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Learn Netris Operations with Kubernetes¶
Intro¶
The Sandbox environment offers a pre-existing 3 node Kubernetes cluster deployed through K3S in HA Mode. To enable user access to the Kubernetes API, a dedicated Netris L4LB service has been created in the Sandbox Controller. Furthermore, this L4LB address serves as K3S_URL environment variable for all nodes within the cluster.
To access the built-in Kubernetes cluster, put the “Kubeconfig” file which you received via the introductory email into your ~/.kube/config or set “KUBECONFIG” environment variable using export KUBECONFIG=~/Downloads/config on your local machine. Afterwards, try to connect to the k8s cluster:
kubectl cluster-info
If your output matches the one below, that means you’ve successfully connected to the Sandbox cluster:
Kubernetes control plane is running at https://api.k8s-sandbox1.netris.io:6443
CoreDNS is running at https://api.k8s-sandbox1.netris.io:6443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy
Metrics-server is running at https://api.k8s-sandbox1.netris.io:6443/api/v1/namespaces/kube-system/services/https:metrics-server:https/proxy
To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.
Install Netris Operator¶
The first step to integrate the Netris Controller with the Kubernetes API is to install the Netris Operator. Installation can be accomplished by installing a regular manifests or a helm chart. For this example we will use the Kubernetes regular manifests:
Install the latest Netris Operator:
kubectl apply -f https://github.com/netrisai/netris-operator/releases/latest/download/netris-operator.yaml
Create credentials secret for Netris Operator:
kubectl -nnetris-operator create secret generic netris-creds \
--from-literal=host='https://sandbox1.netris.io' \
--from-literal=login='demo' --from-literal=password='Your Demo user pass'
Inspect the pod logs and make sure the operator is connected to Netris Controller:
kubectl -nnetris-operator logs -l netris-operator=controller-manager --all-containers -f
Example output demonstrating the successful operation of Netris Operator:
{"level":"info","ts":1629994653.6441543,"logger":"controller","msg":"Starting workers","reconcilerGroup":"k8s.netris.ai","reconcilerKind":"L4LB","controller":"l4lb","worker count":1}
Note
After installing the Netris Operator, your Kubernetes cluster and physical network control planes are connected.
Deploy an Application with an On-Demand Netris Load Balancer¶
In this scenario we will be installing a simple application that requires a network load balancer:
Install the application “Podinfo”:
kubectl apply -k github.com/stefanprodan/podinfo/kustomize
Get the list of pods and services in the default namespace:
kubectl get po,svc
As you can see, the service type is “ClusterIP”:
NAME READY STATUS RESTARTS AGE
pod/podinfo-7cf557d9d7-6gfwx 1/1 Running 0 34s
pod/podinfo-7cf557d9d7-nb2t7 1/1 Running 0 18s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/kubernetes ClusterIP 10.43.0.1 <none> 443/TCP 33m
service/podinfo ClusterIP 10.43.68.103 <none> 9898/TCP,9999/TCP 35s
In order to request access from outside, change the type to “LoadBalancer”:
kubectl patch svc podinfo -p '{"spec":{"type":"LoadBalancer"}}'
Check the services again:
kubectl get svc
Now we can see that the service type has changed to LoadBalancer, and “EXTERNAL-IP” switched to pending state:
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kubernetes ClusterIP 10.43.0.1 <none> 443/TCP 37m
podinfo LoadBalancer 10.43.68.103 <pending> 9898:32486/TCP,9999:30455/TCP 3m45s
Going into the Netris Controller web interface, navigate to Services → L4 Load Balancer, and you may see L4LBs provisioning in real-time. If you do not see the provisioning process it is likely because it already completed. Look for the service with the name “podinfo-xxxxxxxx”
After provisioning has finished, let’s one more time look at service in k8s:
kubectl get svc
You can see that “EXTERNAL-IP” has been injected into Kubernetes:
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
kubernetes ClusterIP 10.43.0.1 <none> 443/TCP 29m
podinfo LoadBalancer 10.43.42.190 45.38.161.13 9898:30771/TCP,9999:30510/TCP 5m14s
Let’s try to curl it (remember to replace the IP below with the IP that has been assigned in the previous command):
curl 45.38.161.13:9898
The application is now accessible directly on the internet:
{
"hostname": "podinfo-7cf557d9d7-6gfwx",
"version": "6.6.0",
"revision": "357009a86331a987811fefc11be1350058da33fc",
"color": "#34577c",
"logo": "https://raw.githubusercontent.com/stefanprodan/podinfo/gh-pages/cuddle_clap.gif",
"message": "greetings from podinfo v6.6.0",
"goos": "linux",
"goarch": "amd64",
"runtime": "go1.21.7",
"num_goroutine": "8",
"num_cpu": "2"
}
As seen, “PodInfo” developers decided to expose 9898 port for HTTP, let’s switch it to 80:
kubectl patch svc podinfo --type='json' -p='[{"op": "replace", "path": "/spec/ports/0/port", "value":80}]'
Wait a few seconds, you can see the provisioning process on the controller:
Curl again, without specifying a port:
curl 45.38.161.13
The output is similar to this:
{
"hostname": "podinfo-7cf557d9d7-6gfwx",
"version": "6.6.0",
"revision": "357009a86331a987811fefc11be1350058da33fc",
"color": "#34577c",
"logo": "https://raw.githubusercontent.com/stefanprodan/podinfo/gh-pages/cuddle_clap.gif",
"message": "greetings from podinfo v6.6.0",
"goos": "linux",
"goarch": "amd64",
"runtime": "go1.21.7",
"num_goroutine": "8",
"num_cpu": "2"
}
You can also verify the application is reachable by putting this IP address directly into your browser.
