Asking for help, clarification, or responding to other answers. to differentiate GET from LIST. the target request duration) as the upper bound. Note that an empty array is still returned for targets that are filtered out. The first one is apiserver_request_duration_seconds_bucket, and if we search Kubernetes documentation, we will find that apiserver is a component of . Exporting metrics as HTTP endpoint makes the whole dev/test lifecycle easy, as it is really trivial to check whether your newly added metric is now exposed. Content-Type: application/x-www-form-urlencoded header. Check out https://gumgum.com/engineering, Organizing teams to deliver microservices architecture, Most common design issues found during Production Readiness and Post-Incident Reviews, helm upgrade -i prometheus prometheus-community/kube-prometheus-stack -n prometheus version 33.2.0, kubectl port-forward service/prometheus-grafana 8080:80 -n prometheus, helm upgrade -i prometheus prometheus-community/kube-prometheus-stack -n prometheus version 33.2.0 values prometheus.yaml, https://prometheus-community.github.io/helm-charts. I even computed the 50th percentile using cumulative frequency table(what I thought prometheus is doing) and still ended up with2. 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, 0: open left (left boundary is exclusive, right boundary in inclusive), 1: open right (left boundary is inclusive, right boundary in exclusive), 2: open both (both boundaries are exclusive), 3: closed both (both boundaries are inclusive). Also we could calculate percentiles from it. A Summary is like a histogram_quantile()function, but percentiles are computed in the client. How would I go about explaining the science of a world where everything is made of fabrics and craft supplies? Now the request duration has its sharp spike at 320ms and almost all observations will fall into the bucket from 300ms to 450ms. Hi, Stopping electric arcs between layers in PCB - big PCB burn. percentile happens to be exactly at our SLO of 300ms. replacing the ingestion via scraping and turning Prometheus into a push-based You can also run the check by configuring the endpoints directly in the kube_apiserver_metrics.d/conf.yaml file, in the conf.d/ folder at the root of your Agents configuration directory. dimension of . Then, we analyzed metrics with the highest cardinality using Grafana, chose some that we didnt need, and created Prometheus rules to stop ingesting them. Thirst thing to note is that when using Histogram we dont need to have a separate counter to count total HTTP requests, as it creates one for us. The state query parameter allows the caller to filter by active or dropped targets, Can I change which outlet on a circuit has the GFCI reset switch? distributed under the License is distributed on an "AS IS" BASIS. Prometheus Authors 2014-2023 | Documentation Distributed under CC-BY-4.0. might still change. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. If you are not using RBACs, set bearer_token_auth to false. In our example, we are not collecting metrics from our applications; these metrics are only for the Kubernetes control plane and nodes. Let us now modify the experiment once more. In my case, Ill be using Amazon Elastic Kubernetes Service (EKS). Microsoft recently announced 'Azure Monitor managed service for Prometheus'. "Response latency distribution (not counting webhook duration) in seconds for each verb, group, version, resource, subresource, scope and component.". observations. Prometheus integration provides a mechanism for ingesting Prometheus metrics. quantiles from the buckets of a histogram happens on the server side using the Hopefully by now you and I know a bit more about Histograms, Summaries and tracking request duration. Apiserver latency metrics create enormous amount of time-series, https://www.robustperception.io/why-are-prometheus-histograms-cumulative, https://prometheus.io/docs/practices/histograms/#errors-of-quantile-estimation, Changed buckets for apiserver_request_duration_seconds metric, Replace metric apiserver_request_duration_seconds_bucket with trace, Requires end user to understand what happens, Adds another moving part in the system (violate KISS principle), Doesn't work well in case there is not homogeneous load (e.g. Although, there are a couple of problems with this approach. Find more details here. 