I'm using Kube-prometheus with Prometheus-Operator to monitor my K8s cluster. I've deployed Jenkins on my cluster and want to start to get metrics here using ServiceMonitor.
I've installed the Prometheus plugin which exposes the metrics using /prometheus or by /metrics/API_KEY/metrics, this works fine if I create a new static job. However, if I want to use ServiceMonitor, it does not work.
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
labels:
k8s-app: jenkins
name: jenkins
namespace: monitoring
spec:
endpoints:
- interval: 30s
port: http
path: /metrics/y1H6G16T-DhqpHdW9XwHWnP9FWAXMMfy4XnXVnyoIOEV3-gPJZKN284OFUcVkPxL/metrics
selector:
matchLabels:
jenkins: main
I don't know about ServiceMonitor, but I monitor my Jenkins instance without any problem, using annotations on Jenkins' service :
prometheus.io/scrape: "true"
prometheus.io/port: "8080"
prometheus.io/path: "/prometheus"
I'm using kube-prometheus-stack v12.8.0 (formerly known as the prometheus-operator helm chart).
To make prometheus-operator detect external serviceMonitors (like the one provided by Jenkins), you'll have to configure two things:
configure it to scan other namespaces:
serviceMonitorNamespaceSelector
matchLabels:
prometheus: please-scan-this-namespace-too
note: alternatively, you can leave it to {} so that all namespaces are scanned
configure it to also select the serviceMonitors detected in these other namespaces:
serviceMonitorSelector:
matchLabels:
release: prometheus-operator
note: even though the documentation states that if you leave serviceMonitorSelector to {}, it will select all serviceMonitors, it does not seem to work.
And finally, you'd still need to add these labels to 1) the namespaces and 2) serviceMonitors that you want prometheus to adopt.
Related
Problem Facing: When I try to run kubectl apply command on both the files below and try to see the app in the browser in http://192.168.49.2:30080/ the app did not render.I tried to run minikube service fleetman - webapp --url but still no progress . Please Help !!!
Additional information :minikube ip -192.168.49.2 .
Note:I have installed docker Desktop app on my mac book air catalina.
Browser message: This site can’t be reached 192.168.49.2 took too long to respond.
Docker image Link :https://hub.docker.com/r/richardchesterwood/k8s-fleetman-webapp-angular
first-pod.yaml file
apiVersion: v1
kind: Pod
metadata:
name: webapp
labels :
mylabelname: webapp
spec:
containers:
- name: webapp
image: richardchesterwood/k8s-fleetman-webapp-angular:release0
webapp-services.yaml file
apiVersion: v1
kind: Service
metadata:
name: fleetman-webapp
spec:
# This defines which pods are going to be represented by this Service
# The service becomes a network endpoint for either other services
# or maybe external users to connect to (eg browser)
selector:
mylabelname: webapp
ports:
- name: http
port: 80
nodePort: 30080
type: NodePort
Try creating minikube with driver none:
$ minikube start --driver=none
The none driver allows advanced minikube users to skip VM creation, allowing minikube to be run on a user-supplied VM.
Hence you will be able to communicate to your app via your host (ie. user-supplied VM) network address.
We are using Rancher and Racher tools for monitoring. i.e. Prometheus and Grafana on Rancher.
Rancher Monitoring
I am looking for automation of custom dashboard import in the Grafana. I referred to the Grafana documentation for provisioning here
Also referred to the answer of the question here. - stackoverflow
The automation needs to be done via updating dashboardProviders in values.yml or enabling sidecar.
Refering Grafana helm chart here values.yml
But this does not seem to be working for Grafana in Rancher Monitoring. Please refer to Rancher Grafana chart here -
Rancher Monitoring Grafana values.yml. The Rancher version does not have dashboardProviders or sideCar.
My questions are -
Is there any way to add dashboardProviders Or sidecar in Rancher Grafana to automate the dashboards?
Is there any other way, to automate the deployment of the dashboards of Grafana in Rancher.
I had the same issue.
After investigation of grafana-helm-charts it seams that you should add two additional blocks.
