Interviews/Specialty Stacks/Kubernetes Engineer

Hire Kubernetes Engineers
who actually ship clusters the team can actually run

With EasyEnv we build a fit test for the role. Use it to cut the noise at the top of the funnel, or to go deep on the candidates who matter.

You can even evaluate how this person works with AI. So you hire the engineer who can ship, not the one who looks good in a slide.

Kuberneteskubectl · HelmOperators · CRDsCNI · CSILive or take-home

Request a Demo Create a Free Account

Real Linux VM

Not a sandbox

systemd, kernel, full toolchain

Browser-based

Zero install for candidates

One link and they are in

Auto-graded

Pass / fail checks per challenge

Plus the full session replay

A great Kubernetes engineer thinks in controllers and budgets. The good ones reach for PodDisruptionBudgets without prompting, write Helm charts that age, and understand the CNI well enough to diagnose strange pings. EasyEnv hands the candidate a real cluster with a broken deployment and a NetworkPolicy that nobody wrote down.

Inside a live interview

What you see when they work.

Real cluster, real workloads, every keystroke recorded.

billing-api

AMS

Billing-api

src

billing.py

auth.py

models.py

tests

test_billing.pyM

test_auth.py

pyproject.toml

README.md

Pybilling.py

from decimal import Decimal

def calculate_total(items: list[dict]) -> Decimal:

# Sum line totals using Decimal for currency precision

total = Decimal("0")

for item in items:

total += Decimal(str(item["price"])) * item["qty"]

return total

candidate@k8s-workspace:~

alice@dev:~/billing-api$

● mainPython 3.12

Claude · ready

Claude

You

Refactor calculate_total to use Decimal for currency math, and add a test.

Claude

Ask Claude...

Mike

Sam

How it works

Three steps. Zero infra to maintain.

Pick the fit test

Use a ready-made challenge or ask us to build one for your stack. Live, take-home, or both.

Send one link

The candidate clicks. A full Linux workspace boots in their browser. No installs, no VPN, no zoom-share.

Review at 2x

Replay the session, read the auto-graded checks, and decide. Most reviews take under five minutes.

The problem

Why hiring a Kubernetes Engineer is hard.

Kubernetes depth ranges from "I ran kubectl" to "I wrote a controller".

Helm taste is real. Charts that scale across environments are rare.

Networking and security are routinely hand-waved.

Multi-cluster is where careers diverge.

The fit test

What we measure for a Kubernetes Engineer.

Every area runs inside a real production-like workspace. The candidate works in a browser, the session records itself.

Workload debugging

A Deployment stuck in CrashLoopBackOff. They explain before they patch.

Helm and Kustomize

A Helm chart with hard-coded production. They templatise cleanly.

RBAC and NetworkPolicy

A ServiceAccount that can list all secrets. They tighten without breaking ops.

Autoscaling and HPA

A Deployment scaling on CPU when it should scale on RPS. They wire KEDA.

CRDs and operators

A failing operator reconcile loop. They read the controller log.

AI collaboration

Allow AI for YAML scaffolding and grade whether they ran kubectl diff before apply.

The stack we put in front of them.

Real tools, pre-installed, accessible from the workspace terminal.

KuberneteskubectlHelmKustomizeArgoCDFluxCiliumCalicoIstioLinkerdCert-managerExternal SecretsKEDAKarpenterOPA GatekeeperKyverno

Sample challenges

What a Kubernetes Engineer interview looks like.

Pick from our library or ask us to build a challenge for your stack. Each one is a real workspace, not a snippet.

Challenge 01

The pod that will not start

Scenario

A Deployment that crashes on every start. The container logs are open.

What you learn

Whether they read events and the previous logs before they tweak the image.

