I want to know if it's possible to get metrics for the services inside the pods using Prometheus.
I don't mean monitoring the pods but the processes inside those pods. For example, containers which have apache or nginx running inside them along other main services, so I can retrieve metrics for the web server and the other main service (for example a wordpress image which aso comes with an apache configured).
The cluster already has running kube-state-metrics, node-exporter and blackbox exporter.
Is it possible? If so, how can I manage to do it?
Thanks in advance
Prometheus works by scraping an HTTP endpoint that provides the actual metrics. That's where you get the term "exporter". So if you want to get metrics from the processes running inside of pods you have three primary steps:
You must modify those processes to export the metrics you care about. This is inherently something that must be custom for each kind of application. The good news is that there are lots of pre-built ones including things like nginx and apache that you mention . Most application frameworks also have capability to export prometheus metrics. ex: Microprofile, Quarkus, and many more.
You must then modify your pod definition to expose the HTTP endpoint that those processes are now providing. Very straightfoward, but will depend on the configuration you specify for your exporters.
You must then modify your Prometheus to scrape those targets. This will depend on your monitoring stack. For Openshift you will find the docs here for enabling user workload monitoring, and here for providing exporter details.
Related
Problem setting. Suppose I have 2 pods, A and B. I want to be able to dynamically scale pod A based on some arbitrary number from some arbitrary source. Suppose that pod B is such a source: for example, it can have an HTTP server with an endpoint which responds with the number of desired replicas of pod A at the moment of request. Or maybe it is an ES server or a SQL DB (does not matter).
Question. What kubernetes objects do I need to define to achieve this (apart from HPA)? What configuration should HPA have to know that it needs to look up B for current metric? How should API of B look like (or is there any constraints?)?
Research I have made. Unfortunately, the official documentation does not say much about it, apart from declaring that there is such a possibility. There are also two repositories, one with some go boilerplate code that I have trouble building and another one that has no usage instructions whatsoever (though allegedly does fulfil the "external metrics over HTTP" requirement).
By having a look at the .yaml configs in those repositories, I have reached a conclusion that apart from Deployment and Service one needs to define an APIService object that registers the external or custom metric in the kubernetes API and links it with a normal service (where you would have your pod) and a handful of ClusterRole and ClusterRoleBinding objects. But there is no explanation about it. Also I could not even list existing APIServices with kubectl in my local cluster (of 1.15 version) like other objects.
The easiest way will be to feed metrics into Prometheus (which is a commonly solved problem), and then setup a Prometheus-based HPA (also a commonly solved problem).
1. Feed own metrics to Prometheus
Start with Prometheus-Operator to get the cluster itself monitored, and get access to ServiceMonitor objects. ServiceMonitors are pointers to services in the cluster. They let your pod's /metrics endpoint be discovered and scraped by a prometheus server.
Write a pod that reads metrics from your 3rd party API and shows them in own /metrics endpoint. This will be the adapter between your API and Prometheus format. There are clients of course: https://github.com/prometheus/client_python#exporting
Write a Service of type ClusterIP that represents your pod.
Write a ServiceMonitor that points to a service.
Query your custom metrics thru Prometheus dashboard to ensure this stage is done.
2. Setup Prometheus-based HPA
Setup Prometheus-Adapter and follow the HPA walkthrough.
Or follow the guide https://github.com/stefanprodan/k8s-prom-hpa
This looks like a huge pile of work to get the HPA. However, only the adapter pod is a custom part here. Everything else is a standard stack setup in most of the clusters, and you will get many other use cases for it anyways.
I have two Kubernetes clusters representing dev and staging environments.
Separately, I am also deploying a custom DevOps dashboard which will be used to monitor these two clusters. On this dashboard I will need to show information such as:
RAM/HD Space/CPU usage of each deployed Pod in each environment
Pod health (as in if it has too many container restarts etc)
Pod uptime
All these stats have to be at a cluster level and also per namespace, preferably. As in, if I query a for a particular namespace, I have to get all the resource usages of that namespace.
So the webservice layer of my dashboard will send a service request to the master node of my respective cluster in order to fetch this information.
Another thing I need is to implement real time notifications in my DevOps dashboard. Every time a container fails, I need to catch that event and notify relevant personnel.
I have been reading around and two things that pop up a lot are Prometheus and Metric Server. Do I need both or will one do? I set up Prometheus on a local cluster but I can't find any endpoints it exposes which could be called by my dashboard service. I'm also trying to set up Prometheus AlertManager but so far it hasn't worked as expected. Trying to fix it now. Just wanted to check if these technologies have the capabilities to meet my requirements.
Thanks!
I don't know why you are considering your own custom monitoring system. Prometheus operator provides all the functionality that you mentioned.
You will end up only with your own grafana dashboard with all required information.
If you need custom notification you can set it up in Alertmanager creating correct prometheusrules.monitoring.coreos.com, you can find a lot of preconfigured prometheusrules in kubernetes-mixin
.
Using labels and namespaces in Alertmanager you can setup a correct route to notify person responsible for a given deployment.
