Steps i have done :
I have two namespaces one with istio injected and another not
Now deploy simple nginx server using this yaml in both namespace
apiVersion: v1
kind: Service
metadata:
name: software-upgrader
labels:
app: software-upgrader
service: software-upgrader
spec:
ports:
- name: http
port: 25301
selector:
app: software-upgrader
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: software-upgrader
spec:
selector:
matchLabels:
app: software-upgrader
version: v1
template:
metadata:
labels:
app: software-upgrader
version: v1
spec:
containers:
- image: gcr.io/mesh7-public-images/scalability/nginx
imagePullPolicy: IfNotPresent
name: software-upgrader
resources:
limits:
cpu: 20m
memory: 32Mi
requests:
cpu: 20m
memory: 32Mi
now deploy HTTPS servers in both namespaces by this steps Steps to deploy HTTPS server
now curl it from another pod in both namespace
The Pod with istio not injected would get 200 OK , while istio-injected pod would get
curl: (56) OpenSSL SSL_read: error:1409445C:SSL routines:ssl3_read_bytes:tlsv13 alert certificate required, errno 0
command terminated with exit code 56
Pardon me of my ignorance do i have to create some Service-entry or Virtual Service for HTTPS to happen between Pods in same namespace to happen if istio is injected?
You have to add Protocol to Service port Definition
apiVersion: v1
kind: Service
metadata:
name: test-https-server
labels:
app: test-https-server
service: test-https-server
spec:
ports:
- name: test-https
port: 25302
appProtocol: https
selector:
app: test-https-server
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: test-https-server
spec:
selector:
matchLabels:
app: test-https-server
template:
metadata:
labels:
app: test-https-server
spec:
containers:
- image: gcr.io/mesh7-public-images/scalability/nginx
command: ["bash", "-c", "python3 ThreadedHTTPSServer.py 25302"]
imagePullPolicy: Always
name: test-https-server
resources:
limits:
cpu: 20m
memory: 32Mi
requests:
cpu: 20m
memory: 32Mi
This has a example of working example
ports:
- name: http
port: 25302
appProtocol: https # Should Specify Protocol
Istio appProtocol configuration doc
Related
I'm a beginner with Kubernetes and YAML.
I've been trying to deploy a ReplicaSet with YAML.
This is the file for the ReplicaSet:
apiVersion: apps/v1
kind: ReplicaSet
metadata:
name: myapp-replicaset
label:
app: myapp
spec:
selector:
matchlabels:
env: production
name: nginx
replicas: 3
template:
metadata:
name: nginx
labels:
env: production
name: nginx
spec:
containers:
- name: nginx
image: nginx
resources:
limits:
memory: "128Mi"
cpu: "500m"
ports:
- containerPort: 80
And this is the Pod file:
apiVersion: v1
kind: Pod
metadata:
name: nginx
labels:
env: production
name: nginx
spec:
containers:
- name: nginx
image: nginx
resources:
limits:
memory: "128Mi"
cpu: "500m"
ports:
- containerPort: 80
However, when I execute the kubectl create -f replicaset.yml command, I get the following error:
The ReplicaSet "myapp-replicaset" is invalid:
spec.selector: Invalid value: v1.LabelSelector{MatchLabels:map[string]string(nil), MatchExpressions:[]v1.LabelSelectorRequirement(nil)}: empty selector is invalid for deployment
spec.template.spec.containers: Required value
Your replicaset.yaml indentation seems to be wrong + with some typos.
replicas & template should be inside the spec level. Also, check the marked & corrected typos in labels & matchLabels.
apiVersion: apps/v1
kind: ReplicaSet
metadata:
name: myapp-replicaset
labels: # labels
app: myapp
spec:
selector:
matchLabels: # matchLabels
env: production
name: nginx
replicas: 3
template:
metadata:
name: nginx
labels:
env: production
name: nginx
spec:
containers:
- name: nginx
image: nginx
resources:
limits:
memory: "128Mi"
cpu: "500m"
ports:
- containerPort: 80
I'm new with Prometheus and I have simple flask app in Kubernetes cluster also I have Prometheus-Monitoring-Grafana services in cluster too in namespace calles prometheus-monitoring. But the problem is when I create ServiceMonitor via .yaml file to connect my app to monitor with Prometheus I see that targets is not added but in config i see that job was added. But status in Prometheus - Service Discovery is Dropped.
