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. AFAIK it's not possible to hide them through Grafana. Those limits are there to catch accidents and also to make sure that if any application is exporting a high number of time series (more than 200) the team responsible for it knows about it. 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. With 1,000 random requests we would end up with 1,000 time series in Prometheus. By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. A common pattern is to export software versions as a build_info metric, Prometheus itself does this too: When Prometheus 2.43.0 is released this metric would be exported as: Which means that a time series with version=2.42.0 label would no longer receive any new samples. For example, I'm using the metric to record durations for quantile reporting. Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2, Prometheus promQL query is not showing 0 when metric data does not exists, PromQL - how to get an interval between result values, PromQL delta for each elment in values array, Trigger alerts according to the environment in alertmanger, Prometheus alertmanager includes resolved alerts in a new alert. This process helps to reduce disk usage since each block has an index taking a good chunk of disk space. 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. Our HTTP response will now show more entries: As we can see we have an entry for each unique combination of labels. To this end, I set up the query to instant so that the very last data point is returned but, when the query does not return a value - say because the server is down and/or no scraping took place - the stat panel produces no data. Well occasionally send you account related emails. Is it suspicious or odd to stand by the gate of a GA airport watching the planes? To your second question regarding whether I have some other label on it, the answer is yes I do. source, what your query is, what the query inspector shows, and any other By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. rate (http_requests_total [5m]) [30m:1m] The number of time series depends purely on the number of labels and the number of all possible values these labels can take. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Hmmm, upon further reflection, I'm wondering if this will throw the metrics off. 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. Cadvisors on every server provide container names. 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. @rich-youngkin Yes, the general problem is non-existent series. In order to make this possible, it's necessary to tell Prometheus explicitly to not trying to match any labels by . Having good internal documentation that covers all of the basics specific for our environment and most common tasks is very important. Often it doesnt require any malicious actor to cause cardinality related problems. It saves these metrics as time-series data, which is used to create visualizations and alerts for IT teams. Returns a list of label values for the label in every metric. will get matched and propagated to the output. Prometheus - exclude 0 values from query result, How Intuit democratizes AI development across teams through reusability. Of course there are many types of queries you can write, and other useful queries are freely available. The advantage of doing this is that memory-mapped chunks dont use memory unless TSDB needs to read them. I suggest you experiment more with the queries as you learn, and build a library of queries you can use for future projects. or something like that. Not the answer you're looking for? Making statements based on opinion; back them up with references or personal experience. Neither of these solutions seem to retain the other dimensional information, they simply produce a scaler 0. rev2023.3.3.43278. Has 90% of ice around Antarctica disappeared in less than a decade? For Prometheus to collect this metric we need our application to run an HTTP server and expose our metrics there. Selecting data from Prometheus's TSDB forms the basis of almost any useful PromQL query before . 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. After a chunk was written into a block and removed from memSeries we might end up with an instance of memSeries that has no chunks. to get notified when one of them is not mounted anymore. Now comes the fun stuff. How to follow the signal when reading the schematic? SSH into both servers and run the following commands to install Docker. Run the following commands in both nodes to install kubelet, kubeadm, and kubectl. How to filter prometheus query by label value using greater-than, PromQL - Prometheus - query value as label, Why time duration needs double dot for Prometheus but not for Victoria metrics, How do you get out of a corner when plotting yourself into a corner. 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. You signed in with another tab or window. Now we should pause to make an important distinction between metrics and time series. Having a working monitoring setup is a critical part of the work we do for our clients. vishnur5217 May 31, 2020, 3:44am 1. This patchset consists of two main elements. I'm not sure what you mean by exposing a metric. Prometheus - exclude 0 values from query result - Stack Overflow 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. I have just used the JSON file that is available in below website The result is a table of failure reason and its count. How to show that an expression of a finite type must be one of the finitely many possible values? it works perfectly if one is missing as count() then returns 1 and the rule fires. Of course, this article is not a primer on PromQL; you can browse through the PromQL documentation for more in-depth knowledge. 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. notification_sender-. Using a query that returns "no data points found" in an - GitHub There is an open pull request on the Prometheus repository. Redoing the align environment with a specific formatting. Setting label_limit provides some cardinality protection, but even with just one label name and huge number of values we can see high cardinality. or Internet application, @juliusv Thanks for clarifying that. How To Query Prometheus on Ubuntu 14.04 Part 1 - DigitalOcean Once you cross the 200 time series mark, you should start thinking about your metrics more. positions. The number of times some specific event occurred. Those memSeries objects are storing all the time series information. And this brings us to the definition of cardinality in the context of metrics. Prometheus does offer some options for dealing with high cardinality problems. The most basic layer of protection that we deploy are scrape limits, which we enforce on all configured scrapes. Can airtags be tracked from an iMac desktop, with no iPhone? Timestamps here can be explicit or implicit. Better to simply ask under the single best category you think fits and see Once it has a memSeries instance to work with it will append our sample to the Head Chunk. See these docs for details on how Prometheus calculates the returned results. 