheus wont scrape anything at all. We know that time series will stay in memory for a while, even if they were scraped only once. Lets adjust the example code to do this. 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. count(container_last_seen{environment="prod",name="notification_sender.*",roles=".application-server."}) To learn more, see our tips on writing great answers. Youll be executing all these queries in the Prometheus expression browser, so lets get started. t]. Time series scraped from applications are kept in memory. Making statements based on opinion; back them up with references or personal experience. privacy statement. I've been using comparison operators in Grafana for a long while. 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. 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. How can I group labels in a Prometheus query? This makes a bit more sense with your explanation. an EC2 regions with application servers running docker containers. This is the standard Prometheus flow for a scrape that has the sample_limit option set: The entire scrape either succeeds or fails. The number of time series depends purely on the number of labels and the number of all possible values these labels can take. What happens when somebody wants to export more time series or use longer labels? (fanout by job name) and instance (fanout by instance of the job), we might 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. Looking to learn more? This holds true for a lot of labels that we see are being used by engineers. Even i am facing the same issue Please help me on this. 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. 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. Asking for help, clarification, or responding to other answers. 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. 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. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? Youve learned about the main components of Prometheus, and its query language, PromQL. following for every instance: we could get the top 3 CPU users grouped by application (app) and process an EC2 regions with application servers running docker containers. 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. Its not going to get you a quicker or better answer, and some people might SSH into both servers and run the following commands to install Docker. node_cpu_seconds_total: This returns the total amount of CPU time. Making statements based on opinion; back them up with references or personal experience. Can airtags be tracked from an iMac desktop, with no iPhone? returns the unused memory in MiB for every instance (on a fictional cluster To make things more complicated you may also hear about samples when reading Prometheus documentation. 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. What this means is that using Prometheus defaults each memSeries should have a single chunk with 120 samples on it for every two hours of data. what does the Query Inspector show for the query you have a problem with? So it seems like I'm back to square one. Perhaps I misunderstood, but it looks like any defined metrics that hasn't yet recorded any values can be used in a larger expression. 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. Sign up and get Kubernetes tips delivered straight to your inbox. We can use these to add more information to our metrics so that we can better understand whats going on. website To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Making statements based on opinion; back them up with references or personal experience. I then hide the original query. Find centralized, trusted content and collaborate around the technologies you use most. privacy statement. Thank you for subscribing! Thanks for contributing an answer to Stack Overflow! A sample is something in between metric and time series - its a time series value for a specific timestamp. These queries are a good starting point. 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. Select the query and do + 0. You're probably looking for the absent function. Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. Internet-scale applications efficiently, Thats why what our application exports isnt really metrics or time series - its samples. Finally, please remember that some people read these postings as an email Adding labels is very easy and all we need to do is specify their names. What is the point of Thrower's Bandolier? The only exception are memory-mapped chunks which are offloaded to disk, but will be read into memory if needed by queries. Already on GitHub? If the total number of stored time series is below the configured limit then we append the sample as usual. Samples are compressed using encoding that works best if there are continuous updates. This article covered a lot of ground. This is the last line of defense for us that avoids the risk of the Prometheus server crashing due to lack of memory. To get a better idea of this problem lets adjust our example metric to track HTTP requests. The subquery for the deriv function uses the default resolution. Why is there a voltage on my HDMI and coaxial cables? Not the answer you're looking for? Other Prometheus components include a data model that stores the metrics, client libraries for instrumenting code, and PromQL for querying the metrics. Prometheus does offer some options for dealing with high cardinality problems. 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. Once theyre in TSDB its already too late. rev2023.3.3.43278. 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. 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. 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). to your account, What did you do? Run the following commands on the master node, only copy the kubeconfig and set up Flannel CNI. but viewed in the tabular ("Console") view of the expression browser. I have a data model where some metrics are namespaced by client, environment and deployment name. which Operating System (and version) are you running it under? 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. Another reason is that trying to stay on top of your usage can be a challenging task. Time arrow with "current position" evolving with overlay number. 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. For example, /api/v1/query?query=http_response_ok [24h]&time=t would return raw samples on the time range (t-24h . Have a question about this project? I'd expect to have also: Please use the prometheus-users mailing list for questions. Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, How Intuit democratizes AI development across teams through reusability. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. 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. 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. Using a query that returns "no data points found" in an expression. With this simple code Prometheus client library will create a single metric. Chunks that are a few hours old are written to disk and removed from memory. If so it seems like this will skew the results of the query (e.g., quantiles).
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