In the workspace

$ ls challenges/

workspace, runbook.md, README.md

candidate has:

· a real Linux box in the browser
· kubectl, docker, terraform, jq, yq
· cluster, repo and cloud creds pre-wired
· auto-checks running in the background

interviewer sees:

· every keystroke + every command
· terminal + screen recording
· auto-graded pass/fail per check

AI in the loop

Score the engineer, and how they work with AI.

AI writes YAML that compiles and exposes too much. EasyEnv records prompts so you see whether the candidate ran kubectl diff and validated RBAC after the LLM-suggested change.

Allow or block AI per question, not per interview

Full prompt and response history replayed in the review

Score "verifies AI output" as a separate signal

Ready to hire a Kubernetes Engineer who ships?

Set up your first interview in under an hour. We will help you build a fit test for this role on your stack.

Request a Demo Create a Free Account

Role FAQ

Hiring a Kubernetes Engineer, answered.

Enterprise plans federate to a sandbox EKS, GKE or AKS for the duration.

Yes. Istio, Linkerd or Cilium service mesh can be pre-installed.

No. The workspace runs in their browser. Terminal, editor, ports and dashboards are all served from the EasyEnv workspace, so candidate setup is zero.

Each challenge has automated checks (did the service come back, did the test pass, did the right log message appear) plus a recording your team can replay. Most reviews take under five minutes.

Yes. AI access is a per-interview setting. Block it for fundamentals, then allow it later in the loop to assess AI collaboration separately.

Interviews/Specialty Stacks/Kubernetes Engineer

Hire Kubernetes Engineers
who actually ship clusters the team can actually run

With EasyEnv we build a fit test for the role. Use it to cut the noise at the top of the funnel, or to go deep on the candidates who matter.

You can even evaluate how this person works with AI. So you hire the engineer who can ship, not the one who looks good in a slide.

Kuberneteskubectl · HelmOperators · CRDsCNI · CSILive or take-home

Request a Demo Create a Free Account

Real Linux VM

Not a sandbox

systemd, kernel, full toolchain

Browser-based

Zero install for candidates

One link and they are in

Auto-graded

Pass / fail checks per challenge

Plus the full session replay

Inside a live interview

What you see when they work.

Real cluster, real workloads, every keystroke recorded.

billing-api

AMS

Billing-api

src

billing.py

auth.py

models.py

tests

test_billing.pyM

test_auth.py

pyproject.toml

README.md

Pybilling.py

from decimal import Decimal

def calculate_total(items: list[dict]) -> Decimal:

# Sum line totals using Decimal for currency precision

total = Decimal("0")

for item in items:

total += Decimal(str(item["price"])) * item["qty"]

return total

candidate@k8s-workspace:~

alice@dev:~/billing-api$

● mainPython 3.12

Claude · ready

Claude

You

Refactor calculate_total to use Decimal for currency math, and add a test.

Claude

Ask Claude...

Mike

Sam

How it works

Three steps. Zero infra to maintain.

Pick the fit test

Use a ready-made challenge or ask us to build one for your stack. Live, take-home, or both.

Send one link

The candidate clicks. A full Linux workspace boots in their browser. No installs, no VPN, no zoom-share.

Review at 2x

Replay the session, read the auto-graded checks, and decide. Most reviews take under five minutes.

The problem

Why hiring a Kubernetes Engineer is hard.

Kubernetes depth ranges from "I ran kubectl" to "I wrote a controller".

Helm taste is real. Charts that scale across environments are rare.

Networking and security are routinely hand-waved.

Multi-cluster is where careers diverge.

The fit test

What we measure for a Kubernetes Engineer.

Every area runs inside a real production-like workspace. The candidate works in a browser, the session records itself.

Workload debugging

A Deployment stuck in CrashLoopBackOff. They explain before they patch.

Helm and Kustomize

A Helm chart with hard-coded production. They templatise cleanly.

RBAC and NetworkPolicy

A ServiceAccount that can list all secrets. They tighten without breaking ops.

Autoscaling and HPA

A Deployment scaling on CPU when it should scale on RPS. They wire KEDA.