Milestone 1
Congratulations! You successfully deployed a network load balancer and exposed an application from your cloud to the internet. Time to get yourself an iced coffee.
Using Netris Custom Resources¶
Introduction to Netris Custom Resources¶
In addition to provisioning on-demand network load balancers, Netris Operator can also provide automatic creation of network services based on Kubernetes CRD objects. Let’s take a look at a few common examples:
L4LB Custom Resource¶
In the previous section, when we changed the service type from “ClusterIP” to “LoadBalancer”, Netris Operator detected a new request for a network load balancer, then it created L4LB custom resources. Let’s see them:
kubectl get l4lb
As you can see, there are two L4LB resources, one for each podinfo’s service port:
NAME STATE FRONTEND PORT SITE TENANT STATUS AGE
podinfo-default-5bdf0a53-027d-449f-8896-547e06028c6b-tcp-80 active 45.38.161.13 80/TCP US/NYC Admin OK 7m21s
podinfo-default-5bdf0a53-027d-449f-8896-547e06028c6b-tcp-9999 active 45.38.161.13 9999/TCP US/NYC Admin OK 15m
You can’t edit/delete them, because Netris Operator will recreate them based on what was originally deployed in the service specifications.
Instead, let’s create a new load balancer using the CRD method. This method allows us to create L4 load balancers for services outside of what is being created natively with the Kubernetes service schema. Our new L4LB’s backends will be “srv04-nyc” & “srv05-nyc” on TCP port 80. These servers are already running the Nginx web server, with the hostname present in the index.html file.
Create a yaml file:
cat << EOF > srv04-5-nyc-http.yaml
apiVersion: k8s.netris.ai/v1alpha1
kind: L4LB
metadata:
name: srv04-5-nyc-http
spec:
ownerTenant: Admin
site: US/NYC
state: active
protocol: tcp
frontend:
port: 80
backend:
- 192.168.45.64:80
- 192.168.46.65:80
check:
type: tcp
timeout: 3000
EOF
And apply it:
kubectl apply -f srv04-5-nyc-http.yaml
Inspect the new L4LB resources via kubectl:
kubectl get l4lb
As you can see, provisioning started:
NAME STATE FRONTEND PORT SITE TENANT STATUS AGE
podinfo-default-5bdf0a53-027d-449f-8896-547e06028c6b-tcp-80 active 45.38.161.13 80/TCP US/NYC Admin OK 9m56s
podinfo-default-5bdf0a53-027d-449f-8896-547e06028c6b-tcp-9999 active 45.38.161.13 9999/TCP US/NYC Admin OK 17m
srv04-5-nyc-http active 45.38.161.14 80/TCP US/NYC Admin Provisioning 5s
When provisioning is finished, you should be able to connect to L4LB. Try to curl, using the L4LB frontend address displayed in the above command output:
curl 45.38.161.14
You will see the servers’ hostname in curl output:
SRV04-NYC
You can also inspect the L4LB in the Netris Controller web interface:
V-Net Custom Resource¶
If one of the backend health-checks is marked as unhealthy like in the screenshot above, it means you didn’t create “vnet-customer” V-Net as described in the “Learn by Creating Services” manual. If that’s the case, let’s create it from Kubernetes using the V-Net custom resource.
Let’s create our V-Net manifest:
cat << EOF > vnet-customer.yaml
apiVersion: k8s.netris.ai/v1alpha1
kind: VNet
metadata:
name: vnet-customer
spec:
ownerTenant: Demo
guestTenants: []
vlanId: "46"
sites:
- name: US/NYC
gateways:
- prefix: 192.168.46.1/24
switchPorts:
- name: swp5@sw12-nyc
untagged: "no"
- name: swp5@sw21-nyc
untagged: "no"
EOF
And apply it:
kubectl apply -f vnet-customer.yaml
Let’s check our V-Net resources in Kubernetes:
kubectl get vnet
As you can see, provisioning for our new V-Net has started:
NAME STATE GATEWAYS SITES OWNER STATUS AGE
vnet-customer active 192.168.46.1/24 US/NYC Demo Active 10s
After provisioning has completed, the L4LB’s checks should work for both backend servers, and incoming requests should be balanced between them.
