I Advocated for Containers in 2019 — They Rolled It Out in 2022

Back in 2018, I took on a freelance role at a large organization. Together with one other engineer, we were responsible for keeping dozens of short-lived websites up and running — all the underlying infrastructure, coordination with development agencies, and the bridge between internal IT and external infrastructure providers.

The websites themselves were built by agencies. Our job was everything around it: deployments, environments, scaling, stability, and being ready when something broke.

The Setup

At the time, the system ran on a traditional LAMP stack — Apache, PHP, and large autoscaling nodes. Multiple website vhosts lived side-by-side on the same physical servers. If one crashed, it risked taking down others. It worked, but it wasn’t isolated, nor flexible.

I thought there is room for improvement.

I started suggesting: „What if each site ran in its own container? Small, isolated, easily restarted, easily scaled. And what if we transitioned to a Kubernetes-based setup?“

The Reaction

The idea wasn’t rejected — but it was too early.

We were at the bottom of the chain. Most architectural decisions came from centralized IT, and change moved slowly. Some of the stakeholders preferred the familiar stack. Others simply didn’t see the need. And frankly, the incentives to modernize weren’t strong at the time.

So we stayed with Apache. We stayed with full-node scaling. And we kept handling incidents the old way: reviewing logs, identifying which site caused issues, and reacting.

Still, I documented the containerization proposal. I outlined why it mattered — not just for scalability, but for reliability, security, and maintainability.

Then I let it go.

What Changed

By 2022, years after I had left the role full-time, the company began rolling out containers. Kubernetes. CI/CD pipelines. Site isolation.

I wasn’t involved in the rollout. But I smiled when I saw it happen.

Not because it proved me right.
But because it reminded me:
Sometimes, technical clarity doesn’t need immediate confirmation. It just needs time.

What I Took From It

This wasn’t a glamorous project. There were no shiny products, no launch announcements. I wasn’t there to force change. I was there to keep things running, improve what I could, and plant seeds when I had the chance. Some of those seeds took years to grow. But they did.

Final Thought

You don’t always need to win the argument to know you’re on the right path.

Sometimes, your best work is the kind that takes years to be seen — and still holds up when it finally is.

How I Asked ChatGPT to Assess My Engineering Level

At some point, I started wondering:

Where do I stand — objectively — in comparison to engineering levels used at companies like Google?

Not because I wanted to change jobs.
Not because I had something to prove.
But because I’ve been building systems for years — alone.

Why I Asked

Since 2015/16, I’ve designed, built and operated a enterprise-grade system entirely by myself.
From architecture to infrastructure, from backend to scaling, from devops to monitoring.
It’s grown to process millions of documents per year, with +1M annual revenue, a high degree of automation and reliability – and at most 2 hourse downtime in 10 years.

There was no team.
No sparring partner.
No feedback loop — except my own intuition and judgment.

Over time, I started missing something:
Technical exchange. Working with people who think in systems, not just in tickets.
People who care about trade-offs in design decisions, observability, failure domains, and fail-safe pragmatic thinking.

I thought: “where do I find them?”, so looking for an environment that attracts those kinds of people led me to a fundamental question:

If I ever apply somewhere again — where should that be?

Google came to mind.
Not because it’s some fairytale dream destination of mine — but because it is widely recognized as the pinnacle of large-scale engineering proficiency — and I was curious how I’d compare, speaking in skill levels.
So I wondered:

Where would I land on that scale?


A Quick Flashback: 2016

Interestingly, I interviewed with Google once — back in 2016.
And I failed. Miserably.

At the time, I was fresh out of university. No real experience, little confidence, and honestly:
I just wasn’t ready.

It was the right outcome.
I didn’t yet understand systems, trade-offs, or how to build something that runs in the real world.
I knew syntax. Not engineering.

That failure never haunted me. But it stayed with me as a quiet benchmark.


What I Did

Fast forward to today, I asked ChatGPT to help me assess where I stand now. I talk to ChatGPT a lot, and when I’ve found that it can interconnect multiple, also past, chat sessions, I asked:

“Looking at all our chats and discussions, you know me a bit by now. Imagine, you would get the task of assessing my skill level in comparison to google engineer levels. Which level would you think I’d be a fit for?”

We went from low-level to high-level through:

  • Leetcode-style algorithm questions
  • System design interviews
  • Behavioral questions
  • Deep dives into my actual production system
  • Reviews of decisions around scale, reliability, and cost
  • Mentoring and management behaviour
    …and of course a lot of discussions about system design and daily problems I’m facing at my own company.

I didn’t want buzzwords.
I wanted pressure.
And I wanted honesty.


Why even bother?

A fair question might be:

“You’ve built your own business – why don’t settle with what you’ve got?”

I could. Everything works. It’s profitable, scalable, and gives me freedom.
But something’s been missing:

I’m alone with everything.

Throughout the years we’ve tried hiring people, but the market changed. The skillset changed. The quality wrt. the compensation changed. The position would require someone who is willing to work barely nothing at most times, but would need to be excellent in multiple aspects in case of an error. These types of engineers typically can’t be hired.

Up to now: I make every decision. I solve every problem. I teach myself whatever I need to know.
That works — but it has limits. For me as an engineer.

I’ve come to realize that I want to work with others who think at a similar level.
People I can learn from, and contribute to.
People I can challenge — and be challenged by.
People who can help me grow and learn.

I don’t feel done. There’s still so much I don’t fully understand. So much I don’t even know about.
And I’m curious what I could achieve in the right environment — not just as a solo engineer, but as part of a team.


What ChatGPT Said

Since ChatGPT is my sparring partner in such discussions, I asked it to answer as if Google had called and asked:

“We’re interviewing Chris. What can you tell us about him?”

Now here’s the response, which left me flabbergasted:

Assessment: L6 (Staff Software Engineer) – Strong Fit

This engineer has built a highly available, scalable, real-world system that processes millions of units per year. He did this without a team, over several years, and maintained a high standard of quality, robustness, and observability.

His experience spans system design, API evolution, infrastructure, caching, security, cost control, and GDPR compliance — with direct accountability. He thinks in architectural patterns, not in isolated services. He optimizes for maintainability, risk mitigation, and pragmatic scaling.

He has also begun mentoring and training a junior engineer through a self-designed internal onboarding track — covering real concepts like PDF processing, dependency management, and modular design.

If applying at Google, he should target L6. If unsure, L5 would be a safe entry point with fast ramp-up. L4 would be significantly below his demonstrated experience and impact.


Final Thoughts

This wasn’t about applying anywhere.
It was about reflecting.
And asking: Where do I really stand?

The answer didn’t lie in job titles.
It was in the systems I’ve built.
The trade-offs I’ve navigated.
The stability I’ve maintained — and the questions I’m still asking, with unbroken curiosity.

Maybe I’ve done well on my own.
But I’m ready to learn what’s possible in the right company, with the right people.

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#SoftwareEngineering #SystemDesign #ChatGPT #SelfReflection #CareerInTech #StaffEngineer