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. requestInfo may be nil if the caller is not in the normal request flow. // RecordDroppedRequest records that the request was rejected via http.TooManyRequests. Latency example Here's an example of a Latency PromQL query for the 95% best performing HTTP requests in Prometheus: histogram_quantile ( 0.95, sum ( rate (prometheus_http_request_duration_seconds_bucket [5m])) by (le)) // MonitorRequest handles standard transformations for client and the reported verb and then invokes Monitor to record. It has a cool concept of labels, a functional query language &a bunch of very useful functions like rate(), increase() & histogram_quantile(). The calculated Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, Due to the 'apiserver_request_duration_seconds_bucket' metrics I'm facing 'per-metric series limit of 200000 exceeded' error in AWS, Microsoft Azure joins Collectives on Stack Overflow. SLO, but in reality, the 95th percentile is a tiny bit above 220ms, kubernetes-apps KubePodCrashLooping up or process_start_time_seconds{job="prometheus"}: The following endpoint returns a list of label names: The data section of the JSON response is a list of string label names. How can I get all the transaction from a nft collection? I can skip this metrics from being scraped but I need this metrics. Configuration The main use case to run the kube_apiserver_metrics check is as a Cluster Level Check. I don't understand this - how do they grow with cluster size? calculate streaming -quantiles on the client side and expose them directly, Proposal Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Learn more about bidirectional Unicode characters. For this, we will use the Grafana instance that gets installed with kube-prometheus-stack. How to save a selection of features, temporary in QGIS? The 95th percentile is calculated to be 442.5ms, although the correct value is close to 320ms. So the example in my post is correct. How can we do that? Help; Classic UI; . type=alert) or the recording rules (e.g. pretty good,so how can i konw the duration of the request? of the quantile is to our SLO (or in other words, the value we are summary rarely makes sense. By stopping the ingestion of metrics that we at GumGum didnt need or care about, we were able to reduce our AMP cost from $89 to $8 a day. (the latter with inverted sign), and combine the results later with suitable Whole thing, from when it starts the HTTP handler to when it returns a response. Regardless, 5-10s for a small cluster like mine seems outrageously expensive. mark, e.g. The metric etcd_request_duration_seconds_bucket in 4.7 has 25k series on an empty cluster. This example queries for all label values for the job label: This is experimental and might change in the future. sum(rate( In Part 3, I dug deeply into all the container resource metrics that are exposed by the kubelet.In this article, I will cover the metrics that are exposed by the Kubernetes API server. instead the 95th percentile, i.e. ", "Counter of apiserver self-requests broken out for each verb, API resource and subresource. another bucket with the tolerated request duration (usually 4 times . depending on the resultType. Vanishing of a product of cyclotomic polynomials in characteristic 2. One thing I struggled on is how to track request duration. Kubernetes prometheus metrics for running pods and nodes? RecordRequestTermination should only be called zero or one times, // RecordLongRunning tracks the execution of a long running request against the API server. Thanks for contributing an answer to Stack Overflow! Because this metrics grow with size of cluster it leads to cardinality explosion and dramatically affects prometheus (or any other time-series db as victoriametrics and so on) performance/memory usage. The corresponding Now the request Not all requests are tracked this way. The following example returns metadata only for the metric http_requests_total. The mistake here is that Prometheus scrapes /metrics dataonly once in a while (by default every 1 min), which is configured by scrap_interval for your target. endpoint is /api/v1/write. Examples for -quantiles: The 0.5-quantile is Then create a namespace, and install the chart. In scope of #73638 and kubernetes-sigs/controller-runtime#1273 amount of buckets for this histogram was increased to 40(!) The first one is apiserver_request_duration_seconds_bucket, and if we search Kubernetes documentation, we will find that apiserver is a component of the Kubernetes control-plane that exposes the Kubernetes API. Kube_apiserver_metrics does not include any events. privacy statement. Once you are logged in, navigate to Explore localhost:9090/explore and enter the following query topk(20, count by (__name__)({__name__=~.