Future-Proofing My Career: Why I\'m Learning DevOps and Automation

Alejandro Arciniegas

nov 15, 2024

"Will AI replace developers?"

It's the question that keeps many of us up at night. While I don't think AI will completely replace developers anytime soon, I can't ignore the writing on the wall: coding is becoming more accessible, and the nature of software development is changing rapidly.

GitHub Copilot writes functions for me. ChatGPT debugs my code. No-code platforms let non-developers build complex applications. Even my non-technical friends are creating websites and automating workflows without writing a single line of code.

So what's a developer to do? Double down on coding skills, or pivot toward something else?

After months of reflection and experimentation, I've decided to bet heavily on DevOps and automation. Let me share why I think this is the right move, and how I'm making the transition.

The Changing Landscape of Software Development

First, let's acknowledge what's actually happening:

1. AI is Democratizing Code Writing

// What I used to spend 30 minutes writing:
function debounce(func, delay) {
  let timeoutId;
  return function (...args) {
    clearTimeout(timeoutId);
    timeoutId = setTimeout(() => func.apply(this, args), delay);
  };
}

// Now I just type a comment and Copilot completes it:
// Create a debounce function that delays execution
// [Tab] -> Complete function appears

2. No-Code/Low-Code is Getting Sophisticated

  • Webflow: Designers are building production websites
  • Zapier: Business users are creating complex workflows
  • Bubble: Non-developers are building full applications
  • Airtable: Database applications without SQL

3. Frameworks are Getting Simpler

Modern frameworks handle more of the complexity:

// Old way - lots of boilerplate
class Component extends React.Component {
  constructor(props) {
    super(props);
    this.state = { count: 0 };
  }
  
  render() {
    return <div>{this.state.count}</div>;
  }
}

// New way - much simpler
function Component() {
  const [count, setCount] = useState(0);
  return <div>{count}</div>;
}

4. The Complexity is Moving Up the Stack

While individual components are getting easier to build, the overall systems are becoming more complex:

  • Microservices architectures
  • Container orchestration
  • Cloud-native deployments
  • Distributed systems
  • Monitoring and observability

Why DevOps and Automation?

As I looked at these trends, I realized something important: the value is shifting from writing code to orchestrating systems.

1. Systems Are Getting More Complex

# Modern application deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      containers:
      - name: app
        image: my-app:latest
        ports:
        - containerPort: 8080
        env:
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef:
              name: db-secret
              key: url

Someone needs to understand how all these pieces fit together.

2. The DevOps Skills Gap is Real

Every company is adopting cloud-native practices, but there aren't enough people who understand:

  • Container orchestration (Kubernetes)
  • Infrastructure as Code (Terraform)
  • CI/CD pipelines
  • Monitoring and alerting
  • Security and compliance

3. DevOps is Hard to Automate (For Now)

While AI can write functions, it can't yet:

  • Design resilient architectures
  • Debug complex distributed systems
  • Make infrastructure trade-offs
  • Handle security and compliance requirements

4. It's About Problems, Not Code

DevOps is fundamentally about solving problems:

  • How do we deploy safely?
  • How do we scale efficiently?
  • How do we monitor effectively?
  • How do we recover quickly?

These are strategic questions that require human judgment.

My Learning Journey

Here's how I'm approaching this transition:

Phase 1: Foundation Building (Months 1-3)

I started with the basics:

# Learning Docker fundamentals
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
EXPOSE 3000
CMD ["npm", "start"]

What I focused on:

  • Docker containers and images
  • Basic Linux administration
  • Cloud providers (AWS, GCP)
  • Command line tools and scripting

Phase 2: Infrastructure as Code (Months 4-6)

# Learning Terraform
resource "aws_instance" "web" {
  ami           = data.aws_ami.ubuntu.id
  instance_type = "t3.micro"
  
  tags = {
    Name = "web-server"
    Environment = "production"
  }
}

resource "aws_security_group" "web" {
  name_prefix = "web-"
  
  ingress {
    from_port   = 80
    to_port     = 80
    protocol    = "tcp"
    cidr_blocks = ["0.0.0.0/0"]
  }
}

What I learned:

  • Infrastructure as Code with Terraform
  • Cloud networking and security
  • Database management and backups
  • Monitoring and logging

Phase 3: Orchestration and Automation (Months 7-9)

# Learning Kubernetes
apiVersion: v1
kind: Service
metadata:
  name: web-service
spec:
  selector:
    app: web
  ports:
  - protocol: TCP
    port: 80
    targetPort: 8080
  type: LoadBalancer

Current focus:

  • Kubernetes orchestration
  • CI/CD pipeline optimization
  • Advanced monitoring and alerting
  • Security and compliance automation

The Skills That Are Paying Off

Here are the DevOps skills that have already proven valuable:

1. Problem Diagnosis

In my current role at Expedia Group working on marketing automation, my DevOps knowledge helps me:

  • Design efficient B2B email workflow systems
  • Set up proper monitoring and alerting
  • Optimize automation pipeline performance
  • Implement scalable infrastructure solutions

2. End-to-End Thinking

// Developer thinking
const handleSubmit = async (data) => {
  const response = await fetch('/api/users', {
    method: 'POST',
    body: JSON.stringify(data)
  });
  return response.json();
};

// DevOps thinking
// - What happens if the API is down?
// - How do we handle retries?
// - How do we monitor this endpoint?
// - What's the error rate threshold?
// - How do we scale if traffic increases?