Do I need both or will one do?, yes, you need both - Prometheus collects and aggregates metric when Metrick server exposes metrics from your cluster node for your Prometheus to scrape it.
If you have problems with Prometheus, Alertmanger and so on consider using helm chart as entrypoint.
Prometheus + Grafana are a pretty standard setup.
Installing kube-prometheus or prometheus-operator via helm will give you
Grafana, Alertmanager, node-exporter and kube-state-metrics by default and all be setup for kubernetes metrics.
Configure alertmanager to do something with the alerts. SMTP is usually the first thing setup but I would recommend some sort of event manager if this is a service people need to rely on.
Although a dashboard isn't part of your requirements, this will inform how you can connect into prometheus as a data source. There is docco on adding prometheus data source for grafana.
There are a number of prebuilt charts available to add to Grafana. There are some charts to visualise alertmanager too.
Your external service won't be querying the metrics directly with prometheus, in will be querying the collected data in prometheus stored inside your cluster. To access the API externally you will need to setup an external path to the prometheus service. This can be configured via an ingress controller in the helm deployment:
prometheus.ingress.enabled: true
You can do the same for the alertmanager API and grafana if needed.
alertmanager.ingress.enabled: true
grafana.ingress.enabled: true
You could use Grafana outside the cluster as your dashboard via the same prometheus ingress if it proves useful.
we are using k8s cluster for one of our application, cluster is owned by other team and we dont have full control over there… We are trying to find out metrics around resource utilization (CPU and memory), detail about running containers/pods/nodes etc. Need to find out how many parallel containers are running. Problem is they have exposed monitoring of cluster via Prometheus but with Prometheus we are not getting live data, it does not have info about running containers.
My query is , what is that API which is by default available in k8s cluster and can give all what we need. We dont want to read data form another client like Prometheus or anything else, we want to read metrics directly from cluster so that data is not stale. Any suggestions?
As you mentioned you will need metrics-server (or heapster) to get those information.
You can confirm if your metrics server is running kubectl top nodes/pods or just by checking if there is a heapster or metrics-server pod present in kube-system namespace.
Also the provided command would be able to show you the information you are looking for. I wont go into details as here you can find a lot of clues and ways of looking at cluster resource usage. You should probably take a look at cadvisor too which should be already present in the cluster. It exposes a web UI which exports live information about all the containers on the machine.
Other than that there are probably commercial ways of acheiving what you are looking for, for example SignalFx and other similar projects - but this will probably require the cluster administrator involvement.
would like to see k8 Service level metrics in Grafana from underlying prometheus server.
For instance:
1) If i have 3 application pods exposed through a service i would like to see service level metrics for CPU,memory & network I/O pressure ,Total # of requests,# of requests failed
2)Also if i have group of pods(replicas) related to an application which doesn"t have Service on top of them would like to see the aggregated metrics of the pods related to that application in a single view on grafana
What would be the prometheus queries to achieve the same
Service level metrics for CPU, memory & network I/O pressure
If you have Prometheus installed on your Kubernetes cluster, all those statistics are being already collected by Prometheus. There are many good articles about how to install and how to use Kubernetes+Prometheus, try to check that one, as an example.
Here is an example of a request to fetch container memory usage:
container_memory_usage_bytes{image="CONTAINER:VERSION"}
Total # of requests,# of requests failed
Those are service-level metrics, and for collecting them, you need to use Prometheus Exporter created especially for your service. Check the list with exporters, find one which you need for your service and follow its instruction.
If you cannot find an Exporter for your application, you can write it yourself, here is an official documentation about it.
application which doesn"t have Service on top of them would like to see the aggregated metrics of the pods related to that application in a single view on grafana
It is possible to combine any graphics in a single view in Grafana using Dashboards and Panels. Check an official documentation, all that topics pretty detailed and easy to understand.
Aggregation can be done by Prometheus itself by aggregation operations.
All metrics from Kubernetes has labels, so you can group by them:
sum(http_requests_total) by (application, group), where application and group is labels.
Also, here is an official Prometheus instruction about how to add Prometheus to Grafana as a Datasourse.
I am trying to figure out how to best collect metrics from a set of spring boot based services running within a Kubernetes cluster. Looking at the various docs, it seems that the choice for internal monitoring is between Actuator or Spectator with metrics being pushed to an external collection store such as Redis or StatsD or pulled, in the case of Prometheus.
Since the number of instances of a given service is going to vary, I dont see how Prometheus can be configured to poll those running services since it will lack knowledge of them. I am also building around a Eureka service registry so not sure if that is polled first in this configuration.
Any real world insight into this kind of approach would be welcome.
You should use the Prometheus java client (https://www.robustperception.io/instrumenting-java-with-prometheus/) for instrumenting. Approaches like redis and statsd are to be avoided, as they mean hitting the network on every single event - greatly limiting what you can monitor.
Use file_sd service discovery in Prometheus to provide it with a list of targets from Eureka (https://www.robustperception.io/using-json-file-service-discovery-with-prometheus/), though if you're using Kubernetes like your tag hints Prometheus has a direct integration there.