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The flight simulator for
production incidents

See how candidates handle outages before something actually breaks.

SRE · DevOps · Platform · Linux Admin · Infrastructure · Data Center
Scenario Simulation
Incident
INC-7234
Severity
SEV-1
State
Active
System
k8s-prod-03
Issue
Pod CrashLoop
Impact
API degraded
Duration
3m 6s
candidate@gpu-node-01
Active
07:12
candidate@gpu-node-01 - parium assessment
# Candidate investigating GPU driver failure
root@gpu-node-01:~$ nvidia-smi
NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver.
 
root@gpu-node-01:~$ lsmod | grep -E 'nvidia|nouveau'
nouveau 2093056 1
 
root@gpu-node-01:~$ modprobe -r nouveau && modprobe nvidia
Loading nvidia driver...
 
root@gpu-node-01:~$ curl -s localhost:8080/health | jq
{ "status": "healthy", "gpus": 2 }
 
# ✓ Incident resolved in 08:42 - 0 hints used

What take-home tests miss

Respect your candidates' time - and your engineers' too.

The take-home test

  • 3-hour time commitment - the best candidates might not find the time
  • Another hour for your team to review each submission
  • Artificial tasks that don't test real incident response
  • Non-deterministic - two reviewers, two different scores
  • Hard to know if LLMs have been used

With Parium

  • 15 minutes. A real broken server. A real terminal.
  • AI analysis reads the session so your team doesn't have to
  • Tests exactly what they'll do on day one: debug production
  • Same scenario, every candidate. Clear pass/fail with data.
  • Built-in paste detection and tab-switch monitoring
  • Full behavioral picture: session replay shows pastes, tab switches, and every command

Up and running in 3 simple steps

Use our ready-made scenarios or let us build custom assessments for your stack.

Step 1
Step 2
Step 3

Tell us what you need

Pick from our ready-made scenarios (GPU debugging, server performance, Kubernetes) or tell us your stack and we'll build custom assessments.

Send to candidates

Share a link. Candidates enter their details and drop straight into a live terminal. No downloads, no accounts, no friction.

Get real insights

See exactly how they debug: time to resolution, commands used, thought process. Make confident hiring decisions backed by data.

Built for serious technical hiring

Everything you need to assess real engineering skills.

Real Terminal Environments

Full Linux containers with production-realistic scenarios. Not a sandbox, a real system to debug.

Time-to-Resolution Tracking

Automatic timing from first command to incident resolution. Compare candidates objectively.

Runbook & Hint System

Real SOPs like your team uses. Track if candidates can follow procedures or need extra guidance.

LLM Detection

Paste event tracking and pattern analysis to flag candidates who might be using AI assistance.

Command History Export

Full session logs with timestamps. Review every step the candidate took to solve the problem.

Multiple Scenarios

GPU drivers, disk space, runaway processes, API configs. Match the assessment to the role.

Scenarios that mirror your production

Each assessment is a carefully crafted incident with realistic logs, configs, and system state. Candidates face the same challenges your team handles in production.

  • Real kernel modules, drivers, and system services
  • Production-accurate log files and error messages
  • Health check endpoints that validate the fix
  • Industry-standard diagnostic tools (dmesg, journalctl, lspci)
Try a Scenario
═══════════════════════════════════════════════
          INCIDENT ALERT - SEV 1
═══════════════════════════════════════════════

INCIDENT ID:  INC-2026-0119-GPU
SEVERITY:     Critical
AFFECTED:     gpu-node-01.neocloud.internal

───────────────────────────────────────────────

GPU compute jobs are failing on gpu-node-01.
The node has 2x NVIDIA A100 80GB GPUs that 
are not being detected by our monitoring.

Impact:  $4.50/hr revenue loss
Queued:  3 customer training jobs

═══════════════════════════════════════════════
              YOUR TASK
═══════════════════════════════════════════════

1. Investigate why nvidia-smi cannot communicate
2. Identify the root cause
3. Restore GPU functionality
4. Verify health check passes

From L1 support to senior SRE

Scenarios matched to every role on your team.

Site Reliability Engineers

Test incident response, system debugging, and production troubleshooting skills with real-world scenarios.

Service Outages Kubernetes GPU Driver Failure Performance Issues

DevOps & Platform Engineers

Assess configuration management, CI/CD pipelines, container orchestration, and infrastructure automation.

API Gateway Config Container Issues CI/CD Pipelines Log Analysis

Data Center Engineers

Evaluate hardware diagnostics, bare metal troubleshooting, and GPU/accelerator management skills.

