prometheus query return 0 if no datashoprider mobility scooter second hand

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. 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. I've added a data source (prometheus) in Grafana. Once theyre in TSDB its already too late. Any excess samples (after reaching sample_limit) will only be appended if they belong to time series that are already stored inside TSDB. To set up Prometheus to monitor app metrics: Download and install Prometheus. 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. At the same time our patch gives us graceful degradation by capping time series from each scrape to a certain level, rather than failing hard and dropping all time series from affected scrape, which would mean losing all observability of affected applications. You can use these queries in the expression browser, Prometheus HTTP API, or visualization tools like Grafana. You must define your metrics in your application, with names and labels that will allow you to work with resulting time series easily. windows. 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. It saves these metrics as time-series data, which is used to create visualizations and alerts for IT teams. Both rules will produce new metrics named after the value of the record field. 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. Run the following commands in both nodes to configure the Kubernetes repository. 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. Already on GitHub? 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 such a stack trace ended up as a label value it would take a lot more memory than other time series, potentially even megabytes. So I still can't use that metric in calculations ( e.g., success / (success + fail) ) as those calculations will return no datapoints. Its the chunk responsible for the most recent time range, including the time of our scrape. Arithmetic binary operators The following binary arithmetic operators exist in Prometheus: + (addition) - (subtraction) * (multiplication) / (division) % (modulo) ^ (power/exponentiation) 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. count(container_last_seen{name="container_that_doesn't_exist"}), What did you see instead? The more labels you have, or the longer the names and values are, the more memory it will use. Of course, this article is not a primer on PromQL; you can browse through the PromQL documentation for more in-depth knowledge. Its not difficult to accidentally cause cardinality problems and in the past weve dealt with a fair number of issues relating to it. 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. We know that the more labels on a metric, the more time series it can create. 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. All they have to do is set it explicitly in their scrape configuration. The more any application does for you, the more useful it is, the more resources it might need. Today, let's look a bit closer at the two ways of selecting data in PromQL: instant vector selectors and range vector selectors. Stumbled onto this post for something else unrelated, just was +1-ing this :). To get a better idea of this problem lets adjust our example metric to track HTTP requests. The most basic layer of protection that we deploy are scrape limits, which we enforce on all configured scrapes. returns the unused memory in MiB for every instance (on a fictional cluster Better to simply ask under the single best category you think fits and see We know what a metric, a sample and a time series is. 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. I then hide the original query. This is a deliberate design decision made by Prometheus developers. Now we should pause to make an important distinction between metrics and time series. Once TSDB knows if it has to insert new time series or update existing ones it can start the real work. The below posts may be helpful for you to learn more about Kubernetes and our company. @zerthimon The following expr works for me following for every instance: we could get the top 3 CPU users grouped by application (app) and process Asking for help, clarification, or responding to other answers. metric name, as measured over the last 5 minutes: Assuming that the http_requests_total time series all have the labels job our free app that makes your Internet faster and safer. Is it possible to create a concave light? Instead we count time series as we append them to TSDB. Adding labels is very easy and all we need to do is specify their names. - I am using this in windows 10 for testing, which Operating System (and version) are you running it under? Yeah, absent() is probably the way to go. Has 90% of ice around Antarctica disappeared in less than a decade? Our metrics are exposed as a HTTP response. It enables us to enforce a hard limit on the number of time series we can scrape from each application instance. This is because once we have more than 120 samples on a chunk efficiency of varbit encoding drops. gabrigrec September 8, 2021, 8:12am #8. What sort of strategies would a medieval military use against a fantasy giant? Those memSeries objects are storing all the time series information. 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. We have hundreds of data centers spread across the world, each with dedicated Prometheus servers responsible for scraping all metrics. Asking for help, clarification, or responding to other answers. 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. Just add offset to the query. without any dimensional information. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. Samples are compressed using encoding that works best if there are continuous updates. This process is also aligned with the wall clock but shifted by one hour. Once configured, your instances should be ready for access. Well be executing kubectl commands on the master node only. help customers build whether someone is able to help out. for the same vector, making it a range vector: Note that an expression resulting in a range vector cannot be graphed directly, 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. In the same blog post we also mention one of the tools we use to help our engineers write valid Prometheus alerting rules. Theres no timestamp anywhere actually. Internet-scale applications efficiently, He has a Bachelor of Technology in Computer Science & Engineering from SRMS. The result of an expression can either be shown as a graph, viewed as tabular data in Prometheus's expression browser, or consumed by external systems via the HTTP API. How do you get out of a corner when plotting yourself into a corner, Partner is not responding when their writing is needed in European project application. 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. About an argument in Famine, Affluence and Morality. 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. I used a Grafana transformation which seems to work. That map uses labels hashes as keys and a structure called memSeries as values. 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. To get a better understanding of the impact of a short lived time series on memory usage lets take a look at another example. Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. In AWS, create two t2.medium instances running CentOS. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? 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. 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. If the total number of stored time series is below the configured limit then we append the sample as usual. This is because the only way to stop time series from eating memory is to prevent them from being appended to TSDB. You set up a Kubernetes cluster, installed Prometheus on it ,and ran some queries to check the clusters health. If all the label values are controlled by your application you will be able to count the number of all possible label combinations. