The Biggest Mistake I Made as a Junior DevOps Engineer

One of the biggest mistakes I made as a junior DevOps engineer had nothing to do with tools.

It had everything to do with how I thought about systems.

How I Started: Fast Learner, Wrong Focus

When I started my DevOps career, I was a very fast learner. Honestly, I believe that’s an ability God gave me.

I picked things up quickly. We started with AWS, then moved into core Linux tools, networking, and other DevOps fundamentals. I was learning back to back—spending nights researching, losing sleep, just trying to get better.

And technically, it worked.

I could deploy things. I could set up pipelines. I could write Dockerfiles.

But when I started working with real-world systems—not dummy projects, not tutorial apps—real production applications, I noticed a pattern.

A mistake I kept making.

The Mistake That Changed Everything

I didn’t understand the system before deploying it.

Here’s what would happen:

A developer would finish building an application, send me the GitHub repository, and as the DevOps engineer, I’d jump straight into deployment.

The first thing I’d do was write a Dockerfile. Then I’d set up CI/CD. Then I’d start shipping.

I never stopped to think.

• What’s the best way to deploy this application?
• Does this really need containers?
• Should this be serverless instead?
• Should this run on a VM, Kubernetes, or a managed service?
• What are the tradeoffs?

I wasn’t asking those questions.

There was even a time I advised someone to deploy an application on GKE—when Cloud Run would have been the better, simpler, and cheaper choice.

That mistake was expensive.

Why This Happens to Junior Engineers

I know why this happens—especially as a junior DevOps engineer.

You want to be seen.

You want to prove yourself. You want to join a team, take the application from GitHub, deploy it to production, and show that you can deliver.

So you move fast. You execute. You ship.

But speed without understanding creates technical debt.

You over-engineer. You choose complex solutions when simple ones would work better. You pick tools because you know them, not because they’re the right fit.

I was optimizing for looking competent instead of being competent.

The Real Lesson

The biggest lesson I learned is this:

You must understand the system before you deploy it.

Not just “what does this code do?”

But deeper questions:

• Who will use this?
• How many users?
• What’s the expected traffic?
• What happens if it goes down?
• What’s the simplest architecture that meets the requirements?
• What will the team need to maintain this?

The moment you can make core architectural decisions—not just tool decisions—you save your team months, sometimes years, of pain.

What Changed for Me

When I started asking these questions first, everything shifted:

Before:

• Deploy first, understand later
• Choose tools I knew, not tools that fit
• Over-engineer to look impressive

After:

• Understand first, deploy second
• Choose the simplest solution that meets requirements
• Explain my decisions clearly

The impact:

• Fewer production issues
• Better cost efficiency
• More trust from my team
• Faster career growth

DevOps is not about deploying fast. It’s about deploying right.

My Advice to Junior DevOps Engineers

If you’re early in your DevOps career, here’s what I wish someone had told me:

1. Slow Down to Speed Up

Take time to understand before you execute.

Spend 30 minutes understanding the application. It will save you 30 hours of fixing mistakes later.

2. Ask Questions

Before deploying, ask:

• What problem does this solve?
• Who uses it and how often?
• What happens if this goes down?
• What’s the simplest way to deploy this?
• What will maintaining this look like?

These questions matter more than technical skills.

3. Simple > Complex

Don’t use Kubernetes if a managed service works.

Don’t containerize if a VM is sufficient.

Don’t build custom infrastructure if a platform-as-a-service exists.

Your job is solving business problems, not showcasing tools.

4. Learn to Say “We Don’t Need That”

Some of my best technical decisions were saying no to complexity:

• “We don’t need Kubernetes for this.”
• “We don’t need a custom solution for this.”
• “We don’t need to build this from scratch.”

Knowing which tools NOT to use is as important as knowing which ones to use.

5. Understand Cost Implications

Every architectural decision has a cost:

• Financial cost (infrastructure)
• Operational cost (maintenance)
• Complexity cost (debugging, scaling)

Make decisions that balance all three.

6. Think About the Team

Choose solutions your team can actually maintain.

The best architecture isn’t the most advanced—it’s the one your team can operate at 3 AM when something breaks.

If you wouldn’t want to be on-call for it, don’t deploy it.

The Framework I Use Now

Before deploying anything, I answer these questions:

1. What does this application do?

• Purpose and functionality
• Users and expected usage

2. What are the technical requirements?

• Traffic expectations
• Performance needs
• Availability requirements

3. What are the constraints?

• Budget limitations
• Team size and skills
• Timeline

4. What are the simplest options?

• List 3 possible architectures (simple → complex)
• Compare tradeoffs
• Choose the simplest that meets all requirements

5. Can I explain this decision?

• Why this architecture?
• Why not something simpler?
• What are the tradeoffs?

Only after answering these do I start writing infrastructure code.

The Transformation

This shift in thinking transformed my career.

I stopped being the engineer who “deployed things fast.”

