# Understanding Kubernetes: Part 5 -Deployment

<figure><img src="https://miro.medium.com/v2/resize:fit:700/0*rzOAGG62sAbSoW3U" alt="Kubernetes deployment" height="355" width="700"><figcaption></figcaption></figure>

> If you’ve been following our **Kubernetes series 2025**, welcome back! For new readers, check out Part 4: [Understanding Kubernetes: Part 4-ReplicaSets](https://medium.com/@techwithpatil/understanding-kubernetes-part-4-replicasets-a639b6b6c3c8)

## What is a Deployment in Kubernetes? <a href="#id-982a" id="id-982a"></a>

A Deployment in Kubernetes is a resource that manages stateless applications by maintaining a specified number of replicas of a pod. It provides features like rolling updates, rollbacks, and scaling, ensuring high availability and declarative updates for applications. Deployments are ideal for managing applications that require consistent uptime and easy version management.

### For example: <a href="#id-4078" id="id-4078"></a>

If you’re running a web application with multiple instances for high availability, you can use a Deployment to manage these replicas. A Deployment ensures the desired number of pods are always running, and if a pod crashes or a node goes down, Kubernetes automatically replaces the failed pod to maintain the application’s state.

### Deployment Capabilities: <a href="#id-91f7" id="id-91f7"></a>

Deployments handle pod lifecycle management through ReplicaSets, offering:

* **Rolling Updates**: Incrementally update pods without downtime.
* **Rollbacks**: Quickly revert to a previous state if an update fails.
* **Scaling**: Dynamically increase or decrease the number of replicas based on workload demands.
* **Self-healing**: Automatically replace failed pods to maintain the desired state.

### In my previous role: <a href="#d49e" id="d49e"></a>

As a Senior DevOps Engineer, I used Deployments extensively to manage microservices in a Kubernetes environment. For instance, we had a Python-based API with six replicas to ensure high availability. I utilized Deployments to perform rolling updates during new releases, ensuring zero downtime. Once, during a production update, an issue arose due to a misconfigured image. Using the rollback feature of Deployments, I quickly restored the application to its previous stable version, minimizing disruption.

### Here’s a simple YAML for deploying a Deployment: <a href="#id-9915" id="id-9915"></a>

```
apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-service
spec:
  replicas: 6
  selector:
    matchLabels:
      app: api
  template:
    metadata:
      labels:
        app: api
    spec:
      containers:
      - name: api-container
        image: python:3.9
        ports:
        - containerPort: 8000
```

This Deployment ensures six replicas of the API are running and allows seamless updates or scaling, making it an essential component for managing stateless applications in Kubernetes.

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