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. I cant see how absent() may help me here @juliusv yeah, I tried count_scalar() but I can't use aggregation with it. We will examine their use cases, the reasoning behind them, and some implementation details you should be aware of. Prometheus lets you query data in two different modes: The Console tab allows you to evaluate a query expression at the current time. *) in region drops below 4. The text was updated successfully, but these errors were encountered: This is correct. rev2023.3.3.43278. 1 Like. rate (http_requests_total [5m]) [30m:1m] 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. After sending a request it will parse the response looking for all the samples exposed there. To select all HTTP status codes except 4xx ones, you could run: Return the 5-minute rate of the http_requests_total metric for the past 30 minutes, with a resolution of 1 minute. Hello, I'm new at Grafan and Prometheus. We know that time series will stay in memory for a while, even if they were scraped only once. 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. will get matched and propagated to the output. new career direction, check out our open Now comes the fun stuff. the problem you have. Time series scraped from applications are kept in memory. By clicking Sign up for GitHub, you agree to our terms of service and 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. 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. These queries are a good starting point. We use Prometheus to gain insight into all the different pieces of hardware and software that make up our global network. At this point, both nodes should be ready. Not the answer you're looking for? t]. Being able to answer How do I X? yourself without having to wait for a subject matter expert allows everyone to be more productive and move faster, while also avoiding Prometheus experts from answering the same questions over and over again. 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. Its very easy to keep accumulating time series in Prometheus until you run out of memory. 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 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. 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. For example, I'm using the metric to record durations for quantile reporting. Our HTTP response will now show more entries: As we can see we have an entry for each unique combination of labels. 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. or Internet application, 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 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. 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. prometheus-promql query based on label value, Select largest label value in Prometheus query, Prometheus Query Overall average under a time interval, Prometheus endpoint of all available metrics. Good to know, thanks for the quick response! Next, create a Security Group to allow access to the instances. instance_memory_usage_bytes: This shows the current memory used. count the number of running instances per application like this: This documentation is open-source. Prometheus query check if value exist. Ive deliberately kept the setup simple and accessible from any address for demonstration. Before that, Vinayak worked as a Senior Systems Engineer at Singapore Airlines. The simplest construct of a PromQL query is an instant vector selector. Neither of these solutions seem to retain the other dimensional information, they simply produce a scaler 0. Passing sample_limit is the ultimate protection from high cardinality. It will record the time it sends HTTP requests and use that later as the timestamp for all collected time series. 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! 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. That way even the most inexperienced engineers can start exporting metrics without constantly wondering Will this cause an incident?. 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. privacy statement. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. First rule will tell Prometheus to calculate per second rate of all requests and sum it across all instances of our server. rev2023.3.3.43278. We can add more metrics if we like and they will all appear in the HTTP response to the metrics endpoint. or Internet application, ward off DDoS One Head Chunk - containing up to two hours of the last two hour wall clock slot. Other Prometheus components include a data model that stores the metrics, client libraries for instrumenting code, and PromQL for querying the metrics. The only exception are memory-mapped chunks which are offloaded to disk, but will be read into memory if needed by queries. Have a question about this project? ward off DDoS Since labels are copied around when Prometheus is handling queries this could cause significant memory usage increase. This might require Prometheus to create a new chunk if needed. 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. A metric can be anything that you can express as a number, for example: To create metrics inside our application we can use one of many Prometheus client libraries. Prometheus is an open-source monitoring and alerting software that can collect metrics from different infrastructure and applications. 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. Prometheus's query language supports basic logical and arithmetic operators. Operating such a large Prometheus deployment doesnt come without challenges. Even i am facing the same issue Please help me on this. This would inflate Prometheus memory usage, which can cause Prometheus server to crash, if it uses all available physical memory. Using regular expressions, you could select time series only for jobs whose privacy statement. your journey to Zero Trust. 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. 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. And then there is Grafana, which comes with a lot of built-in dashboards for Kubernetes monitoring. This is one argument for not overusing labels, but often it cannot be avoided. Each time series will cost us resources since it needs to be kept in memory, so the more time series we have, the more resources metrics will consume. 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. 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. 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. There will be traps and room for mistakes at all stages of this process. 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. Once we do that we need to pass label values (in the same order as label names were specified) when incrementing our counter to pass this extra information. But you cant keep everything in memory forever, even with memory-mapping parts of data. Use it to get a rough idea of how much memory is used per time series and dont assume its that exact number. Why is this sentence from The Great Gatsby grammatical? Return the per-second rate for all time series with the http_requests_total By clicking Post Your Answer, you agree to our terms of service, privacy policy and cookie policy. How Intuit democratizes AI development across teams through reusability. Please help improve it by filing issues or pull requests. For operations between two instant vectors, the matching behavior can be modified. Returns a list of label names. I've created an expression that is intended to display percent-success for a given metric. 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? count(container_last_seen{environment="prod",name="notification_sender.*",roles=".application-server."}) Internally time series names are just another label called __name__, so there is no practical distinction between name and labels. ***> wrote: You signed in with another tab or window. 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. 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 it seems like I'm back to square one. A sample is something in between metric and time series - its a time series value for a specific timestamp. 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.

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