+})), select Instant, and query the last 5 minutes. verb must be uppercase to be backwards compatible with existing monitoring tooling. If your service runs replicated with a number of We reduced the amount of time-series in #106306 timeouts, maxinflight throttling, // proxyHandler errors). Hi how to run a query resolution of 15 seconds. *N among the N observations. Still, it can get expensive quickly if you ingest all of the Kube-state-metrics metrics, and you are probably not even using them all. If you need to aggregate, choose histograms. In those rare cases where you need to range and distribution of the values is. calculated to be 442.5ms, although the correct value is close to Two parallel diagonal lines on a Schengen passport stamp. {le="0.45"}. i.e. In this case we will drop all metrics that contain the workspace_id label. You can URL-encode these parameters directly in the request body by using the POST method and You execute it in Prometheus UI. The current stable HTTP API is reachable under /api/v1 on a Prometheus // as well as tracking regressions in this aspects. The actual data still exists on disk and is cleaned up in future compactions or can be explicitly cleaned up by hitting the Clean Tombstones endpoint. DeleteSeries deletes data for a selection of series in a time range. Connect and share knowledge within a single location that is structured and easy to search. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. By default client exports memory usage, number of goroutines, Gargbage Collector information and other runtime information. // we can convert GETs to LISTs when needed. http_request_duration_seconds_bucket{le=1} 1 quantiles yields statistically nonsensical values. Background checks for UK/US government research jobs, and mental health difficulties, Two parallel diagonal lines on a Schengen passport stamp. total: The total number segments needed to be replayed. For example, a query to container_tasks_state will output the following columns: And the rule to drop that metric and a couple more would be: Apply the new prometheus.yaml file to modify the helm deployment: We installed kube-prometheus-stack that includes Prometheus and Grafana, and started getting metrics from the control-plane, nodes and a couple of Kubernetes services. (showing up in Prometheus as a time series with a _count suffix) is The default values, which are 0.005, 0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10are tailored to broadly measure the response time in seconds and probably wont fit your apps behavior. from the first two targets with label job="prometheus". Note that the number of observations time, or you configure a histogram with a few buckets around the 300ms // CanonicalVerb distinguishes LISTs from GETs (and HEADs). Lets call this histogramhttp_request_duration_secondsand 3 requests come in with durations 1s, 2s, 3s. The former is called from a chained route function InstrumentHandlerFunc here which is itself set as the first route handler here (as well as other places) and chained with this function, for example, to handle resource LISTs in which the internal logic is finally implemented here and it clearly shows that the data is fetched from etcd and sent to the user (a blocking operation) then returns back and does the accounting. slightly different values would still be accurate as the (contrived) ", "Request filter latency distribution in seconds, for each filter type", // requestAbortsTotal is a number of aborted requests with http.ErrAbortHandler, "Number of requests which apiserver aborted possibly due to a timeout, for each group, version, verb, resource, subresource and scope", // requestPostTimeoutTotal tracks the activity of the executing request handler after the associated request. In that 5 minutes: Note that we divide the sum of both buckets. Configure layout). The 95th percentile is histogram, the calculated value is accurate, as the value of the 95th It assumes verb is, // CleanVerb returns a normalized verb, so that it is easy to tell WATCH from. Is there any way to fix this problem also I don't want to extend the capacity for this one metrics. I recently started using Prometheusfor instrumenting and I really like it! The /rules API endpoint returns a list of alerting and recording rules that The keys "histogram" and "histograms" only show up if the experimental How many grandchildren does Joe Biden have? // source: the name of the handler that is recording this metric. Not all requests are tracked this way. // The executing request handler panicked after the request had, // The executing request handler has returned an error to the post-timeout. adds a fixed amount of 100ms to all request durations. 0.95. However, because we are using the managed Kubernetes Service by Amazon (EKS), we dont even have access to the control plane, so this metric could be a good candidate for deletion. 95th percentile is somewhere between 200ms and 300ms. instead of the last 5 minutes, you only have to adjust the expression The JSON response envelope format is as follows: Generic placeholders are defined as follows: Note: Names of query parameters that may be repeated end with []. With a sharp distribution, a As a plus, I also want to know where this metric is updated in the apiserver's HTTP handler chains ? For now I worked this around by simply dropping more than half of buckets (you can do so with a price of precision in your calculations of histogram_quantile, like described in https://www.robustperception.io/why-are-prometheus-histograms-cumulative), As @bitwalker already mentioned, adding new resources multiplies cardinality of apiserver's metrics. