Hands-on LabExpert
Build Workflows with Terraform & Airflow
Assess platform engineers who can fix real Terraform + Airflow issues — not just write tutorials.
Audit, fix, and stabilize a hastily deployed Airflow platform provisioned by Terraform. Resolve IaC defects, correct DAG templates, enforce idempotent execution, and ensure the LocalExecutor configuration for production reliability.
⏱️ 60 min
📝 2 exercises
⭐ 5/5
Eliminate false positives. 100% verified skills.
Real Environment: Terraform, Airflow, Python, Linux CLI, systemd
The Stack
Production-Grade Environment
Terraform
Infrastructure as Code tool used to provision directories, configurations, and deployment scripts for the Airflow platform.
Apache Airflow
Python
Linux
Role Relevancy
How this lab maps to your role
High Match95%
DevOps Engineer
Core
High Match92%
Platform Engineer
Core
High Match85%
Data Engineer
Core
Good Match65%
Site Reliability Engineer
Relevant
Good Match55%
Cloud Engineer
Relevant
Technical Assessment Guide
Technical Assessment (Build Workflows with Terraform & Airflow)
When to use this lab
- ✓Hiring Platform EngineersValidates the ability to audit and fix Terraform provisioning defects, enforce idempotency, and stabilize infrastructure for production use.
- ✓Screening Data EngineersTests proficiency in Airflow DAG debugging, correct template rendering, and data processing pipeline orchestration.
- ✓Assessing Production ReadinessMeasures the candidate's ability to transform a broken, hastily deployed platform into a stable, idempotent, production-grade system.
Skills Evaluated
Terraform WorkflowAirflow DAG DebugSecure OrchestrationIaC Automation
Who is this for?
Built for Both Sides
Corporate
For Recruiters & Hiring Managers
Validate skills with certainty. No more guessing games.
Assess real skills, not quiz answers
Get automated, objective scoring for every candidate
Reduce mis-hires with proof of hands-on ability
Screen faster with ready-to-send lab invitations
Individual
For Professionals & Learners
- Build real portfolio experience, not toy projects
- Practice in safe, real cloud environments
- Earn verifiable credentials to share on LinkedIn
- Stand out in technical interviews with proof of skills
Common Questions
Frequently Asked Questions
What issues does this Terraform + Airflow lab present?
The lab provides a hastily provisioned Airflow platform with known defects: incomplete directory provisioning, wrong script paths in Terraform, incorrect executor configuration, missing file permissions, and non-idempotent provisioning steps.
How long does the Terraform & Airflow lab take?
The lab is designed for 60 minutes. This includes reviewing main.tf, fixing provisioning defects, updating DAG templates, running terraform plan/apply, and validating idempotency.
What level of experience is required?
This lab targets expert-level engineers (L4). You should have strong experience with Terraform, Airflow, Python, and Linux system administration.
How is idempotency validated?
After applying Terraform, running terraform plan again must report 'No changes.' This confirms the infrastructure provisioning is fully repeatable without side effects.
What executor should Airflow use in this lab?
Airflow must be configured to use the LocalExecutor, which supports parallel task execution without requiring an external message queue like Celery.
Is this lab suitable for hiring decisions?
Yes, this lab is built for qualifying senior DevOps, Platform, and Data Engineers. It tests real-world debugging, IaC best practices, and production readiness assessment.
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Copyright © 2026 Scalyz