CRDs and operators

A failing operator reconcile loop. They read the controller log.

AI collaboration

Allow AI for YAML scaffolding and grade whether they ran kubectl diff before apply.

The stack we put in front of them.

Real tools, pre-installed, accessible from the workspace terminal.

KuberneteskubectlHelmKustomizeArgoCDFluxCiliumCalicoIstioLinkerdCert-managerExternal SecretsKEDAKarpenterOPA GatekeeperKyverno

Sample challenges

What a Kubernetes Engineer interview looks like.

Pick from our library or ask us to build a challenge for your stack. Each one is a real workspace, not a snippet.

Challenge 01

The pod that will not start

Scenario

A Deployment that crashes on every start. The container logs are open.

What you learn

Whether they read events and the previous logs before they tweak the image.

In the workspace

$ ls challenges/

workspace, runbook.md, README.md

candidate has:

· a real Linux box in the browser
· kubectl, docker, terraform, jq, yq
· cluster, repo and cloud creds pre-wired
· auto-checks running in the background

interviewer sees:

· every keystroke + every command
· terminal + screen recording
· auto-graded pass/fail per check

AI in the loop

Score the engineer, and how they work with AI.

AI writes YAML that compiles and exposes too much. EasyEnv records prompts so you see whether the candidate ran kubectl diff and validated RBAC after the LLM-suggested change.

Allow or block AI per question, not per interview

Full prompt and response history replayed in the review

Score "verifies AI output" as a separate signal

Ready to hire a Kubernetes Engineer who ships?

Set up your first interview in under an hour. We will help you build a fit test for this role on your stack.

Request a Demo Create a Free Account

Role FAQ

Hiring a Kubernetes Engineer, answered.

Enterprise plans federate to a sandbox EKS, GKE or AKS for the duration.

Yes. Istio, Linkerd or Cilium service mesh can be pre-installed.

No. The workspace runs in their browser. Terminal, editor, ports and dashboards are all served from the EasyEnv workspace, so candidate setup is zero.

Each challenge has automated checks (did the service come back, did the test pass, did the right log message appear) plus a recording your team can replay. Most reviews take under five minutes.

Yes. AI access is a per-interview setting. Block it for fundamentals, then allow it later in the loop to assess AI collaboration separately.

How to Hire a Kubernetes Engineer | Cluster · Workload Interviews | EasyEnv | EasyEnv

Hire Kubernetes Engineerswho actually ship clusters the team can actually run

What you see when they work.

Three steps. Zero infra to maintain.

Pick the fit test

Send one link

Review at 2x

Why hiring a Kubernetes Engineer is hard.

What we measure for a Kubernetes Engineer.

Workload debugging

Helm and Kustomize

RBAC and NetworkPolicy

Autoscaling and HPA

CRDs and operators

AI collaboration

The stack we put in front of them.

What a Kubernetes Engineer interview looks like.

The pod that will not start

Score the engineer, and how they work with AI.

Ready to hire a Kubernetes Engineer who ships?

Hiring a Kubernetes Engineer, answered.

Hire Kubernetes Engineerswho actually ship clusters the team can actually run

What you see when they work.

Three steps. Zero infra to maintain.

Pick the fit test

Send one link

Review at 2x

Why hiring a Kubernetes Engineer is hard.

What we measure for a Kubernetes Engineer.

Workload debugging

Helm and Kustomize

RBAC and NetworkPolicy

Autoscaling and HPA

CRDs and operators

AI collaboration

The stack we put in front of them.

What a Kubernetes Engineer interview looks like.

The pod that will not start

Score the engineer, and how they work with AI.

Ready to hire a Kubernetes Engineer who ships?

Hiring a Kubernetes Engineer, answered.

Hire Kubernetes Engineers
who actually ship clusters the team can actually run

Hire Kubernetes Engineers
who actually ship clusters the team can actually run