Deploying workloads to AKS in Azure - Step-by-Step Execution

Process Flow - Deploying workloads to AKS

Write Kubernetes YAML manifest

↓

Connect to AKS cluster

↓

Run kubectl apply -f manifest

↓

Kubernetes API receives manifest

↓

Scheduler assigns pods to nodes

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Pods start running workload

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Check pod status and logs

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Workload deployed and accessible

This flow shows how a workload defined in a YAML file is deployed step-by-step to an AKS cluster using kubectl.

Execution Sample

Azure

apiVersion: v1
kind: Pod
metadata:
  name: myapp-pod
spec:
  containers:
  - name: myapp
    image: nginx

This YAML defines a simple pod running an nginx container to be deployed on AKS.

Process Table

Step	Action	Input/Command	Result/State Change
1	Write manifest	YAML pod definition	Pod manifest ready to deploy
2	Connect to AKS	az aks get-credentials	kubectl configured to AKS cluster
3	Deploy workload	kubectl apply -f pod.yaml	API server receives pod manifest
4	Schedule pod	Kubernetes scheduler	Pod assigned to a node
5	Start pod	Kubelet on node	Container starts running nginx
6	Check status	kubectl get pods	Pod status is Running
7	Check logs	kubectl logs myapp-pod	Nginx logs displayed
8	Access workload	curl pod IP or service	Nginx welcome page served
9	Exit	Workload running	Deployment complete and stable

💡 Workload is deployed and running successfully on AKS cluster

Status Tracker

Variable	Start	After Step 3	After Step 4	After Step 5	Final
Pod Manifest	Not created	Created and applied	Scheduled to node	Running container	Running pod
kubectl Context	Not set	Set to AKS cluster	Same	Same	Same
Pod Status	None	Pending	Scheduled	Running	Running

Key Moments - 3 Insights

Why does the pod status show 'Pending' after applying the manifest?

After applying the manifest (Step 3), the pod is created but not yet scheduled to a node. It stays 'Pending' until the scheduler assigns it (Step 4).

What happens if kubectl is not configured to the AKS cluster?

If kubectl context is not set (Step 2), the apply command will fail because it cannot reach the AKS API server to deploy the workload.

How do we verify the workload is running correctly?

By checking pod status (Step 6) and viewing logs (Step 7), we confirm the container is running and serving as expected.

Visual Quiz - 3 Questions

Look at the execution table, what is the pod status immediately after Step 3?

A Pending

B Running

C Succeeded

D Failed

💡 Hint

Check the 'Pod Status' variable in variable_tracker after Step 3

At which step does the pod get assigned to a node?

A Step 2

B Step 4

C Step 3

D Step 5

💡 Hint

Look at the 'Action' column in execution_table for scheduling

If kubectl is not connected to AKS, what will happen at Step 3?

A Pod will be scheduled anyway

B Pod will start running locally

C kubectl apply will fail

D Pod status will be Running

💡 Hint

Refer to key_moments about kubectl context configuration

Concept Snapshot

Deploying workloads to AKS:
- Write Kubernetes YAML manifest (pods, deployments)
- Connect kubectl to AKS cluster (az aks get-credentials)
- Run 'kubectl apply -f manifest.yaml' to deploy
- Kubernetes schedules pods to nodes
- Pods start containers and run workload
- Check status with 'kubectl get pods'
- View logs with 'kubectl logs <pod>'

Full Transcript

To deploy workloads to AKS, first write a Kubernetes YAML manifest describing your pod or deployment. Then connect your kubectl tool to the AKS cluster using 'az aks get-credentials'. Next, deploy the workload by running 'kubectl apply -f' with your manifest file. The Kubernetes API server receives this manifest and creates the pod resource. The scheduler assigns the pod to a node, where the kubelet starts the container. You can check the pod status with 'kubectl get pods' and view logs with 'kubectl logs'. Once the pod is running, your workload is deployed and accessible.