GPU Diagnostics IPMI/BMC Hardware Failures Driver Conflicts

Linux System Administrators

Test core Linux skills, process management, and filesystem troubleshooting abilities.

Runaway Process Disk Management Service Recovery System Boot

An assessment that respects engineers' time.

No unfamiliar IDEs. No artificial puzzles. Just a terminal and a real incident - the environment they work in every day.

For candidates

  • Finish in under 20 minutes - not days
  • Real tools, real terminal - no unfamiliar IDEs
  • Reflects how your team actually works

For your team

  • Your engineers focus on building, not reviewing take-homes
  • AI-generated analysis - no more subjective scoring
  • Results ready to share with the hiring panel
Passed
Assessment Results
Feb 15, 2025 · 14:32 UTC
Candidate
Sarah Chen
Scenario
GPU Failure
Resolution
07:38
Time Limit
20:00
Commands
14
Hints Used
0
LLM Risk
Low
Outcome
Root cause correctly identified
Production-safe fix applied
Service health verified
Timeline
00:00 Session started
01:12 Checked GPU state
03:44 Identified driver conflict
05:21 Applied fix
07:38 Health check passed
Behaviour
3:44
Time to root cause
High
Confidence
Command Log
00:12 $ nvidia-smi
NVIDIA-SMI has failed - driver not loaded
00:45 $ lsmod | grep nouveau
nouveau 2461696 1
01:12 $ dmesg | grep -i gpu
[10:14:32] NVRM: GPU has fallen off the bus
02:34 $ modprobe -r nouveau
03:44 $ modprobe nvidia
Loading nvidia driver...
05:21 $ nvidia-smi
GPU 0: NVIDIA A100 | 45C | 32W
07:38 $ curl -s localhost:8080/health
{"status":"healthy"}

Common questions

Everything you need to know about how Parium works.

Candidates connect to a real, isolated Linux environment - not a browser simulation or multiple-choice sandbox. Each assessment spins up a fresh system with the incident pre-configured. They get full terminal access with real bash, real logs, and real system tools. It's the same experience as SSH'ing into a production server.

Parium is built for any role that requires hands-on Linux troubleshooting: Site Reliability Engineers (SRE), DevOps Engineers, Platform Engineers, Data Center Technicians, Linux System Administrators, Cloud Engineers, and Infrastructure Engineers. Our scenarios range from L1 support tasks (config errors, disk space) to L4 senior-level incidents (GPU driver conflicts, kernel modules, PCIe issues).

We monitor for patterns that suggest external help - things like leaving the terminal for extended periods, large paste events, and unusual command timing. Suspicious activity gets flagged in the hiring manager report with enough context for you to make an informed judgment. We can't catch everything, but the patterns are usually pretty obvious.

When the candidate clicks "Verify Fix," we run a health check against the scenario's success criteria (e.g., curl the API endpoint, check nvidia-smi output). If it passes, we record their time-to-resolution. The hiring manager gets a full report: every command with timestamps, hints used, suspicious activity flags, and an AI-generated analysis of their troubleshooting approach and methodology.

HackerRank, Codility, and similar platforms test algorithmic coding in sandboxed editors. Parium tests operational skills in real Linux environments. Your SRE candidates don't need to reverse a linked list - they need to figure out why nginx won't start or why the GPU driver isn't loading. We measure how they investigate, not whether they memorised the answer.

Yes. We can build scenarios that mirror your actual production environment - your monitoring tools, your deployment setup, your common failure modes. Whether it's Kubernetes on EKS, GPU clusters with SLURM, or legacy systems with custom daemons, we'll create assessments that test exactly what your team deals with day-to-day. Get in touch to discuss.

Beyond pass/fail, we give you session replay - watch exactly how candidates approached the problem. You'll see every command they ran, when they pasted content (and what they pasted), when they switched tabs, how long they were away, and when they used hints. It's like watching over their shoulder, but asynchronously. You see how they think, not just whether they got the answer.

Consistent by design

Every candidate gets the same scenario, the same environment, the same success criteria. No more "it depends on who reviewed it." Structured evaluation that gives every candidate a fair shot.

Same scenario, every time

No variation between candidates. Everyone faces the same incident with the same tools available.

Objective criteria

Clear pass/fail based on whether the fix works - not on how well someone writes a README or formats their code.

Data-driven decisions

Time-to-resolution, commands used, hints requested. Compare candidates on the metrics that matter.

Get started with Parium

Whether you need a custom scenario for your stack, want to discuss enterprise pricing, or just have questions, we'd love to hear from you.

Request a callback

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