First is grafana.dashboardProviders and second grafana.dashboards eg:
grafana:
enabled: true
plugins:
- grafana-worldmap-panel
- grafana-piechart-panel
dashboardProviders:
external.yaml:
apiVersion: 1
providers:
- name: 'external'
orgId: 1
folder: ''
type: file
disableDeletion: false
editable: false
options:
path: /var/lib/grafana/dashboards/external
dashboards:
external:
nginx-ingress-prod:
gnetId: 9614
datasource: prod_cluster
The external word in above example is a name of provider and need to match to this one used in grafana.dashboard section.
Also the path in grafana.dashboardProviders.options.path should contains the provider name at the end as it is used by download_dashboards.sh script that download the json body of the dashboard.
Another way of adding own dashboard is by using config map with proper label like it is described in create-persistent-grafana-dashboard but for me this way did not work until I added the dashboard-provider: external label beside grafana_dashboard: "1" eg:
---
apiVersion: v1
kind: ConfigMap
metadata:
labels:
grafana_dashboard: "1"
dashboard-provider: external
name: nginx-ingress
namespace: cattle-dashboards
data:
nginx-ingress.json: |-
{...}
For non-regular and manual generation of the Grafana dashboards from the Prometheus metrics sample (i.e Micrometer format sample) you can use this service:
http://eljah.tatar/micrometer2grafana/
I'm working for a spinnaker for create a new CD pipeline.
I've deployed halyard in a docker container on my computer, and also deployed spinnaker from it to the Google Kubernetes Engine.
After all of them, I've prepared a new ingress yaml file, shown as below.
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
name: jenkins-cloud
namespace: spinnaker
spec:
rules:
- http:
paths:
- path: /*
backend:
serviceName: spin-deck
servicePort: 9000
After accessing the spinnaker UI via a public IP, I got an error, shown as below.
Error fetching applications. Check that your gate endpoint is accessible.
After all of them, I've checked the docs about it and I've run some commands shown as below.
I've checked the service data on my K8S cluster.
spin-deck NodePort 10.11.245.236 <none> 9000:32111/TCP 1h
spin-gate NodePort 10.11.251.78 <none> 8084:31686/TCP 1h
For UI
hal config security ui edit --override-base-url "http://spin-deck.spinnaker:9000"
For API
hal config security api edit --override-base-url "http://spin-gate.spinnaker:8084"
After running these commands and redeploying spinnaker, the error repeated itself.
How can I solve the problem of accessing the spinnaker gate from the UI?
--override-base-url should be populated without port.
Background: I'm trying to set up a Bitcoin Core regtest pod on Google Cloud Platform. I borrowed some code from https://gist.github.com/zquestz/0007d1ede543478d44556280fdf238c9, editing it so that instead of using Bitcoin ABC (a different client implementation), it uses Bitcoin Core instead, and changed the RPC username and password to both be "test". I also added some command arguments for the docker-entrypoint.sh script to forward to bitcoind, the daemon for the nodes I am running. When attempting to deploy the following three YAML files, the dashboard in "workloads" shows bitcoin has not having minimum availability. Getting the pod to deploy correctly is important so I can send RPC commands to the Load Balancer. Attached below are my YAML files being used. I am not very familiar with Kubernetes, and I'm doing a research project on scalability which entails running RPC commands against this pod. Ask for relevant logs and I will provide them in seperate pastebins. Right now, I'm only running three machines on my cluster, as I'm am still setting this up. The zone is us-east1-d, machine type is n1-standard-2.
Question: Given these files below, what is causing GCP Kubernetes Engine to respond with "Does not have minimum availability", and how can this be fixed?
