If you're looking for a 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. The way labels are stored internally by Prometheus also matters, but thats something the user has no control over. Name the nodes as Kubernetes Master and Kubernetes Worker. Has 90% of ice around Antarctica disappeared in less than a decade? To set up Prometheus to monitor app metrics: Download and install Prometheus. If instead of beverages we tracked the number of HTTP requests to a web server, and we used the request path as one of the label values, then anyone making a huge number of random requests could force our application to create a huge number of time series. It will record the time it sends HTTP requests and use that later as the timestamp for all collected time series. I've been using comparison operators in Grafana for a long while. binary operators to them and elements on both sides with the same label set 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. 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. Since we know that the more labels we have the more time series we end up with, you can see when this can become a problem. After running the query, a table will show the current value of each result time series (one table row per output series). Better to simply ask under the single best category you think fits and see However, the queries you will see here are a baseline" audit. 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 we add another label that can also have two values then we can now export up to eight time series (2*2*2). Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Once it has a memSeries instance to work with it will append our sample to the Head Chunk. 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. 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. 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. I.e., there's no way to coerce no datapoints to 0 (zero)? Chunks that are a few hours old are written to disk and removed from memory. This works fine when there are data points for all queries in the expression. One of the most important layers of protection is a set of patches we maintain on top of Prometheus. There is a maximum of 120 samples each chunk can hold. See this article for details. To make things more complicated you may also hear about samples when reading Prometheus documentation. I've added a data source (prometheus) in Grafana. @zerthimon You might want to use 'bool' with your comparator list, which does not convey images, so screenshots etc. notification_sender-. Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2. I'm still out of ideas here. If you do that, the line will eventually be redrawn, many times over. 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. Lets adjust the example code to do this. 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. Each chunk represents a series of samples for a specific time range. 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. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Lets create a demo Kubernetes cluster and set up Prometheus to monitor it. (fanout by job name) and instance (fanout by instance of the job), we might 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. (pseudocode): This gives the same single value series, or no data if there are no alerts. 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. Connect and share knowledge within a single location that is structured and easy to search. Adding labels is very easy and all we need to do is specify their names. 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. So there would be a chunk for: 00:00 - 01:59, 02:00 - 03:59, 04:00 - 05:59, , 22:00 - 23:59. For Prometheus to collect this metric we need our application to run an HTTP server and expose our metrics there. For a list of trademarks of The Linux Foundation, please see our Trademark Usage page. The downside of all these limits is that breaching any of them will cause an error for the entire scrape. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? Internally time series names are just another label called __name__, so there is no practical distinction between name and labels. This is one argument for not overusing labels, but often it cannot be avoided. Have a question about this project? This process is also aligned with the wall clock but shifted by one hour. And then there is Grafana, which comes with a lot of built-in dashboards for Kubernetes monitoring. The Head Chunk is never memory-mapped, its always stored in memory. count the number of running instances per application like this: This documentation is open-source. Having good internal documentation that covers all of the basics specific for our environment and most common tasks is very important. Timestamps here can be explicit or implicit. 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. First is the patch that allows us to enforce a limit on the total number of time series TSDB can store at any time. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. The idea is that if done as @brian-brazil mentioned, there would always be a fail and success metric, because they are not distinguished by a label, but always are exposed. 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. 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. 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. 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? Prometheus Queries: 11 PromQL Examples and Tutorial - ContainIQ This gives us confidence that we wont overload any Prometheus server after applying changes. 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. 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? It saves these metrics as time-series data, which is used to create visualizations and alerts for IT teams. Going back to our time series - at this point Prometheus either creates a new memSeries instance or uses already existing memSeries. Theres no timestamp anywhere actually. Those memSeries objects are storing all the time series information. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. and can help you on 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. The Linux Foundation has registered trademarks and uses trademarks. Return the per-second rate for all time series with the http_requests_total 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. Returns a list of label names. Separate metrics for total and failure will work as expected. 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. Ive deliberately kept the setup simple and accessible from any address for demonstration. Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. Now comes the fun stuff. which version of Grafana are you using? What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? Good to know, thanks for the quick response! Perhaps I misunderstood, but it looks like any defined metrics that hasn't yet recorded any values can be used in a larger expression. Selecting data from Prometheus's TSDB forms the basis of almost any useful PromQL query before . 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). You can verify this by running the kubectl get nodes command on the master node. But the key to tackling high cardinality was better understanding how Prometheus works and what kind of usage patterns will be problematic. Although, sometimes the values for project_id doesn't exist, but still end up showing up as one. Having better insight into Prometheus internals allows us to maintain a fast and reliable observability platform without too much red tape, and the tooling weve developed around it, some of which is open sourced, helps our engineers avoid most common pitfalls and deploy with confidence. @juliusv Thanks for clarifying that. 