k8s resources overview planning - kubernetes

We are planning on delivering small k8s clusters to clients with our application on top.
Currently we are struggling on see what resources we actually need. At average we are running 20-30 pods in the system.
While getting resources requests and limits per deployment is not hard to see.
It is hared to get full view of all requests or all limits resources for all pods that are running in the cluster. At least in an automated way.
Is there prebuild dashboard in Grafana or some kind of kubectl command that would collect all of the requests and limits for all pods running in the k8s cluster?
The result should be a "nice" report for all resource requirements.
Since we are delivering a "static" cluster to clients there is no hpa roles in our clusters.
So far we have done manual check per each pod and write it in Excel table which is not time efficient and repeatable.

Hi skolko you can use prometheus for monitoring your kubernetes cluster there are various options available like monitoring individual deployments, monitoring entire cluster and monitoring each pod individually. Follow this document for setting up the prometheus monitoring for kubernetes and this document for getting an overview on metrics available for monitoring.

Related

Is it possible to schedule a pod to run for say 24 hours and then remove deployment/statefulset? or need to use jobs?

We have a bunch of pods running in dev environment. The pods are auto-provisioned by an application on every business action. The problem is that across various namespaces they are accumulating and eating available resources in EKS.
Is there a way without jenkins/k8s jobs to simply put some parameter on the pod manifest to tell it to self destruct say in 24 hours?
Add to your pod.spec:
activeDeadlineSeconds: 86400
After deadline your Pod will be stopped for good with the status DeadlineExceeded
If I understood your situation properly, you would like to scale your cluster down in order to save resources.
Kubernetes is featured with the ability to autoscale your application in a cluster. Literally, it means that Kubernetes can start additional pods when the load is increasing and terminate excessive pods when the load is decreasing.
It is possible to downscale the application to zero pods, but, in this case, you will have a delay serving the first request while the pod is starting.
This functionality relies on performance metrics. From the practical side, it means that autoscaling doesn't happen instantly, because it takes some time to performance metrics reach the configured threshold.
The mentioned Kubernetes feature called HPA(horizontal pod autoscale) is described in this document.
In case you are running your cluster on GCP or GKE, you are able to go further and automatically start additional nodes for your cluster when you need more computing capacity and shut down nodes when they are not running application pods anymore.
More information about this functionality can be found following the link.
Last, but not least, you can use tool like Ansible to manage all your kubernetes assets (it can create/manage deployments via playbooks).
If you decide to give it a try, you might find this information useful:
Creating a Container cluster in GKE
70% cheaper Kubernetes cluster on AWS
How to build a Kubernetes Horizontal Pod Autoscaler using custom metrics

Are Kube-state-metrics new or well formatted metrics?

I am fairly new to Kubernetes and had a question concerning kube-state-metrics. When I simply monitor Kubernetes using Prometheus I obtain a set of metrics from the cAdvisor, the nodes (node exporter), the pods, etc. When I include the kube-state-metrics, I seem to obtain more "relevant" metrics. Do kube-state-metrics allow to scrape "new" information from Kubernetes or are they rather "formatted" metrics using the initial Kubernetes metrics (from the nodes, etc. I mentioned earlier).
The two are basically unrelated. Cadvisor is giving you low-level stats about the containers like how much RAM and CPU they are using. KSM gives you info from the Kubernetes API like the Pod object status. Both are useful for different things and you probably want both.

Live monitoring of container, nodes and cluster

we are using k8s cluster for one of our application, cluster is owned by other team and we dont have full control over thereā€¦ 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.

Kubernetes automatic shutdown after some idle time

Does kubernetes or Helm support shut down the pods if it is idle for more than a given threshold time?
This would be very useful in the development environment, to provide room for other processes to consume it and save cost.
Kubernetes is featured with the ability to autoscale your application in a cluster. Literally, it means that Kubernetes can start additional pods when the load is increasing and terminate excessive pods when the load is decreasing.
It is possible to downscale the application to zero pods, but, in this case, you will have a delay serving the first request while the pod is starting.
This functionality relies on performance metrics provided by Heapster application, that must be run in the cluster. From the practical side, it means that autoscaling doesn't happen instantly, because it takes some time to performance metrics reach the configured threshold.
The mentioned Kubernetes feature called HPA(horizontal pod autoscale) is described in this document.
In case you are running your cluster on GCP or GKE, you are able to go further and automatically start additional nodes for your cluster when you need more computing capacity and shut down nodes when they are not running application pods anymore.
More information about this functionality can be found following the link.
If you decide to give it a try, you might find this information useful:
Creating a Container cluster in GKE
70% cheaper Kubernetes cluster on AWS
How to build a Kubernetes Horizontal Pod Autoscaler using custom metrics

How do you monitor kubernetes nodes deployed using kops?

We have some Kubernetes clusters that have been deployed using kops in AWS.
We really like using the upstream/official images.
We have been wondering whether or not there was a good way to monitor the systems without installing software directly on the hosts? Are there docker containers that can extract the information from the host? I think that we are likely concerned with:
Disk space (this seems to be passed through to docker via df
Host CPU utilization
Host memory utilization
Is this host/node level information already available through heapster?
Not really a question about kops, but a question about operating Kubernetes. kops stops at the point of having a functional k8s cluster. You have networking, DNS, and nodes have joined the cluster. From there your world is your oyster.
There are many different options for monitoring with k8s. If you are a small team I usually recommend offloading monitoring and logging to a provider.
If you are a larger team or have more specific needs then you can look at such options as Prometheus and others. Poke around in the https://github.com/kubernetes/charts repository, as I know there is a Prometheus chart there.
As with any deployment of any form of infrastructure you are going to need Logging, Monitoring, and Metrics. Also, do not forget to monitor the monitoring ;)
I am using https://prometheus.io/, it goes naturally with kubernetes.
Kubernetes api already exposes a bunch of metrics in prometheus format,
https://github.com/kubernetes/ingress-nginx also exposes prometheus metrics (enable-vts-status: "true"), and you can also install https://github.com/prometheus/node_exporter as a daemonset to monitor CPU, disk, etc...
I install one prometheus inside the cluster to monitor internal metrics and one outside the cluster to monitor LBs and URLs.
Both send alerts to the same https://github.com/prometheus/alertmanager that MUST be outside the cluster.
It took me about a week to configure everything properly.
It was worth it.