Let’s curl several times to see that:
curl 45.38.161.14
As we can see, the curl request shows the behavior of “round robin” between the backends:
SRV05-NYC
curl 45.38.161.14
SRV05-NYC
curl 45.38.161.14
SRV04-NYC
curl 45.38.161.14
SRV04-NYC
Note
If intermittently the result of the curl command is “Connection timed out”, it is likely that the request went to the srv05-nyc backend, and the “Default ACL Policy” is set to “Deny”. To remedy this, configure an ACL entry that will allow the srv05-nyc server to communicate with external addresses. For step-by-step instruction review the ACL documentation.
BTW, if you already created “vnet-customer” V-Net as described in the “Learn by Creating Services”, you may import that to k8s, by adding resource.k8s.netris.ai/import: "true" annotation in V-Net manifest, the manifest should look like this:
cat << EOF > vnet-customer.yaml
apiVersion: k8s.netris.ai/v1alpha1
kind: VNet
metadata:
name: vnet-customer
annotations:
resource.k8s.netris.ai/import: "true"
spec:
ownerTenant: Demo
guestTenants: []
vlanId: "46"
sites:
- name: US/NYC
gateways:
- prefix: 192.168.46.1/24
switchPorts:
- name: swp5@sw12-nyc
untagged: "no"
- name: swp5@sw21-nyc
untagged: "no"
EOF
Apply it:
kubectl apply -f vnet-customer.yaml
After applying the manifest containing “import” annotation, the V-Net, created from the Netris Controller web interface, will appear in k8s and you will be able to manage it from Kubernetes.
kubectl get vnet
NAME STATE GATEWAYS SITES OWNER STATUS AGE
vnet-customer active 192.168.46.1/24 US/NYC Demo Active 2m
BGP Custom Resource¶
Let’s create a new BGP peer, that is listed in the “Learn by Creating Services”.
Create a yaml file:
cat << EOF > iris-isp2-ipv4-customer.yaml
apiVersion: k8s.netris.ai/v1alpha1
kind: BGP
metadata:
name: iris-isp2-ipv4-customer
spec:
site: US/NYC
hardware: SoftGate2
neighborAs: 65007
transport:
name: swp16@sw02-nyc
vlanId: 1012
localIP: 45.38.161.22/30
remoteIP: 45.38.161.21/30
description: Example BGP to ISP2
prefixListOutbound:
- permit 45.38.161.0/28 le 32
EOF
And apply it:
kubectl apply -f iris-isp2-ipv4-customer.yaml
Check created BGP:
kubectl get bgp
Allow up to 1 minute for both sides of the BGP sessions to come up:
NAME STATE BGP STATE PORT STATE NEIGHBOR AS LOCAL ADDRESS REMOTE ADDRESS AGE
iris-isp2-ipv4-customer enabled Link Up 65007 45.38.161.22/30 45.38.161.21/30 15s
Then check the state again:
kubectl get bgp
The output is similar to this:
NAME STATE BGP STATE PORT STATE NEIGHBOR AS LOCAL ADDRESS REMOTE ADDRESS AGE iris-isp2-ipv4-customer enabled bgp: Established; prefix: 957240; time: 00:04:02 65007 45.38.161.22/30 45.38.161.21/30 2m3s
Feel free to use the import annotation for this BGP if you created it from the Netris Controller web interface previously.
Return to the Netris Controller and navigate to Network → Topology to see the new BGP neighbor you created.
Importing Existing Resources from Netris Controller to Kubernetes¶
You can import any custom resources already created from the Netris Controller to k8s by adding the following annotation:
resource.k8s.netris.ai/import: "true"
Otherwise, if try to apply them without the “import” annotation, the Netris Operator will complain that the resource with such name or specs already exists.
After importing resources to k8s, they will belong to the Netris Operator, and you won’t be able to edit/delete them directly from the Netris Controller web interface, because the Netris Operator will put everything back, as declared in the custom resources.
Reclaim Policy¶
There is also one useful annotation. So suppose you want to remove some custom resource from k8s, and want to prevent its deletion from the Netris Controller, for that you can use “reclaimPolicy” annotation:
resource.k8s.netris.ai/reclaimPolicy: "retain"
Just add this annotation in any custom resource while creating it. Or if the custom resource has already been created, change the "delete" value to "retain" for key resource.k8s.netris.ai/reclaimPolicy in the resource annotation. After that, you’ll be able to delete any Netris Custom Resource from Kubernetes, and it won’t be deleted from the Netris Controller.
