How to Use Blackbox AI for Free in DevOps

DevOps engineers constantly write Dockerfiles, Kubernetes YAMLs, CI/CD pipelines, Terraform scripts, and shell automation. Writing all of this manually takes time and increases the chance of configuration errors.

This is where Blackbox AI becomes useful.

In this blog, we will cover:

1. What Blackbox AI is

2. How to use it for FREE

3. How it helps in Docker, Kubernetes, CI/CD, Terraform

4. Step-by-step DevOps examples

5. Limitations of the free plan

6. Best practices

What is Blackbox AI?

Blackbox AI is an AI-powered coding assistant that helps developers:

1. Generate code from prompts

2. Auto-complete scripts

3. Convert screenshots to code

4. Explain errors

5. Generate configuration files

Unlike general AI chat tools, it is optimized for coding environments like VS Code.

For DevOps engineers, it can generate:

1. Dockerfile

2. docker-compose.yml

3. Kubernetes deployment & service YAML

4. GitHub Actions workflows

5. Jenkins pipelines

6. Terraform infrastructure code

How to Use Blackbox AI for Free

Method 1: VS Code Extension (Recommended)

Step 1: Install Extension

1. Open VS Code

2. Press Ctrl + Shift + X

3. Search: Blackbox AI

4. Install extension

5. Sign in with Google

Free plan includes:

1. Limited AI requests per day

2. Code autocomplete

3. Script generation

Method 2: Website Version

You can also use:👉 https://www.blackbox.ai

Paste your YAML or Dockerfile and ask it to fix or generate configurations.

How Blackbox Helps in DevOps

Let’s see practical examples.

Example 1: Generate Dockerfile for Flask App

Prompt:

Create Dockerfile for Flask app running on port 5000

It generates:

FROM python:3.9
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 5000
CMD ["python", "app.py"]

This saves time and ensures correct base image and structure.

Example 2: Kubernetes Deployment & Service

Prompt:

Create Kubernetes deployment and service yaml for flask app running on port 5000

Output:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: flask-app
spec:
  replicas: 2
  selector:
    matchLabels:
      app: flask-app
  template:
    metadata:
      labels:
        app: flask-app
    spec:
      containers:
      - name: flask-app
        image: flask-demo:latest
        ports:
        - containerPort: 5000
---
apiVersion: v1
kind: Service
metadata:
  name: flask-service
spec:
  type: NodePort
  selector:
    app: flask-app
  ports:
  - port: 80
    targetPort: 5000

Instead of writing YAML manually, you generate it instantly.

Example 3: CI/CD with GitHub Actions

Using GitHub, you can ask:

Prompt:

Create GitHub Actions workflow to build docker image and push to DockerHub

It generates .github/workflows/docker.yml automatically.

Example 4: Terraform for Azure VM

Prompt:

Create terraform script to deploy Ubuntu VM in Azure

You’ll get ready .tf files including:

1. provider

2. resource group

3. virtual machine

4. network interface

   
   

   DevOps Workflow Using Blackbox (Real Scenario)

Let’s say you are building:

Flask App → Docker → Kubernetes → CI/CD

Step 1: Generate Dockerfile

Step 2: Generate Kubernetes YAML

Step 3: Generate CI/CD pipeline

Step 4: Ask it to fix errors

This reduces development time by 60–70%.

Free Plan Limitations

Blackbox free version has:

• Limited daily requests

• Slower response

• No premium AI models

• Rate limiting

If limit is exceeded, you must wait 24 hours.

Best Practices for DevOps Engineers

Do NOT blindly copy-paste generated YAML.

Instead:

• Understand every line

• Validate using docker build

• Validate using kubectl apply --dry-run=client

• Test pipelines in staging

AI should assist, not replace understanding.

Blackbox vs Other Free Tools

Tool	Strength
OpenAI ChatGPT	Explanation + DevOps architecture
Google Gemini	Free AI scripting
GitHub Copilot (trial)	Strong inline autocomplete
Blackbox AI	Dev-focused code generation

If you are on free plan, combining ChatGPT + Blackbox gives best results.

When Should You Use Blackbox?

Use it when:

1. Writing repetitive YAML

2. Creating CI/CD templates

3. Fixing syntax errors

4. Learning new DevOps tools

5. Preparing for DevOps interviews

Avoid using it when:

1. Writing security-sensitive production scripts

2. Handling secrets

3. Deploying without testing

   
   

Is Blackbox Good for DevOps Beginners?

Yes — especially if you are learning:

1. Docker

2. Kubernetes

3. Azure / AWS

4. Jenkins

5. Terraform

It helps you:

1. Learn structure faster

2. Understand configuration patterns

3. Avoid beginner mistakes

But remember — AI accelerates learning only if you verify outputs.

Final Thoughts

Blackbox AI is a powerful free tool for DevOps engineers who want to:

1. Automate code writing

2. Generate infrastructure scripts

3. Build CI/CD pipelines quickly

4. Reduce configuration errors

For beginners, it acts like a DevOps assistant.For professionals, it improves productivity.

However, DevOps success depends on:

1. Strong fundamentals

2. Understanding YAML deeply

3. Knowing Docker networking

4. Understanding Kubernetes architecture

AI is a helper — not a replacement.