Gitlab Interview Questions (11+ Questions)
Last Updated: June 8, 2026 • 11 Questions • Real Company Interviews
Prepare for your Gitlab interview with our comprehensive collection of 11+ real interview questions and detailed answers. These questions have been curated from actual Gitlab technical interviews across various roles including DevOps Engineer, Data Engineer, QA Engineer, and more.
Table of Contents
- Recursive Database File Backup (easy)
- Docker Volume Cross-Platform Consistency (easy)
- Remove Last Commit and Discard Changes (easy)
- Node Drain Blocked by PDB (medium) 🔒
- Image Tag Validation with Admission Control (medium) 🔒
- Integration Testing with Docker Compose (medium) 🔒
- Modify Terraform List (medium) 🔒
- Group and Filter with HAVING (medium) 🔒
- Export SQLite Database to Parquet Format with Metadata (hard)
- Extract Email Addresses from Text File Using RegEx (easy)
- INTERSECT for Common Orders (medium) 🔒
Our Gitlab interview questions cover a wide range of technical topics and difficulty levels, from entry-level positions to senior roles. Each question includes detailed explanations and answers to help you understand the concepts and prepare effectively for your interview.
💡 Pro Tips for Gitlab Interviews
- Practice each question and understand the underlying concepts
- Review Gitlab's specific technologies and methodologies
- Prepare follow-up questions and edge cases
- Practice explaining your solutions clearly and concisely
Interview Questions & Answers
1. Recursive Database File Backup
Learn how to recursively back up database files across nested directories using Linux Bash commands. This guide covers scanning directory trees for .db files, creating .bak copies with preserved paths, and maintaining original files, essential for pre-migration safety, disaster recovery preparation, and data protection in DevOps workflows.
2. Docker Volume Cross-Platform Consistency
Enable persistent storage across containerized applications by creating Docker volumes that work consistently across different operating systems and distributions. Write data from Ubuntu containers, read from Alpine containers, verify cross-platform compatibility, and access volume data at /var/lib/docker/volumes/. Essential for multi-container applications, stateful services, database persistence, and building platform-agnostic containerized infrastructure.
3. Remove Last Commit and Discard Changes
Completely remove bad commits and their changes from history for unpushed work. Use hard reset to return repository to previous commit state, discard all changes permanently, and clean up commit history. Essential for fixing accidental commits before pushing, preventing bad code from reaching remote, and maintaining clean local history before sharing with team.
4. Node Drain Blocked by PDB
5. Image Tag Validation with Admission Control
Implement Kubernetes admission control: configure ValidatingWebhookConfiguration for image tag validation, enforce latest-tag policy, and secure cluster deployments.
6. Integration Testing with Docker Compose
Automate integration testing with GitHub Actions and Docker Compose: start multi-service stacks, run health checks, and ensure reliable cleanup on failure.
7. Modify Terraform List
Transforming a Flat Map to a List of Objects in Terraform
When working with Terraform, there are instances where you need to transform data structures to better interface with external systems, such as APIs. One common requirement is converting a flat map into a list of objects. This is particu...
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8. Group and Filter with HAVING
Crafting a SQL Query to Identify Departments with High Average Salaries
Introduction:
When preparing for an SQL interview, a common question revolves around manipulating and extracting data from multiple related tables. A notable example involves using SQL commands to identify departments w...
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9. Export SQLite Database to Parquet Format with Metadata
Extract all tables from an SQLite database, convert each to Parquet format with Snappy compression, and generate a manifest file documenting table relationships and export metadata.
10. Extract Email Addresses from Text File Using RegEx
Use Python regular expressions to extract all email addresses from a log file, remove duplicates, and save unique emails to a text file.
11. INTERSECT for Common Orders
Objective
To solve the problem of finding common orders between two tables, orders and special_orders, you need to write an SQL query that identifies orders that have the same order_id, customer_name, and order_date in both tables. Additionally, the result should be presented in an as...
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