See also
See all options and examples for Netris Custom Resources here.
Netris Calico CNI Integration¶
Netris Operator can integrate with Calico CNI, in your Sandbox k8s cluster, Calico has already been configured as the CNI, so you can try this integration. It will automatically create BGP peering between cluster nodes and the leaf/TOR switch for each node, then to clean up it will disable Calico Node-to-Node mesh. To understand why you need to configure peering between Kubernetes nodes and the leaf/TOR switch, and why you should disable Node-to-Node mesh, review the Calico docs.
Integration is very simple, you just need to add the annotation in calico’s bgpconfigurations custom resource. Before doing that, let’s see the current state of bgpconfigurations:
kubectl get bgpconfigurations default -o yaml
As we can see, nodeToNodeMeshEnabled is enabled:
apiVersion: projectcalico.org/v3
kind: BGPConfiguration
metadata:
annotations:
...
name: default
...
spec:
nodeToNodeMeshEnabled: true
Let’s enable the “netris-calico” integration:
kubectl annotate bgpconfigurations default manage.k8s.netris.ai/calico='true'
Let’s check our BGP resources in k8s:
kubectl get bgp
Here are our freshly created BGPs, one for each k8s node:
NAME STATE BGP STATE PORT STATE NEIGHBOR AS LOCAL ADDRESS REMOTE ADDRESS AGE
iris-isp2-ipv4-customer enabled bgp: Established; prefix: 957241; time: 00:15:03 65007 45.38.161.22/30 45.38.161.21/30 16m
sandbox-srv06-192.168.110.66 enabled 4230000000 192.168.110.1/24 192.168.110.66/24 37s
sandbox-srv07-192.168.110.67 enabled 4230000001 192.168.110.1/24 192.168.110.67/24 37s
sandbox-srv08-192.168.110.68 enabled 4230000002 192.168.110.1/24 192.168.110.68/24 37s
You might notice that peering neighbor AS is different from Calico’s default 64512. The is because the Netris Operator is setting a particular AS number for each node.
Allow up to 1 minute for the BGP sessions to come up, then check BGP resources again:
kubectl get bgp
As we can see, our BGP peers have become established:
NAME STATE BGP STATE PORT STATE NEIGHBOR AS LOCAL ADDRESS REMOTE ADDRESS AGE
iris-isp2-ipv4-customer enabled bgp: Established; prefix: 957194; time: 00:18:24 65007 45.38.161.22/30 45.38.161.21/30 19m
sandbox-srv06-192.168.110.66 enabled bgp: Established; prefix: 1; time: 00:01:26 N/A 4230000000 192.168.110.1/24 192.168.110.66/24 2m7s
sandbox-srv07-192.168.110.67 enabled bgp: Established; prefix: 1; time: 00:01:26 N/A 4230000001 192.168.110.1/24 192.168.110.67/24 2m7s
sandbox-srv08-192.168.110.68 enabled bgp: Established; prefix: 1; time: 00:01:26 N/A 4230000002 192.168.110.1/24 192.168.110.68/24 2m7s
Now let’s check if nodeToNodeMeshEnabled is still enabled:
kubectl get bgpconfigurations default -o yaml
It is disabled, which means the “netris-calico” integration process is finished:
apiVersion: projectcalico.org/v3
kind: BGPConfiguration
metadata:
annotations:
...
manage.k8s.netris.ai/calico: "true"
...
name: default
...
spec:
nodeToNodeMeshEnabled: false
Note
Netris Operator won’t disable Node-to-Node mesh until all BGP peers of all the nodes in the k8s cluster become established.
Finally, let’s check if our earlier deployed “Podinfo” application is still working when Calico Node-to-Node mesh is disabled:
curl 45.38.161.13
Yes, it works:
{
"hostname": "podinfo-7cf557d9d7-nb2t7",
"version": "6.6.0",
"revision": "357009a86331a987811fefc11be1350058da33fc",
"color": "#34577c",
"logo": "https://raw.githubusercontent.com/stefanprodan/podinfo/gh-pages/cuddle_clap.gif",
"message": "greetings from podinfo v6.6.0",
"goos": "linux",
"goarch": "amd64",
"runtime": "go1.21.7",
"num_goroutine": "8",
"num_cpu": "2"
}
Disabling Netris-Calico Integration¶
To disable “Netris-Calico” integration, delete the annotation from Calico’s bgpconfigurations resource:
kubectl annotate bgpconfigurations default manage.k8s.netris.ai/calico-
or change its value to "false".
Milestone 2
Congratulations on completing Milestone 2!