A have no idea why my service is not connect to serviceMonitor
serviceMonitor/default/monitoring-webapp/0 (0 / 2 active targets)
app.py
app = Flask(__name__)
metrics = PrometheusMetrics(app)
#app.route('/api')
def index():
return 'ok'
deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: webapp-deployment
labels:
app: webapp
spec:
replicas: 1
selector:
matchLabels:
app: webapp
template:
metadata:
labels:
app: webapp
spec:
containers:
- name: webapp
image: dmitriy83/flask_one:latest
imagePullPolicy: Always
resources:
requests:
memory: "64Mi"
cpu: "250m"
limits:
memory: "128Mi"
cpu: "500m"
ports:
- containerPort: 5000
env:
- name: flask_url
value: http://flasktwo-service:5003
imagePullSecrets:
- name: dockersecret
---
apiVersion: v1
kind: Service
metadata:
name: webapp-service
spec:
selector:
app: webapp
ports:
- name: service
protocol: TCP
port: 5000
targetPort: 5000
---
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: monitoring-webapp
labels:
release: prometheus-monitoring
app: webapp
spec:
endpoints:
- path: /metrics
port: service
targetPort: 5000
namespaceSelector:
matchNames:
- default
selector:
matchLabels:
app: webapp
Finally i figured it out. The issue was port name. Please find workable solution below
deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: webapp
labels:
component: backend
instance: app
name: containers-my-app
namespace: default
spec:
selector:
matchLabels:
component: backend
instance: app
name: containers-my-app
template:
metadata:
labels:
component: backend
instance: app
name: containers-my-app
spec:
containers:
- name: app
image: dmitriy83/flask_one:latest
imagePullPolicy: IfNotPresent
ports:
- containerPort: 5000
name: webapp
imagePullSecrets:
- name: myregistrykey
service.yaml
apiVersion: v1
kind: Service
metadata:
name: webapp
labels:
component: backend
instance: app
name: containers-my-app
namespace: default
spec:
type: ClusterIP
ports:
- name: http
port: 5000
protocol: TCP
targetPort: webapp # one of the major thing w/o it you could not have active targets in Prometheus
selector:
component: backend
instance: app
name: containers-my-app
finally monitor.yaml
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: webapp-super
labels:
component: backend
instance: app
name: containers-my-app
release: kube-prometheus-stack # You need to verify what is your realease name pf prometheus
namespace: prometheus-monitoring # choose in what name space your prometheus is
spec:
namespaceSelector:
matchNames:
- default
selector:
matchLabels:
component: backend
instance: app
name: containers-my-app
endpoints:
- port: http # http - is a port name which was put in service.yaml
I have created a kubernetes project in visual studio 2019, with the default template. This template creates a WeatherForecast controller.
After that I have published it to my ARC.
I used this command to create the AKS:
az aks create -n $MYAKS -g $MYRG --generate-ssh-keys --z 1 -s Standard_B2s --attach-acr /subscriptions/mysubscriptionguid/resourcegroups/$MYRG/providers/Microsoft.ContainerRegistry/registries/$MYACR
And I enabled HTTP application routing via the azure portal.
I have deployed it to azure kubernetes (Standard_B2s), with the following deployment.yaml:
# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: kubernetes1-deployment
labels:
app: kubernetes1-deployment
spec:
replicas: 2
selector:
matchLabels:
app: kubernetes1
template:
metadata:
labels:
app: kubernetes1
spec:
containers:
- name: kubernetes1
image: mycontainername.azurecr.io/kubernetes1:latest
ports:
- containerPort: 80
service.yaml:
#service.yaml
apiVersion: v1
kind: Service
metadata:
name: kubernetes1
spec:
type: ClusterIP
selector:
app: kubernetes1
ports:
- port: 80 # SERVICE exposed port
name: http # SERVICE port name
protocol: TCP # The protocol the SERVICE will listen to
targetPort: http # Port to forward to in the POD
ingress.yaml:
#ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: kubernetes1
annotations:
kubernetes.io/ingress.class: addon-http-application-routing
spec:
rules:
- host: kubernetes1.<uuid (removed for this post)>.westeurope.aksapp.io # Which host is allowed to enter the cluster
http:
paths:
- backend: # How the ingress will handle the requests
service:
name: kubernetes1 # Which service the request will be forwarded to
port:
name: http # Which port in that service
path: / # Which path is this rule referring to