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. Operating such a large Prometheus deployment doesnt come without challenges. Is it plausible for constructed languages to be used to affect thought and control or mold people towards desired outcomes? There's also count_scalar(), 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. Variable of the type Query allows you to query Prometheus for a list of metrics, labels, or label values. I'm displaying Prometheus query on a Grafana table. 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 simplest way of doing this is by using functionality provided with client_python itself - see documentation here. Prometheus Authors 2014-2023 | Documentation Distributed under CC-BY-4.0. There is a single time series for each unique combination of metrics labels. In the screenshot below, you can see that I added two queries, A and B, but only . If the time series already exists inside TSDB then we allow the append to continue. Knowing that it can quickly check if there are any time series already stored inside TSDB that have the same hashed value. 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. To avoid this its in general best to never accept label values from untrusted sources. Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, Simple succinct answer. In AWS, create two t2.medium instances running CentOS. In our example we have two labels, content and temperature, and both of them can have two different values. Prometheus - exclude 0 values from query result - Stack Overflow 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. Cadvisors on every server provide container names. Basically our labels hash is used as a primary key inside TSDB. I'm not sure what you mean by exposing a metric. 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. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. About an argument in Famine, Affluence and Morality. The more any application does for you, the more useful it is, the more resources it might need. Return all time series with the metric http_requests_total: Return all time series with the metric http_requests_total and the given scheduler exposing these metrics about the instances it runs): The same expression, but summed by application, could be written like this: If the same fictional cluster scheduler exposed CPU usage metrics like the Prometheus - exclude 0 values from query result, How Intuit democratizes AI development across teams through reusability. Are there tables of wastage rates for different fruit and veg? 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. If the error message youre getting (in a log file or on screen) can be quoted (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. The text was updated successfully, but these errors were encountered: It's recommended not to expose data in this way, partially for this reason. Since labels are copied around when Prometheus is handling queries this could cause significant memory usage increase. This page will guide you through how to install and connect Prometheus and Grafana. Instead we count time series as we append them to TSDB. Yeah, absent() is probably the way to go. 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. This garbage collection, among other things, will look for any time series without a single chunk and remove it from memory. How to tell which packages are held back due to phased updates. See these docs for details on how Prometheus calculates the returned results. Arithmetic binary operators The following binary arithmetic operators exist in Prometheus: + (addition) - (subtraction) * (multiplication) / (division) % (modulo) ^ (power/exponentiation) Redoing the align environment with a specific formatting. When Prometheus collects metrics it records the time it started each collection and then it will use it to write timestamp & value pairs for each time series. Play with bool So I still can't use that metric in calculations ( e.g., success / (success + fail) ) as those calculations will return no datapoints. The advantage of doing this is that memory-mapped chunks dont use memory unless TSDB needs to read them. In general, having more labels on your metrics allows you to gain more insight, and so the more complicated the application you're trying to monitor, the more need for extra labels. 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. rev2023.3.3.43278. Managed Service for Prometheus Cloud Monitoring Prometheus # ! 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. The simplest construct of a PromQL query is an instant vector selector. But you cant keep everything in memory forever, even with memory-mapping parts of data. I'm displaying Prometheus query on a Grafana table. In both nodes, edit the /etc/hosts file to add the private IP of the nodes. Here are two examples of instant vectors: You can also use range vectors to select a particular time range. PromQL allows you to write queries and fetch information from the metric data collected by Prometheus. PROMQL: how to add values when there is no data returned? By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. 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. What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? This pod wont be able to run because we dont have a node that has the label disktype: ssd. Already on GitHub? Ive added a data source(prometheus) in Grafana. We covered some of the most basic pitfalls in our previous blog post on Prometheus - Monitoring our monitoring. whether someone is able to help out. Can airtags be tracked from an iMac desktop, with no iPhone? This article covered a lot of ground. entire corporate networks, Also the link to the mailing list doesn't work for me. Next, create a Security Group to allow access to the instances. A sample is something in between metric and time series - its a time series value for a specific timestamp. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. prometheus - Promql: Is it possible to get total count in Query_Range Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, How Intuit democratizes AI development across teams through reusability. Use Prometheus to monitor app performance metrics. We will also signal back to the scrape logic that some samples were skipped. ***> wrote: You signed in with another tab or window. count() should result in 0 if no timeseries found #4982 - GitHub returns the unused memory in MiB for every instance (on a fictional cluster Well be executing kubectl commands on the master node only. Theres only one chunk that we can append to, its called the Head Chunk. Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. 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 . There is no equivalent functionality in a standard build of Prometheus, if any scrape produces some samples they will be appended to time series inside TSDB, creating new time series if needed. Once theyre in TSDB its already too late. https://github.com/notifications/unsubscribe-auth/AAg1mPXncyVis81Rx1mIWiXRDe0E1Dpcks5rIXe6gaJpZM4LOTeb. Each Prometheus is scraping a few hundred different applications, each running on a few hundred servers. which outputs 0 for an empty input vector, but that outputs a scalar Can airtags be tracked from an iMac desktop, with no iPhone? Asking for help, clarification, or responding to other answers. 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. If we configure a sample_limit of 100 and our metrics response contains 101 samples, then Prometheus wont scrape anything at all.
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