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. If your expression returns anything with labels, it won't match the time series generated by vector(0). Every time we add a new label to our metric we risk multiplying the number of time series that will be exported to Prometheus as the result. 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. Although you can tweak some of Prometheus' behavior and tweak it more for use with short lived time series, by passing one of the hidden flags, its generally discouraged to do so. Have a question about this project? If so it seems like this will skew the results of the query (e.g., quantiles). I believe it's the logic that it's written, but is there any . Connect and share knowledge within a single location that is structured and easy to search. 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. what does the Query Inspector show for the query you have a problem with? but viewed in the tabular ("Console") view of the expression browser. The downside of all these limits is that breaching any of them will cause an error for the entire scrape. If this query also returns a positive value, then our cluster has overcommitted the memory. 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. Already on GitHub? feel that its pushy or irritating and therefore ignore it. Combined thats a lot of different metrics. The Graph tab allows you to graph a query expression over a specified range of time. what error message are you getting to show that theres a problem? 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. About an argument in Famine, Affluence and Morality. 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). 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. prometheus - Promql: Is it possible to get total count in Query_Range 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? You saw how PromQL basic expressions can return important metrics, which can be further processed with operators and functions. As we mentioned before a time series is generated from metrics. Add field from calculation Binary operation. Please help improve it by filing issues or pull requests. 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 Comparing current data with historical data. prometheus promql Share Follow edited Nov 12, 2020 at 12:27 Asking for help, clarification, or responding to other answers. The more labels we have or the more distinct values they can have the more time series as a result. 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. 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. Im new at Grafan and Prometheus. 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. 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. Staging Ground Beta 1 Recap, and Reviewers needed for Beta 2. At the moment of writing this post we run 916 Prometheus instances with a total of around 4.9 billion time series. 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. I've created an expression that is intended to display percent-success for a given metric. Prometheus will keep each block on disk for the configured retention period. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. That's the query (Counter metric): sum(increase(check_fail{app="monitor"}[20m])) by (reason). How is Jesus " " (Luke 1:32 NAS28) different from a prophet (, Luke 1:76 NAS28)? Finally we do, by default, set sample_limit to 200 - so each application can export up to 200 time series without any action. Is it possible to rotate a window 90 degrees if it has the same length and width? 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. Chunks that are a few hours old are written to disk and removed from memory. The real power of Prometheus comes into the picture when you utilize the alert manager to send notifications when a certain metric breaches a threshold. 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. Each Prometheus is scraping a few hundred different applications, each running on a few hundred servers. 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 . If you do that, the line will eventually be redrawn, many times over. We will examine their use cases, the reasoning behind them, and some implementation details you should be aware of. Examples 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. These flags are only exposed for testing and might have a negative impact on other parts of Prometheus server. How can I group labels in a Prometheus query? In our example case its a Counter class object. A metric is an observable property with some defined dimensions (labels). In both nodes, edit the /etc/hosts file to add the private IP of the nodes. 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. 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. 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. The way labels are stored internally by Prometheus also matters, but thats something the user has no control over. 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. privacy statement. This works fine when there are data points for all queries in the expression. @zerthimon You might want to use 'bool' with your comparator However when one of the expressions returns no data points found the result of the entire expression is no data points found.In my case there haven't been any failures so rio_dashorigin_serve_manifest_duration_millis_count{Success="Failed"} returns no data points found.Is there a way to write the query so that a . returns the unused memory in MiB for every instance (on a fictional cluster Knowing that it can quickly check if there are any time series already stored inside TSDB that have the same hashed value. Lets pick client_python for simplicity, but the same concepts will apply regardless of the language you use. Internally all time series are stored inside a map on a structure called Head. want to sum over the rate of all instances, so we get fewer output time series, 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. Next you will likely need to create recording and/or alerting rules to make use of your time series. These will give you an overall idea about a clusters health. But the key to tackling high cardinality was better understanding how Prometheus works and what kind of usage patterns will be problematic. Can airtags be tracked from an iMac desktop, with no iPhone? Once configured, your instances should be ready for access. 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. Especially when dealing with big applications maintained in part by multiple different teams, each exporting some metrics from their part of the stack. What is the point of Thrower's Bandolier? In both nodes, edit the /etc/sysctl.d/k8s.conf file to add the following two lines: Then reload the IPTables config using the
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