bitcoin-deployment.sh
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
namespace: default
labels:
service: bitcoin
name: bitcoin
spec:
strategy:
type: Recreate
replicas: 1
template:
metadata:
labels:
service: bitcoin
spec:
containers:
- env:
- name: BITCOIN_RPC_USER
valueFrom:
secretKeyRef:
name: test
key: test
- name: BITCOIN_RPC_PASSWORD
valueFrom:
secretKeyRef:
name: test
key: test
image: ruimarinho/bitcoin-core:0.17.0
name: bitcoin
ports:
- containerPort: 18443
protocol: TCP
volumeMounts:
- mountPath: /data
name: bitcoin-data
resources:
requests:
memory: "1.5Gi"
command: ["./entrypoint.sh"]
args: ["-server", "-daemon", "-regtest", "-rpcbind=127.0.0.1", "-rpcallowip=0.0.0.0/0", "-rpcport=18443", "-rpcuser=test", "-rpcpassport=test"]
restartPolicy: Always
volumes:
- name: bitcoin-data
gcePersistentDisk:
pdName: disk-bitcoincore-1
fsType: ext4
bitcoin-secrets.yml
apiVersion: v1
kind: Secret
metadata:
name: bitcoin
type: Opaque
data:
rpcuser: dGVzdAo=
rpcpass: dGVzdAo=
bitcoin-srv.yml
apiVersion: v1
kind: Service
metadata:
name: bitcoin
namespace: default
spec:
ports:
- port: 18443
targetPort: 18443
selector:
service: bitcoin
type: LoadBalancer
externalTrafficPolicy: Local
I have run into this issue several times. The solutions that I used:
Wait. Google Cloud does not have enough resource available in the Region/Zone that you are trying to launch into. In some cases this took an hour to an entire day.
Select a different Region/Zone.
An example was earlier this month. I could not launch new resources in us-west1-a. I think just switched to us-east4-c. Everything launched.
I really do not know why this happens under the covers with Google. I have personally experienced this problem three times in the last three months and I have seen this problem several times on StackOverflow. The real answer might be a simple is that Google Cloud is really started to grow faster than their infrastructure. This is a good thing for Google as I know that they are investing in major new reasources for the cloud. Personally, I really like working with their cloud.
There could be many reasons for this failure:
Insufficient resources
Liveliness probe failure
Readiness probe failure
I encountered this error within GKE.
The reason was the pod was not about to find the configmap due to name mismatch. So make sure all the resources are discoverable by the pod.
The error message you mentioned isn't directly pointing to a stockout; it's more of resources unavailable within the cluster. You can try again after adding another node to the cluster etc. Also, this troubleshooting guide suggests if your Nodes have enough resources but you still have Does not have minimum availability message, check if the Nodes have SchedulingDisabled or Cordoned status: in this case they don't accept new pods.
Please, check your logs https://console.cloud.google.com/logs you might be surprised that your app is been failing.
I faced with the same issue when my spring-boot application failed to start due to my spring-boot configuration mistake.
Also in the args you use:
args: ["-server", "-daemon", "-regtest", "-rpcbind=127.0.0.1", "-rpcallowip=0.0.0.0/0", "-rpcport=18443", "-rpcuser=test", "-rpcpassport=test"]
should it be "-rpcpassport" or "-rpcpassword" ?
Is there any way to scale Kubernetes nodes based on network utilization and not based on memory or CPU?
Let's say for example you are sending thousands of requests to a couple of nodes behind a load balancer. The CPU is not struggling or the memory, but because there are thousands of requests per second you would need additional nodes to serve this. How can you do this in Google Cloud Kubernetes?
I have been researching around but I can't seem to find any references to this type of scaling, and I am guessing I am not the only one to come across this problem. So I am wondering if any of you knows of any best practice solutions.
I guess the ideal solution would be to have one pod per node receiving requests and creating more nodes based on more requests and scale up or down based on this.
This is possible and you have to use Prometheus Adaptor to configure custom rules to generate Custom Metrics.
This link has more details on how to setup prometheus, install adaptor and apply configuration with custom metrics..
I've implement this on my gke cluster using this custom metrics.
This the example of my HPA configuration :
apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
name: hpa-name
namespace: your-namespace
annotations:
metric-config.external.prometheus-query.prometheus/interval: 30s
metric-config.external.prometheus-query.prometheus/prometheus-server: http://your-prometheus-server-ip
metric-config.external.prometheus-query.prometheus/istio-requests-total: |
sum(rate(istio_requests_total{reporter="destination", destination_workload="deployment-name", destination_service_namespace="your-namespace"}[2m]))
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: deployment-name
minReplicas: 1
maxReplicas: 10
metrics:
- type: External
external:
metric:
name: prometheus-query
selector:
matchLabels:
query-name: istio-requests-total
target:
type: AverageValue
averageValue: 7
I think HPA(Horizontal Pod Autoscaler) along with Cluster Autoscaler will do the magic.
Have a look at this - https://medium.com/google-cloud/kubernetes-autoscaling-with-istio-metrics-76442253a45a