> ## Documentation Index
> Fetch the complete documentation index at: https://notes.kodekloud.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Summary

> This lesson explores managing Kubernetes resources declaratively in Azure Kubernetes Service, detailing CI/CD workflows and observability features.

In this lesson, we explore the declarative approach to managing Kubernetes resources in Azure Kubernetes Service (AKS). By adopting declarative configurations, you define *what* your infrastructure should look like, and Kubernetes ensures the cluster’s actual state matches your desired state.

Azure Kubernetes Service supports two primary CI/CD workflow patterns:

| Workflow Type                | Description                                                                                                                  | Trigger Mechanism                                  |
| ---------------------------- | ---------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------- |
| Push-based workflow          | You push code or configuration changes directly to a pipeline, which then builds and deploys artifacts.                      | Manual `git push` or automated CI pipeline trigger |
| Pull-based workflow (GitOps) | A Git repository serves as the single source of truth. A GitOps operator continuously reconciles your cluster with the repo. | Operator polling or webhook-based syncing          |

## Push-based Workflow

With a **push-based** approach, your CI server (Azure DevOps, GitHub Actions, etc.) listens for changes in your application repository. When you commit or merge code, the pipeline:

```yaml theme={null}
# Example GitHub Actions job for AKS deployment
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Build Docker image
        run: docker build -t myregistry.azurecr.io/myapp:${{ github.sha }} .
      - name: Push to ACR
        run: docker push myregistry.azurecr.io/myapp:${{ github.sha }}
      - name: Deploy to AKS
        run: |
          kubectl set image deployment/myapp myapp=myregistry.azurecr.io/myapp:${{ github.sha }}
          kubectl rollout status deployment/myapp
```

<Callout icon="lightbulb" color="#1CB2FE">
  Push-based pipelines are straightforward and give you direct control over each deployment step. They work well if you prefer an explicit trigger model.
</Callout>

## Pull-based Workflow (GitOps)

In a **GitOps** (pull-based) model, you store your Kubernetes manifests alongside application code or in a dedicated Git repo. A GitOps operator (Flux, Argo CD) watches the repo and applies changes automatically:

```yaml theme={null}
# Simplified Flux v2 GitRepository resource
apiVersion: source.toolkit.fluxcd.io/v1beta1
kind: GitRepository
metadata:
  name: aks-config
spec:
  interval: 1m
  url: https://github.com/contoso/aks-config
  branch: main
---
apiVersion: kustomize.toolkit.fluxcd.io/v1beta1
kind: Kustomization
metadata:
  name: apps
spec:
  path: ./apps/prod
  prune: true
  sourceRef:
    kind: GitRepository
    name: aks-config
```

<Callout icon="lightbulb" color="#1CB2FE">
  GitOps ensures that your cluster’s live state automatically converges with the declared Git state. This model enhances auditability, reversibility, and compliance.
</Callout>

Effective observability is critical for running production workloads on AKS. Azure provides:

* **Azure Monitor for Containers**: Collects metrics, logs, and health data for nodes and pods.
* **Azure Log Analytics**: Enables querying of container logs using Kusto Query Language (KQL).
* **Application Insights**: Offers distributed tracing, exception tracking, and performance monitoring for your applications.

| Feature                        | Purpose                                      | Example Query                   |                                     |
| ------------------------------ | -------------------------------------------- | ------------------------------- | ----------------------------------- |
| Container CPU & Memory Metrics | Track resource utilization                   | \`InsightsMetrics               | where Name == "cpuUsageNanoCores"\` |
| Pod Log Collection             | Aggregate stdout/stderr logs from containers | \`ContainerLog                  | where PodName == "myapp"\`          |
| Distributed Tracing            | Monitor service-to-service calls             | View in Application Insights UI |                                     |

Refer to the following resources for more details:

* [Azure Kubernetes Service Documentation](https://docs.microsoft.com/azure/aks/)
* [Azure Monitor for Containers Overview](https://docs.microsoft.com/azure/azure-monitor/containers/)
* [Getting Started with Flux v2 on AKS](https://fluxcd.io/docs/get-started/)

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