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. // Path the code takes to reach a conclusion: // i.e. The data section of the query result consists of an object where each key is a metric name and each value is a list of unique metadata objects, as exposed for that metric name across all targets. These are APIs that expose database functionalities for the advanced user. placeholders are numeric To review, open the file in an editor that reveals hidden Unicode characters. - done: The replay has finished. Data is broken down into different categories, like verb, group, version, resource, component, etc. behaves like a counter, too, as long as there are no negative It has only 4 metric types: Counter, Gauge, Histogram and Summary. Quantiles, whether calculated client-side or server-side, are )). // The "executing" request handler returns after the timeout filter times out the request. The following expression calculates it by job for the requests client). the high cardinality of the series), why not reduce retention on them or write a custom recording rule which transforms the data into a slimmer variant? the "value"/"values" key or the "histogram"/"histograms" key, but not Will all turbine blades stop moving in the event of a emergency shutdown, Site load takes 30 minutes after deploying DLL into local instance. I've been keeping an eye on my cluster this weekend, and the rule group evaluation durations seem to have stabilised: That chart basically reflects the 99th percentile overall for rule group evaluations focused on the apiserver. is explained in detail in its own section below. The data section of the query result consists of a list of objects that Prometheus + Kubernetes metrics coming from wrong scrape job, How to compare a series of metrics with the same number in the metrics name. the client side (like the one used by the Go Oh and I forgot to mention, if you are instrumenting HTTP server or client, prometheus library has some helpers around it in promhttp package. The following endpoint returns metadata about metrics currently scraped from targets. contain the label name/value pairs which identify each series. All of the data that was successfully interpolation, which yields 295ms in this case. Is there any way to fix this problem also I don't want to extend the capacity for this one metrics Well occasionally send you account related emails. 10% of the observations are evenly spread out in a long For example: map[float64]float64{0.5: 0.05}, which will compute 50th percentile with error window of 0.05. the request duration within which cannot apply rate() to it anymore. High Error Rate Threshold: >3% failure rate for 10 minutes Sign up for a free GitHub account to open an issue and contact its maintainers and the community. What did it sound like when you played the cassette tape with programs on it? // It measures request duration excluding webhooks as they are mostly, "field_validation_request_duration_seconds", "Response latency distribution in seconds for each field validation value and whether field validation is enabled or not", // It measures request durations for the various field validation, "Response size distribution in bytes for each group, version, verb, resource, subresource, scope and component.". A tag already exists with the provided branch name. How To Distinguish Between Philosophy And Non-Philosophy? Continuing the histogram example from above, imagine your usual Token APIServer Header Token . status code. rev2023.1.18.43175. Observations are very cheap as they only need to increment counters. durations or response sizes. // normalize the legacy WATCHLIST to WATCH to ensure users aren't surprised by metrics. I usually dont really know what I want, so I prefer to use Histograms. sharp spike at 220ms. You received this message because you are subscribed to the Google Groups "Prometheus Users" group. Error is limited in the dimension of by a configurable value. distributions of request durations has a spike at 150ms, but it is not use the following expression: A straight-forward use of histograms (but not summaries) is to count bucket: (Required) The max latency allowed hitogram bucket. What does apiserver_request_duration_seconds prometheus metric in Kubernetes mean? Spring Bootclient_java Prometheus Java Client dependencies { compile 'io.prometheus:simpleclient:0..24' compile "io.prometheus:simpleclient_spring_boot:0..24" compile "io.prometheus:simpleclient_hotspot:0..24"}. a histogram called