I became the engineer who “made smart architectural decisions.”

The difference?

• More responsibility
• More trust from leadership
• Better outcomes for the team
• Faster career progression

All because I learned to understand before I executed.

Final Thought

Speed is valuable. Execution is important.

But understanding is everything.

The moment you prioritize understanding over speed, you stop being a junior engineer and start thinking like a senior engineer.

You save your company money. You reduce technical debt. You make better decisions. You build systems that last.

And that’s when your career takes off.

The Core Principle

DevOps is not about deploying fast.

It’s about deploying right.

Slow down. Ask questions. Understand the system.

That decision alone can change your entire career.

What about you?

Are you deploying before understanding? Are you choosing tools because you know them, not because they fit?

The first step is recognizing the pattern.

I learned this lesson after making expensive mistakes. You can learn it today—before it costs you anything.

Choose understanding over speed. Choose simplicity over complexity. Choose wisdom over ego.

Your future self will thank you.

Conclusion: The Core Principle

The fundamental principle underlying effective DevOps architecture:

Understand the system before you deploy the system.

This principle manifests in several corollary insights:

1. Technical proficiency is necessary but insufficient. Knowing how to use Kubernetes doesn’t mean you should use Kubernetes.
2. Simplicity is sophisticated. The simplest architecture that meets requirements is superior to complex solutions, regardless of technical impressiveness.
3. Context determines correctness. There are no universally correct architectural decisions—only decisions that are appropriate or inappropriate for specific contexts.
4. Documentation creates clarity. Explicit reasoning about architectural choices prevents implicit assumptions and enables organizational learning.
5. Career advancement comes from judgment, not execution. Senior engineers are distinguished by decision-making capability, not tool proficiency.

The DevOps discipline is not about deploying quickly—it’s about deploying appropriately. Speed of execution without quality of thinking creates technical debt, inflates costs, and compromises system reliability.

For early-career DevOps engineers: invest as much time developing architectural judgment as you invest developing technical skills. The former will determine your career trajectory far more than the latter.

The question is not “Can I deploy this to Kubernetes?”

The question is “What is the appropriate architecture for this system’s requirements, constraints, and context?”

Answer that question correctly, and you transform from a capable operator into a strategic technical leader.

Practical Recommendations

For Junior DevOps Engineers

1. Implement a mandatory analysis phase before any deployment
   • Minimum 2 hours of requirements analysis
   • Document findings before writing any infrastructure code
   • Share analysis with senior engineer for feedback
2. Maintain an architecture decision log
   • Brief ADRs for all deployment decisions
   • Review quarterly to identify patterns
   • Use as learning record
3. Study one architectural case study weekly
   • Focus on understanding rationale, not just implementation
   • Compare their context to your context
   • Extract transferable principles
4. Schedule monthly architecture reviews
   • Review deployments from previous month
   • Evaluate decisions with benefit of operational experience
   • Document lessons learned

For Engineering Managers

1. Establish architecture review processes
   • Require ADRs for significant deployments
   • Conduct peer review before production deployment
   • Create culture where asking “why” is expected
2. Create decision-making frameworks
   • Document organizational architectural principles
   • Provide decision matrices for common scenarios
   • Establish cost/complexity budgets
3. Reward architectural thinking
   • Recognize engineers who prevent problems through analysis
   • Promote based on decision quality, not execution speed
   • Include architectural judgment in performance evaluations
4. Invest in architectural education
   • Provide access to architecture courses and resources
   • Create internal architecture review boards
   • Facilitate knowledge sharing from senior engineers

For Organizations

1. Establish architectural governance
   • Define standards for when different approaches are appropriate
   • Create reference architectures for common use cases
   • Implement cost visibility and accountability
2. Measure architectural decisions
   • Track infrastructure costs relative to requirements
   • Monitor operational incident patterns
   • Assess technical debt accumulation
3. Create learning systems
   • Conduct blameless post-mortems on architectural mistakes
   • Share learnings across engineering organization
   • Build institutional knowledge through documentation

Additional Resources

Architecture Frameworks and Patterns

• AWS Well-Architected Framework
• Google Cloud Architecture Framework
• Azure Well-Architected Framework
• The Twelve-Factor App Methodology

Books on System Design and Architecture

• Building Microservices by Sam Newman
• Designing Data-Intensive Applications by Martin Kleppmann
• Site Reliability Engineering by Google
• The DevOps Handbook by Gene Kim et al.
• Fundamentals of Software Architecture by Mark Richards and Neal Ford

Cost Optimization

• AWS Cost Optimization Pillar
• Cloud FinOps Foundation
• Infracost – Infrastructure cost estimation for Terraform

Architecture Decision Records

• ADR GitHub Organization
• Architecture Decision Records Tutorial

About the Author: John Ojabo – DevOps Engineer with 3 years of experience in cloud architecture, infrastructure optimization, and platform engineering. Specializes in cost-effective, operationally sustainable system design.

Last Updated: February 2026

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