I am trying to run this project configured for AWS cloud deployment in my local cluster environment. In the cloud deployment, it is configured using Kubernetes CLI (kubectl) and kops (a tool to create & manage Kubernetes clusters on public cloud infrastructure) on AWS cloud.
In short, my question is: Is not it possible to run this application in my local 2-node kubernetes cluster for testing (as I do not have AWS cloud)?
In the cloud setup, it has a cluster creating script to create a cluster and after the creation of the cluster, we get the URL of two AWS ELBs, which can be used to interact with two services provided by the cloud loadbalancer (one backend service+ one frontend service).
My problem: As I am trying to run the project on a 2-node kubernetes cluster hosted in my lab. I have set up the cluster using kubeadm instead of native AWS cloud (kops + k8s) as given in the GitHub link. I have modified the script to remove the references to kops and AWS respectively. In this local kubernetes cluster, I have used MetalLB as a loadBalancer for the services.
At the end of script, unlike in AWS cloud deployment, instead of 2 AWS ELB address links which the client can use to interface with the system services, we are getting two public IPs of the physical nodes: xxx.xxx.80.72 and xxx.xxx.12.58 respectively for the two services, provided by the MetalLb loadbalancer (using pre-configured address pool).
As expected all the pods are in running state.
$ kubectl get all -o wide
NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
pod/benchmark-nodes-qccl6 4/4 Running 0 22h xxx.xxx..58 srl1 <none> <none>
pod/benchmark-nodes-s2rqj 4/4 Running 0 22h xxx.xxx.80.72 srl2 <none> <none>
pod/function-nodes-ct7jm 4/4 Running 17 22h xxx.xxx.12.58 srl1 <none> <none>
pod/function-nodes-d5r6w 4/4 Running 7 22h xxx.xxx..80.72 srl2 <none> <none>
pod/management-pod 1/1 Running 0 22h 192.168.120.66 srl1 <none> <none>
pod/memory-nodes-7dhsv 1/1 Running 1 22h xxx.xxx.80.72 srl2 <none> <none>
pod/memory-nodes-v8s2c 1/1 Running 1 22h xxx.xxx.12.58 srl1 <none> <none>
pod/monitoring-pod 1/1 Running 1 22h 192.168.120.84 srl1 <none> <none>
pod/routing-nodes-lc62q 1/1 Running 1 22h xxx.xxx.80.72 srl2 <none> <none>
pod/routing-nodes-xm8n2 1/1 Running 1 22h xxx.xxx.12.58 srl1 <none> <none>
pod/scheduler-nodes-495kj 1/1 Running 0 22h xxx.xxx.80.72 srl2 <none> <none>
pod/scheduler-nodes-pjb9w 1/1 Running 0 22h xxx.xxx.12.58 srl1 <none> <none>
$kubectl get svc -A
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR
service/function-service LoadBalancer 10.108.79.97 xxx.xxx.12.58 5000:32427/TCP,5001:30516/TCP,5002:30830/TCP,5003:31430/TCP,5004:32448/TCP,5005:30177/TCP,5006:30892/TCP 22h role=scheduler
service/kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 20d <none>
service/routing-service LoadBalancer 10.107.63.188 xxx.xxx.80.72 6450:31251/TCP,6451:31374/TCP,6452:30037/TCP,6453:32030/TCP 22h role=routing
However, when I try to connect with the service from a client in the cluster, it is failing to connect to the services. The execution always going into the exception in the if-else condition at _connect method (code given bellow):
At this point can someone please give me some pointers on what might be the issue with connecting the services for this project in my bare-metal 2-node cluster?
def _connect(self):
sckt = self.context.socket(zmq.REQ)
sckt.setsockopt(zmq.RCVTIMEO, 1000)
sckt.connect(self.service_addr % CONNECT_PORT)
sckt.send_string('')
try:
result = sckt.recv_string()
return result
except zmq.ZMQError as e:
if e.errno == zmq.EAGAIN:
return None
else:
raise e
Is not it possible to run this application in my local 2-node kubernetes cluster for testing (as I do not have aws cloud)?
It is not a recommended approach and will not work as expected.
By trying to run this setup on non-AWS environment you are not meeting the Prerequisites:
We assume you are running inside an EC2 linux VM on AWS, where you have Python3 installed (preferably Python3.6 or later -- we have not tested with earlier versions). AWS has default quotas on resources that can be allocated for accounts. The cluster to create in this doc will exceed the default vCPU limit(32) for a regular AWS account. Please make sure this limit is lifted before proceeding.
For learning and testing purposes locally it would be better for you to go by Creating a cluster with kubeadm:
The kubeadm tool is good if you need:
- A simple way for you to try out Kubernetes, possibly for the first time.
- A way for existing users to automate setting up a cluster and test their application.
- A building block in other ecosystem and/or installer tools with a larger scope.