pathType: Prefix # See more at https://kubernetes.io/docs/concepts/services-networking/ingress/#path-types
But when I go to kubernetes1..westeurope.aksapp.io or kubernetes1..westeurope.aksapp.io/WeatherForecast I get the following error:
503 Service Temporarily Unavailable
nginx/1.15.3
It's working now. For other people who have the same problem. I have updated my deployment config from:
# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: kubernetes1-deployment
labels:
app: kubernetes1-deployment
spec:
replicas: 2
selector:
matchLabels:
app: kubernetes1
template:
metadata:
labels:
app: kubernetes1
spec:
containers:
- name: kubernetes1
image: mycontainername.azurecr.io/kubernetes1:latest
ports:
- containerPort: 80
to:
# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: kubernetes1
spec:
selector: # Define the wrapping strategy
matchLabels: # Match all pods with the defined labels
app: kubernetes1 # Labels follow the `name: value` template
template: # This is the template of the pod inside the deployment
metadata:
labels:
app: kubernetes1
spec:
nodeSelector:
kubernetes.io/os: linux
containers:
- image: mycontainername.azurecr.io/kubernetes1:latest
name: kubernetes1
resources:
requests:
cpu: 100m
memory: 128Mi
limits:
cpu: 250m
memory: 256Mi
ports:
- containerPort: 80
name: http
I don't know exactly which line solved the problem. Feel free to comment it if you know which line the problem was.
I have a Kubernetes cluster with 1 control-plane and 1 worker, the worker has in it 3 pods. The pods and service with Type: NodePort are on the same node. I was expecting the service to load balance the requests between the pods but looks like all the requests are always getting forwarded to only one pod.
apiVersion: v1
kind: Service
metadata:
name: web-svc
spec:
type: NodePort
ports:
- port: 80
targetPort: 80
nodePort: 30002
selector:
app: web
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: web-app
labels:
app: web
spec:
selector:
matchLabels:
app: web
replicas: 3
template:
metadata:
labels:
app: web
spec:
containers:
- name: web-app
image: webimage
ports:
- containerPort: 80
imagePullPolicy: Never
resources:
limits:
cpu: "0.5"
requests:
cpu: "0.5"
~
This is expected behavior if your requests have persistent TCP connection. Try adding "connection":"close" in your HTTP header.
in my env file for my angular frontend I have the API endpoint set as localhost:8000 because my API listens on that port, but it is in a separate pod is this correct or am I meant to use the name I gave to the backend service in the deployment file. Second, how do I connect the backend service is how I have it done in the deployment file below correct?
apiVersion: apps/v1
kind: Deployment
metadata:
name: ai-api
spec:
replicas: 1
selector:
matchLabels:
app: ai-api
template:
metadata:
labels:
app: ai-api
spec:
nodeSelector:
"beta.kubernetes.io/os": linux
containers:
- name: ai-api
image: test.azurecr.io/api:v5
resources:
requests:
cpu: 100m
memory: 128Mi
limits:
cpu: 250m
memory: 256Mi
ports:
- containerPort: 8000
name: ai-api
---
apiVersion: v1
kind: Service
metadata:
name: ai-api
spec:
ports:
- port: 8000
selector:
app: ai-api
---
# Frontend
apiVersion: apps/v1
kind: Deployment
metadata:
name: ai-front
spec:
replicas: 1
selector:
matchLabels:
app: ai-front
template:
metadata:
labels:
app: ai-front
spec:
nodeSelector:
"beta.kubernetes.io/os": linux
containers:
- name: ai-front
image: test.azurecr.io/front-end:v5.1
resources:
requests:
cpu: 100m
memory: 128Mi
limits:
cpu: 250m
memory: 256Mi
ports:
- containerPort: 80
env:
- name: api
value: "ai-api"
---
apiVersion: v1
kind: Service
metadata:
name: ai-front
spec:
type: LoadBalancer
ports:
- port: 80
#Tells loadbalancer which deployment to use
selector:
app: ai-front
You mentioned that you have API endpoint set as localhost:8000 for your frontend which is not correct as localhost is referring to the same pod from which the request is send from (so it means "connect to myself"). Change it to ai-api:8000. And also make sure that your api server is listening on 0.0.0.0:8000 and not on localhost:8000.
I also see that you are passing the name of your backend service to the frontend pod:
env:
- name: api
value: "ai-api"
and if you are using this env to connect to your backend app it would stand in contradiction with your earlier statement that you are connecting to localhost:8000.