Error setting up tools on kubernetes on local system
I am just beginning with kubernetes. I am following the wiki provided by pipelineIO and setting everything up. I have successfully setup kubernetes but the other tools that I need to run on the clusters havent gone so successfully. Here is the bash script for them:
#!/bin/sh
echo '...MySql...'
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/sql.ml/mysql-rc.yaml
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/sql.ml/mysql-svc.yaml
echo '...HDFS...'
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/hdfs.ml/hdfs-rc.yaml
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/hdfs.ml/hdfs-svc.yaml
echo '...Hive Metastore...'
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/metastore.ml/metastore-rc.yaml
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/metastore.ml/metastore-svc.yaml
echo '...Spark - Master...'
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/apachespark.ml/spark-master-rc.yaml
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/apachespark.ml/spark-master-svc.yaml
echo '...Spark - Worker...'
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/apachespark.ml/spark-worker-rc.yaml
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/apachespark.ml/spark-worker-svc.yaml
echo '...JupyterHub...'
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/jupyterhub.ml/jupyterhub-rc.yaml
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/jupyterhub.ml/jupyterhub-svc.yaml
echo '...Dashboard - Weavescope...'
kubectl create -f https://raw.githubusercontent.com/fluxcapacitor/pipeline/master/dashboard.ml/weavescope/weavescope.yaml
kubectl describe svc weavescope-app
Out of these, only weavescope has been successfully setup and rest show error as displayed in image:
I dont understand what went wrong and how to fix it. I haven't been able to fix the issue by searching online. I don't think any docker images were actually downloaded by kubernetes but I dont know if that is the problem or not. Please help.
ps: If it is in any way required :
OS: Ubuntu 16.04
CPU: Intel i5 6200
GPU: Nvidia GeForce 940MX
EDIT 1:
I didnt find anything about findSelector after running the query kubectl describe node minikube, here's the output:
Name: minikube
Role:
Labels: beta.kubernetes.io/arch=amd64
beta.kubernetes.io/os=linux
kubernetes.io/hostname=minikube
Taints: <none>
CreationTimestamp: Mon, 30 Jan 2017 02:16:46 +0530
Phase:
Conditions:
Type Status LastHeartbeatTime LastTransitionTime Reason Message
---- ------ ----------------- ------------------ ------ -------
OutOfDisk False Tue, 31 Jan 2017 02:55:10 +0530 Mon, 30 Jan 2017 02:16:46 +0530 KubeletHasSufficientDisk kubelet has sufficient disk space available
MemoryPressure False Tue, 31 Jan 2017 02:55:10 +0530 Mon, 30 Jan 2017 02:16:46 +0530 KubeletHasSufficientMemory kubelet has sufficient memory available
DiskPressure False Tue, 31 Jan 2017 02:55:10 +0530 Mon, 30 Jan 2017 02:16:46 +0530 KubeletHasNoDiskPressure kubelet has no disk pressure
Ready True Tue, 31 Jan 2017 02:55:10 +0530 Mon, 30 Jan 2017 02:16:47 +0530 KubeletReady kubelet is posting ready status
Addresses: 192.168.99.100,192.168.99.100,minikube
Capacity:
alpha.kubernetes.io/nvidia-gpu: 0
cpu: 2
memory: 2049008Ki
pods: 110
Allocatable:
alpha.kubernetes.io/nvidia-gpu: 0
cpu: 2
memory: 2049008Ki
pods: 110
System Info:
Machine ID: 112c60c791a944ff93bbc446e8c28598
System UUID: E0D8970E-F2E2-4503-A282-756ADA83592A
Boot ID: 9305d5d2-11e9-411a-b335-b5aa3d59432e
Kernel Version: 4.7.2
OS Image: Buildroot 2016.08
Operating System: linux
Architecture: amd64
Container Runtime Version: docker://1.11.1
Kubelet Version: v1.5.1
Kube-Proxy Version: v1.5.1
ExternalID: minikube
Non-terminated Pods: (4 in total)
Namespace Name CPU Requests CPU Limits Memory Requests Memory Limits
--------- ---- ------------ ---------- --------------- -------------
default weavescope-probe-zk779 50m (2%) 50m (2%) 0 (0%) 0 (0%)
kube-system kube-addon-manager-minikube 5m (0%) 0 (0%) 50Mi (2%) 0 (0%)
kube-system kube-dns-v20-75pq6 110m (5%) 0 (0%) 120Mi (5%)220Mi (10%)
kube-system kubernetes-dashboard-5q16v 0 (0%) 0 (0%) 0 (0%) 0 (0%)
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.
CPU Requests CPU Limits Memory Requests Memory Limits
------------ ---------- --------------- -------------
165m (8%) 50m (2%) 170Mi (8%) 220Mi (10%)
Events:
FirstSeen LastSeen Count From SubObjectPath Type Reason Message
--------- -------- ----- ---- ------------- -------- ------ -------
17m 17m 1 {kube-proxy minikube} Normal Starting Starting kube-proxy.
17m 17m 1 {kubelet minikube} Normal Starting Starting kubelet.
17m 17m 1 {kubelet minikube} Warning ImageGCFailed unable to find data for container /
17m 17m 1 {kubelet minikube} Normal NodeHasSufficientDisk Node minikube status is now: NodeHasSufficientDisk
17m 17m 1 {kubelet minikube} Normal NodeHasSufficientMemory Node minikube status is now: NodeHasSufficientMemory
17m 17m 1 {kubelet minikube} Normal NodeHasNoDiskPressure Node minikube status is now: NodeHasNoDiskPressure
17m 17m 1 {kubelet minikube} Warning Rebooted Node minikube has been rebooted, boot id: 9305d5d2-11e9-411a-b335-b5aa3d59432eEDIT 2:
cortana@cortana:~$ kubectl get pods
NAME READY STATUS RESTARTS AGE
hdfs-gv0ss 0/1 Completed 0 8h
jupyterhub-master-tt81t 0/1 ContainerCreating 0 8h
metastore-1-2-1-4qdnz 0/1 ContainerCreating 0 8h
mysql-master-8ksch 0/1 Completed 0 8h
spark-master-2-0-1-r8g9j 1/1 Running 1 8h
spark-worker-2-0-1-9v45w 0/1 Completed 0 8h
weavescope-app-lkl15 0/1 ContainerCreating 0 8h
weavescope-probe-s5zsd 0/1 ContainerCreating 0 6hThe pods are completed but aren't running except the spark one. How can I run them ?
Similar Questions
1 Answer
The problem is that ReplicationControllers you are deploying have a node selector:
nodeSelector:
training: "true"A node selector will affect the scheduling of pods. In this case, the scheduler is looking for nodes that have a label called training, with a value of true.
My suspicion is that you do not have a node that has this label. To look at the labels of a given node, you may use kubectl describe node $NODE_NAME. More information on node selectors here.
Edit: As you can see from kubectl's output, your node does not have a label training=true. The node has the labels:
Name: minikube
Role:
Labels: beta.kubernetes.io/arch=amd64
beta.kubernetes.io/os=linux
kubernetes.io/hostname=minikubeFor this reason, there is no suitable node where to deploy your workloads. If you want to label the node, you can kubectl label node minikube training=true.