Mumshad Mannambeth's Kubernetes Programming Techniques
Kubernetes Declarative Configuration
LabEx's Kubernetes programming techniques focus on using declarative configuration files to manage Kubernetes resources. This approach promotes infrastructure as code, making it easier to version, test, and deploy Kubernetes applications.
YAML Configuration Files
Kubernetes resources are defined using YAML configuration files. These files describe the desired state of the resources, such as Pods, Deployments, Services, and Volumes.
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-deployment
spec:
replicas: 3
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.14.2
ports:
- containerPort: 80
Kubernetes Object Management
LabEx's Kubernetes programming techniques leverage the kubectl
command-line tool to create, update, and delete Kubernetes resources based on the YAML configuration files.
## Create a Kubernetes resource
kubectl create -f nginx-deployment.yaml
## Update a Kubernetes resource
kubectl apply -f nginx-deployment.yaml
## Delete a Kubernetes resource
kubectl delete -f nginx-deployment.yaml
Kubernetes Imperative Commands
While declarative configuration is the preferred approach, LabEx's Kubernetes programming techniques also cover the use of imperative commands for quick, ad-hoc tasks.
## Create a Kubernetes Pod
kubectl run nginx --image=nginx
## Expose a Kubernetes Service
kubectl expose pod nginx --port=80 --type=LoadBalancer
## Scale a Kubernetes Deployment
kubectl scale deployment nginx-deployment --replicas=5
Kubernetes Resource Management
LabEx's Kubernetes programming techniques include efficient resource management techniques, such as:
- Resource Requests and Limits: Defining resource requests and limits for Pods to ensure optimal resource utilization.
- Horizontal Pod Autoscaling: Automatically scaling the number of Pods based on CPU or memory utilization.
- Vertical Pod Autoscaling: Automatically adjusting the resources allocated to a Pod based on its usage.
apiVersion: v1
kind: Pod
metadata:
name: example-pod
spec:
containers:
- name: example-container
image: example/image:v1
resources:
requests:
cpu: 100m
memory: 128Mi
limits:
cpu: 500m
memory: 512Mi