Blog
Kubernetes
DevOps
Platform Engineering
2
minutes

A Quick Technical Guide to Automating Kubernetes Deployments

Get a quick technical guide to automating Kubernetes deployments. Learn to use kubectl and YAML for consistent application setup, updates, and rollbacks in your cluster.
October 14, 2025
Morgan Perry
Co-founder
Summary
Twitter icon
linkedin icon

Automating Kubernetes deployments streamlines your development workflows and ensures consistency across environments.

This guide focuses on using native Kubernetes tools such as kubectl and YAML configuration files to automate your deployment processes.

Prerequisites

  • A working Kubernetes cluster
  • kubectl command-line tool installed
  • Basic understanding of Kubernetes concepts and YAML syntax

Step 1: Creating a Deployment YAML File

Start by creating a YAML file for your deployment. This file will define the desired state of your application in the Kubernetes cluster. Here’s a simple example of a YAML file for deploying a basic nginx container:

apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx-deployment
spec:
replicas: 3
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx

This configuration creates a deployment named nginx-deployment, starting three replicas of the nginx container.

Step 2: Deploying with kubectl

To deploy the application to your Kubernetes cluster, run the following command:

kubectl apply -f nginx-deployment.yaml

This command instructs Kubernetes to set up the deployment as described in your YAML file.

Step 3: Automating Deployment Updates and Testing Automation

Automate with CI/CD Pipeline: Configure a CI/CD pipeline (e.g., Jenkins, GitLab CI, GitHub Actions) to automatically run kubectl apply -f <configuration-file>.yaml whenever changes are pushed to the main branch. Here is an example using GitLab CI:

deploy:
stage: deploy
script:
- kubectl apply -f nginx-deployment.yaml
only:
- main

Step 4:Testing the Automation

  • Make a change (e.g., update the nginx image version in the YAML file).
  • Commit and push the change; watch the CI/CD pipeline trigger and update the deployment.
  • Verify updates using kubectl rollout status deployment/nginx-deployment.
  • Optionally, test rollback by deploying a faulty configuration and then executing kubectl rollout undo deployment/nginx-deployment.

Step 5: Verifying the Deployment

After deploying, verify the status of your deployment with:

kubectl get deployments

This command provides details about the current deployments, including their desired and actual states.

Ready to Streamline Your Deployments?

For a deeper dive into how these and other tools can transform your CI/CD pipelines, read our Kubernetes automation tools article here.

Share on :
Twitter icon
linkedin icon
Tired of fighting your Kubernetes platform?
Qovery provides a unified Kubernetes control plane for cluster provisioning, security, and deployments - giving you an enterprise-grade platform without the DIY overhead.
See it in action

Suggested articles

Kubernetes
8
 minutes
Kubernetes management in 2026: mastering Day-2 ops with agentic control

The cluster coming up is the easy part. What catches teams off guard is what happens six months later: certificates expire without a single alert, node pools run at 40% over-provisioned because nobody revisited the initial resource requests, and a manual kubectl patch applied during a 2am incident is now permanent state. Agentic control planes enforce declared state continuously. Monitoring tools just report the problem.

Mélanie Dallé
Senior Marketing Manager
Kubernetes
6
 minutes
Kubernetes observability at scale: how to cut APM costs without losing visibility

The instinct when setting up Kubernetes observability is to instrument everything and send it all to your APM vendor. That works fine at ten nodes. At a hundred, the bill becomes a board-level conversation. The less obvious problem is the fix most teams reach for: aggressive sampling. That is how intermittent failures affecting 1% of requests disappear from your monitoring entirely.

Mélanie Dallé
Senior Marketing Manager
Kubernetes
 minutes
How to automate environment sleeping and stop paying for idle Kubernetes resources

Scaling your deployments to zero is only half the battle. If your cluster autoscaler does not aggressively bin-pack and terminate the underlying worker nodes, you are still paying for idle metal. True environment sleeping requires tight integration between your ingress layer and your node provisioner to actually realize FinOps savings.

Mélanie Dallé
Senior Marketing Manager
Kubernetes
DevOps
6
 minutes
10 best Kubernetes management tools for enterprise fleets in 2026

The structure, table, tool list, and code blocks are all worth keeping. The main work is fixing AI-isms in the prose, updating the case study to real metrics, correcting the FAQ format, and replacing the CTAs with the proper HTML blocks. The tool descriptions need the "Core strengths / Potential weaknesses" headers made less template-y, and the intro needs a sharper human voice.

Mélanie Dallé
Senior Marketing Manager
DevOps
Kubernetes
Platform Engineering
6
 minutes
10 best Red Hat OpenShift alternatives to reduce licensing costs

For years, Red Hat OpenShift has been the safe choice for heavily regulated, on-premise environments. It operates as a secure fortress. But in the public cloud, that fortress acts as an expensive prison. Paying proprietary per-core licensing fees on top of your standard AWS or GCP compute bill is a redundant "middleware tax." Escaping OpenShift requires decoupling your infrastructure from your developer experience by running standard, vanilla Kubernetes paired with an agentic control plane.

Morgan Perry
Co-founder
AI
Product
3
 minutes
Qovery Skill for AI Agents: Deploy Apps in One Prompt

Use Qovery from Claude Code, OpenCode, Codex, and 20+ AI Coding agents

Romaric Philogène
CEO & Co-founder
Kubernetes
 minutes
Stopping Kubernetes cloud waste: agentic automation for enterprise fleets

Agentic Kubernetes resource reclamation is the practice of using an autonomous control plane to continuously identify, suspend, and delete idle infrastructure across a multi-cloud Kubernetes fleet. It replaces manual cleanup and reactive autoscaling with intent-based policies that act on business state, eliminating the configuration drift and cloud waste typical of unmanaged fleets.

Mélanie Dallé
Senior Marketing Manager
Platform Engineering
Kubernetes
DevOps
10
 minutes
What is Kubernetes? The reality of Day-2 enterprise fleet orchestration

Kubernetes focuses on container orchestration, but the reality on the ground is far less forgiving. Provisioning a single cluster is a trivial Day-1 exercise. The true operational nightmare begins on Day 2. Teams that treat multi-cloud fleets like isolated pets inevitably face crushing YAML configuration drift, runaway AWS bills, and severe scaling bottlenecks.

Morgan Perry
Co-founder

It’s time to change
the way you manage K8s

Turn Kubernetes into your strategic advantage with Qovery, automating the heavy lifting while you stay in control.