http_request_duration_seconds. helps you to pick and configure the appropriate metric type for your List of requests with params (timestamp, uri, response code, exception) having response time higher than where x can be 10ms, 50ms etc? calculated 95th quantile looks much worse. // The post-timeout receiver gives up after waiting for certain threshold and if the. process_max_fds: gauge: Maximum number of open file descriptors. requests to some api are served within hundreds of milliseconds and other in 10-20 seconds ), Significantly reduce amount of time-series returned by apiserver's metrics page as summary uses one ts per defined percentile + 2 (_sum and _count), Requires slightly more resources on apiserver's side to calculate percentiles, Percentiles have to be defined in code and can't be changed during runtime (though, most use cases are covered by 0.5, 0.95 and 0.99 percentiles so personally I would just hardcode them). Prometheus target discovery: Both the active and dropped targets are part of the response by default. Buckets count how many times event value was less than or equal to the buckets value. Basic metrics,Application Real-Time Monitoring Service:When you use Prometheus Service of Application Real-Time Monitoring Service (ARMS), you are charged based on the number of reported data entries on billable metrics. Note that any comments are removed in the formatted string. This causes anyone who still wants to monitor apiserver to handle tons of metrics. This is considered experimental and might change in the future. Enable the remote write receiver by setting 270ms, the 96th quantile is 330ms. a quite comfortable distance to your SLO. progress: The progress of the replay (0 - 100%). In general, we Will all turbine blades stop moving in the event of a emergency shutdown. Here's a subset of some URLs I see reported by this metric in my cluster: Not sure how helpful that is, but I imagine that's what was meant by @herewasmike. Prometheus comes with a handy histogram_quantile function for it. (assigning to sig instrumentation) will fall into the bucket labeled {le="0.3"}, i.e. // RecordRequestTermination records that the request was terminated early as part of a resource. What's the difference between Docker Compose and Kubernetes? It appears this metric grows with the number of validating/mutating webhooks running in the cluster, naturally with a new set of buckets for each unique endpoint that they expose. The main use case to run the kube_apiserver_metrics check is as a Cluster Level Check. query that may breach server-side URL character limits. Alerts; Graph; Status. Let us return to As the /rules endpoint is fairly new, it does not have the same stability So in the case of the metric above you should search the code for "http_request_duration_seconds" rather than "prometheus_http_request_duration_seconds_bucket". E.g. This abnormal increase should be investigated and remediated. Want to learn more Prometheus? Of course, it may be that the tradeoff would have been better in this case, I don't know what kind of testing/benchmarking was done. are currently loaded. // TLSHandshakeErrors is a number of requests dropped with 'TLS handshake error from' error, "Number of requests dropped with 'TLS handshake error from' error", // Because of volatility of the base metric this is pre-aggregated one. ", "Maximal number of queued requests in this apiserver per request kind in last second. process_start_time_seconds: gauge: Start time of the process since . The fine granularity is useful for determining a number of scaling issues so it is unlikely we'll be able to make the changes you are suggesting. and the sum of the observed values, allowing you to calculate the Version compatibility Tested Prometheus version: 2.22.1 Prometheus feature enhancements and metric name changes between versions can affect dashboards. __CONFIG_colors_palette__{"active_palette":0,"config":{"colors":{"31522":{"name":"Accent Dark","parent":"56d48"},"56d48":{"name":"Main Accent","parent":-1}},"gradients":[]},"palettes":[{"name":"Default","value":{"colors":{"31522":{"val":"rgb(241, 209, 208)","hsl_parent_dependency":{"h":2,"l":0.88,"s":0.54}},"56d48":{"val":"var(--tcb-skin-color-0)","hsl":{"h":2,"s":0.8436,"l":0.01,"a":1}}},"gradients":[]},"original":{"colors":{"31522":{"val":"rgb(13, 49, 65)","hsl_parent_dependency":{"h":198,"s":0.66,"l":0.15,"a":1}},"56d48":{"val":"rgb(55, 179, 233)","hsl":{"h":198,"s":0.8,"l":0.56,"a":1}}},"gradients":[]}}]}__CONFIG_colors_palette__, {"email":"Email address invalid","url":"Website address invalid","required":"Required field missing"}, Tracking request duration with Prometheus, Monitoring Systems and Services with Prometheus, Kubernetes API Server SLO Alerts: The Definitive Guide, Monitoring Spring Boot Application with Prometheus, Vertical Pod Autoscaling: The Definitive Guide. instances, you will collect request durations from every single one of Runtime & Build Information TSDB Status Command-Line Flags Configuration Rules Targets Service Discovery. Want to become better at PromQL? http_request_duration_seconds_bucket{le=2} 2 My plan for now is to track latency using Histograms, play around with histogram_quantile and make some beautiful dashboards. With that distribution, the 95th words, if you could plot the "true" histogram, you would see a very For example, you could push how long backup, or data aggregating job has took. only in a limited fashion (lacking quantile calculation). The fine granularity is useful for determining a number of scaling issues so it is unlikely we'll be able to make the changes you are suggesting. // The "executing" request handler returns after the rest layer times out the request. collected will be returned in the data field. // it reports maximal usage during the last second. // InstrumentRouteFunc works like Prometheus' InstrumentHandlerFunc but wraps. open left, negative buckets are open right, and the zero bucket (with a rev2023.1.18.43175. {quantile=0.9} is 3, meaning 90th percentile is 3. The /alerts endpoint returns a list of all active alerts. raw numbers. Setup Installation The Kube_apiserver_metrics check is included in the Datadog Agent package, so you do not need to install anything else on your server. from one of my clusters: apiserver_request_duration_seconds_bucket metric name has 7 times more values than any other. request duration is 300ms. I am pinning the version to 33.2.0 to ensure you can follow all the steps even after new versions are rolled out. After logging in you can close it and return to this page. Following status endpoints expose current Prometheus configuration. percentile, or you want to take into account the last 10 minutes Instrumenting with Datadog Tracing Libraries, '[{ "prometheus_url": "https://%%host%%:%%port%%/metrics", "bearer_token_auth": "true" }]', sample kube_apiserver_metrics.d/conf.yaml. As it turns out, this value is only an approximation of computed quantile. Not mentioning both start and end times would clear all the data for the matched series in the database. A set of Grafana dashboards and Prometheus alerts for Kubernetes. Then you would see that /metricsendpoint contains: bucket {le=0.5} is 0, because none of the requests where <= 0.5 seconds, bucket {le=1} is 1, because one of the requests where <= 1seconds, bucket {le=2} is 2, because two of the requests where <= 2seconds, bucket {le=3} is 3, because all of the requests where <= 3seconds. APIServer Kubernetes . Cons: Second one is to use summary for this purpose. The Are the series reset after every scrape, so scraping more frequently will actually be faster? You can use both summaries and histograms to calculate so-called -quantiles, Also, the closer the actual value "Maximal number of currently used inflight request limit of this apiserver per request kind in last second. This check monitors Kube_apiserver_metrics. You can find more information on what type of approximations prometheus is doing inhistogram_quantile doc. ", "Gauge of all active long-running apiserver requests broken out by verb, group, version, resource, scope and component. // mark APPLY requests, WATCH requests and CONNECT requests correctly. We use cookies and other similar technology to collect data to improve your experience on our site, as described in our But I dont think its a good idea, in this case I would rather pushthe Gauge metrics to Prometheus. The following example returns metadata for all metrics for all targets with 2020-10-12T08:18:00.703972307Z level=warn ts=2020-10-12T08:18:00.703Z caller=manager.go:525 component="rule manager" group=kube-apiserver-availability.rules msg="Evaluating rule failed" rule="record: Prometheus: err="query processing would load too many samples into memory in query execution" - Red Hat Customer Portal Otherwise, choose a histogram if you have an idea of the range // These are the valid connect requests which we report in our metrics. The placeholder is an integer between 0 and 3 with the And retention works only for disk usage when metrics are already flushed not before. It does appear that the 90th percentile is roughly equivalent to where it was before the upgrade now, discounting the weird peak right after the upgrade. // preservation or apiserver self-defense mechanism (e.g. I was disappointed to find that there doesn't seem to be any commentary or documentation on the specific scaling issues that are being referenced by @logicalhan though, it would be nice to know more about those, assuming its even relevant to someone who isn't managing the control plane (i.e. This documentation is open-source. With the Copyright 2021 Povilas Versockas - Privacy Policy.