Homelabs are great. They are a gateway for many into the world of Linux, DevOps, and Platform Engineering. The online community is booming and there is a plethora of information (hullo r/homelab). Homelabs nourish curiosity and tinkering, but there is a misconception that a homelab == employability. While it is certainly a great positive differentiator, I’d like to propose an alternative not as popular: cloud labs.
Cloud labs optimize for employability. If your goal is a Cloud, DevOps, or Platform career, cloud labs are more aligned with modern DevOps hiring signals.
Allow me to elaborate.
If you ask how to break into DevOps or Platform Engineering, you’ll often hear the same advice on repeat, “Build a homelab.”
It’s well-intentioned. It’s historically accurate. It’s also increasingly outdated. Homelabs made sense when infrastructure was primarily self-hosted, virtualization was a core skill, and a deeper sense of hardware knowledge was required to build systems. And don’t get me wrong, scienta ist potentia, knowledge is power. And I’ll be the last person to tell you not to learn. Like the Third Way of DevOps states, embrace a culture a continuous learning and experimentation. That said, seeking a career in DevOps in 2026 isn’t about racking servers under your desk. It’s about building, maintaining, and operating distributed, managed, cloud-native systems.
Unfortunately, the truth about homelabs is that it teaches skills that are more difficult to map to real job requirements or less common in modern production environments. Most companies are not managing bare-metal hypervisors or deploying their own DNS resolver. Instead, they are working towards automating everything in a reproducible manner, configuring IAM boundaries, designing resilient architecture, and of course, managing cost.
When one interviews DevOps or Platform engineers, concerns may be:
- Can you automate and document your work?
- Do you understand the trade-offs and compromises of managed services?
- Are you familiar with different cloud architecture patterns and when to leverage one over the other?
- Is security in the cloud an afterthought or shifted left?
Running some docker containers with Proxmox on an old Thinkpad doesn’t showcase this, however a well-designed cloud environment does.
Cloud labs are more production-like by default. It’ll force you to use IAM, meaning writing policies, setting up roles, taking into consideration the principle of least privilege, etc. Networking can be more complicated. Do you understand what you’re exposing? What is public vs private? And considering employability is closely related to cost and profit, is the engineer cost-aware when running their system in the cloud.
With a cloud lab, you can automatically begin to claim experience with a major CSP, be it AWS, Azure, or GCP. It creates a public, career-relevant portfolio, not a side-project. It can be fully defined in an IaC like Terraform. It can be version-controlled in Github. Architectural diagrams showcase thought and design decisions.
When I recently told someone attempting to break into the field to try out a cloud lab, the first response was: “But cloud is expensive.” Great. Cost is a constraint in every real system. That said, between generous free tiers, tearing down environments, setting budgets and alerts, and designing cost-efficient architecture (which is literally part of the job), you’ll not only have a convincing positive differentiator that highlights experience, but it’ll also cost you almost nothing on a monthly basis at small-scale.
If you love homelabs, keep building, keep sharing. But if you’re looking for a job, build cloud labs. There are plenty of example projects online, plus a wealth of information on well-architected frameworks.
Keep building, keep learning, keep upskilling.
Hard work and perseverance will deliver results.