3. Automation Mindset

I now automatically think about automating repetitive tasks:

#!/bin/bash
# Instead of manual deployments
git pull origin main
docker build -t my-app .
docker stop my-app-container
docker run -d --name my-app-container my-app

4. Security Awareness

DevOps has made me much more security-conscious:

# Proper secrets management
apiVersion: v1
kind: Secret
metadata:
  name: api-secrets
type: Opaque
data:
  api-key: <base64-encoded-key>
  database-url: <base64-encoded-url>

The Intersection: Development + DevOps

The most valuable skill I'm developing is the ability to bridge development and operations:

1. Developer-Friendly DevOps

# Making deployment easy for developers
name: Deploy to Production
on:
  push:
    branches: [main]
    
jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v3
    - name: Deploy to production
      run: |
        # Simple deployment script
        ./deploy.sh production

2. DevOps-Aware Development

// Writing code with operations in mind
const healthCheck = (req, res) => {
  const status = {
    uptime: process.uptime(),
    message: 'OK',
    timestamp: new Date().toISOString(),
    checks: {
      database: checkDatabase(),
      redis: checkRedis(),
      externalApi: checkExternalApi()
    }
  };
  
  res.status(200).json(status);
};

3. Full-Stack Problem Solving

When issues arise, I can troubleshoot across the entire stack:

  • Frontend performance issues
  • API bottlenecks
  • Database query optimization
  • Infrastructure scaling
  • Network configuration

The Challenges I'm Facing

This transition isn't without its difficulties:

1. The Learning Curve is Steep

DevOps involves many interconnected concepts:

# Just to set up a basic Kubernetes cluster
kubectl create cluster
kubectl apply -f deployment.yaml
kubectl apply -f service.yaml
kubectl apply -f ingress.yaml
helm install monitoring prometheus-community/prometheus

2. The Tooling Changes Rapidly

The DevOps ecosystem evolves quickly:

  • Docker → Podman
  • Jenkins → GitHub Actions
  • Prometheus → Grafana
  • Ansible → Terraform

3. Higher Stakes

Unlike frontend bugs that affect user experience, infrastructure issues can take down entire systems.

4. Different Mindset Required

Moving from "make it work" to "make it reliable, scalable, and secure" requires a fundamental shift in thinking.

What I'm Seeing in the Job Market

The demand for DevOps skills is real:

1. Salary Premiums

DevOps engineers often command higher salaries than pure developers:

const salaryTrends = {
  frontendDeveloper: '$70k-$120k',
  backendDeveloper: '$80k-$130k',
  fullStackDeveloper: '$75k-$125k',
  devOpsEngineer: '$90k-$150k',
  cloudArchitect: '$120k-$180k'
};

2. Job Security

Companies are always looking for people who can:

  • Reduce deployment times
  • Improve system reliability
  • Cut infrastructure costs
  • Enhance security posture

3. Strategic Roles

DevOps engineers are involved in architectural decisions, not just implementation.

Practical Advice for Making This Transition

If you're considering a similar move, here's what I'd recommend:

1. Start with Your Current Projects

# Add DevOps to your existing work
# Set up CI/CD for your projects
# Containerize your applications
# Monitor your applications
# Automate your deployments

2. Build Real Infrastructure

Don't just follow tutorials - build real systems:

# Deploy a real application
resource "aws_instance" "app" {
  ami           = "ami-12345678"
  instance_type = "t3.micro"
  
  user_data = file("setup.sh")
  
  tags = {
    Name = "my-real-app"
    Project = "learning-devops"
  }
}

3. Learn the Why, Not Just the How

Understand the problems DevOps solves:

  • Why do we need containers?
  • Why is infrastructure as code important?
  • Why do we need monitoring?
  • Why is security automation crucial?

4. Focus on Business Value

Frame your learning in terms of business outcomes:

  • "I reduced deployment time from 2 hours to 10 minutes"
  • "I improved system uptime from 99.5% to 99.9%"
  • "I cut infrastructure costs by 30%"

The Future I'm Betting On

Here's my prediction for how the industry will evolve:

1. AI Will Handle More Coding

But humans will still need to:

  • Design systems
  • Make architectural decisions
  • Handle edge cases
  • Ensure security and compliance

2. Systems Will Get More Complex

As individual components become easier to build, the challenge will be orchestrating them at scale.

3. The Value Will Be in Integration

The most valuable developers will be those who can make different systems work together seamlessly.

4. Operations Will Be Table Stakes

Every developer will need to understand how their code runs in production.

My Current Focus Areas

Right now, I'm doubling down on:

1. Kubernetes Mastery

# Complex orchestration patterns
apiVersion: argoproj.io/v1alpha1
kind: Rollout
metadata:
  name: my-app
spec:
  replicas: 5
  strategy:
    canary:
      steps:
      - setWeight: 20
      - pause: {duration: 10}
      - setWeight: 40
      - pause: {duration: 10}
      - setWeight: 60
      - pause: {duration: 10}
      - setWeight: 80
      - pause: {duration: 10}

2. Observability

Understanding how to monitor and debug distributed systems.

3. Security Automation

Implementing security controls and compliance checks in CI/CD pipelines.

4. Cost Optimization

Learning how to build efficient, cost-effective infrastructure.

The Bottom Line

I'm not abandoning development - I'm expanding beyond it. The combination of development skills + DevOps knowledge is incredibly powerful.

While AI might make writing individual functions easier, orchestrating complex systems at scale will remain a human skill for the foreseeable future.

The developers who will thrive in the next decade are those who can:

  • Understand business requirements
  • Design system architectures
  • Implement solutions (with AI assistance)
  • Deploy and operate systems reliably
  • Optimize for performance and cost

That's the future I'm building toward. What about you? Are you thinking about expanding your skills beyond pure development? I'd love to hear your thoughts on where the industry is heading.

Currently deep in the DevOps learning journey and always happy to discuss infrastructure, automation, and career strategies. Feel free to reach out via email or connect with me on LinkedIn.