Most Asked GitLab Interview Questions for DevOps Engineers [2025]

Core Concepts

1. What is the role of GitLab in DevOps workflows?

GitLab is an integrated DevOps platform combining version control, CI/CD pipelines, and collaboration tools, streamlining code management and automation. It uses .gitlab-ci.yml to define pipelines for build, test, and deploy stages, ensuring rapid iteration. In enterprises, GitLab centralizes workflows, supports scalability, and integrates with tools like Kubernetes, enabling efficient management of complex development cycles across global teams.

Explore GitLab basics in trunk-based development.

2. Why do organizations choose GitLab for CI/CD?

• Unified Platform: Combines repo, CI/CD, and monitoring.
• Scalability: Handles large-scale enterprise pipelines.
• Flexibility: YAML-based pipeline customization.
• Security: Built-in SAST, DAST scanning.
• Integrations: Supports Docker, Helm, Terraform.

GitLab reduces tool fragmentation, enhancing efficiency in MNC DevOps environments.

3. When is GitLab CI/CD most effective?

GitLab CI/CD excels in agile environments for automating integration and deployment, ensuring fast feedback on commits. It’s ideal for microservices or cloud-native setups.

Less suited for small projects with minimal automation needs, it shines in complex, distributed systems requiring robust pipeline orchestration.

4. Where is the .gitlab-ci.yml file stored?

The .gitlab-ci.yml file resides in the repository’s root directory, defining pipeline stages, jobs, and scripts. Its placement ensures automatic triggering on commits, with validation via GitLab’s CI Lint tool for error-free execution in enterprise-grade CI/CD workflows.

5. Who manages GitLab repositories in enterprises?

• DevOps Engineers: Configure pipelines and integrations.
• Developers: Manage code commits and branches.
• Security Teams: Enforce access controls and scans.
• Admins: Oversee repository permissions and settings.

Collaborative roles ensure secure and efficient repository management in MNCs.

6. Which components define a GitLab pipeline?

GitLab pipelines consist of stages (e.g., build, test), jobs with scripts, and runners executing tasks. Defined in .gitlab-ci.yml, they support artifacts and variables, enabling structured automation for enterprise DevOps workflows across diverse environments.

7. How does GitLab CI/CD process workflows?

GitLab CI/CD processes workflows by triggering pipelines on commits or schedules, executing jobs in defined stages via runners. Jobs use scripts for tasks, with artifacts for outputs. Parallel execution and rules optimize performance, ensuring seamless automation in enterprise environments with high code throughput.

• Triggers: Commits, merges, or webhooks.
• Jobs: Execute scripts in stages.
• Runners: Handle job execution.

8. What are the main features of GitLab CI/CD?

• Pipelines: Sequential or parallel job execution.
• Runners: Infrastructure for job processing.
• Artifacts: Store and share build outputs.
• Variables: Securely manage secrets and configs.
• Includes: Reuse YAML configurations.

These features enable robust automation for enterprise DevOps teams.

9. Why is the .gitlab-ci.yml file essential?

The .gitlab-ci.yml file defines the CI/CD pipeline structure, specifying stages, jobs, scripts, and conditions. It ensures reproducible builds, supports dynamic rules for conditional execution, and integrates with GitLab’s repository, critical for scalable, automated workflows in enterprise DevOps environments.

• Structure: Defines pipeline flow.
• Flexibility: Conditional job rules.
• Integration: Ties to version control.

Learn about YAML in declarative vs. imperative.

10. When should you use GitLab runners?

Use GitLab runners for executing CI/CD jobs, particularly in high-volume environments like Kubernetes clusters or cloud setups. They’re ideal for automated testing and deployment, ensuring low-latency execution in enterprise workflows with diverse job requirements.

11. Where are GitLab runner configurations stored?

• Location: /etc/gitlab-runner/config.toml on runner host.
• Settings: Executor, tags, concurrency limits.
• Registration: Via gitlab-runner register command.
• Validation: Check in GitLab UI runners section.

Configurations ensure efficient job execution in enterprises.

12. Who sets up GitLab CI/CD pipelines?

DevOps engineers design pipelines, developers write .gitlab-ci.yml, and operations teams configure runners. Security teams review for compliance, ensuring collaborative setup for reliable, scalable CI/CD in multinational corporate environments.

13. Which GitLab features enhance collaboration?

• Merge Requests: Code review and approvals.
• Issues: Track tasks and bugs.
• Wikis: Document project details.
• Comments: Inline code discussions.

These features streamline teamwork in enterprises.

14. How do you configure a GitLab runner?

Install gitlab-runner, register with GitLab using a token and URL, and configure executor (e.g., Docker, shell) in config.toml. Add tags for job matching, ensuring scalability and security for enterprise CI/CD job execution.

[[runners]] name = "docker-runner" url = "https://gitlab.com/" executor = "docker" [runners.docker] image = "alpine:latest"

15. What steps are needed to set up GitLab CI/CD?

Create .gitlab-ci.yml in the repo root, define stages and jobs, and register runners with gitlab-runner register. Enable CI/CD in project settings, configure variables, and test with CI Lint for reliable enterprise automation.

• File: Create .gitlab-ci.yml with stages.
• Runners: Register and tag for jobs.
• Validation: Use CI Lint for checks.

16. Why use variables in GitLab CI/CD?

Variables store secrets, API keys, or configuration values, enabling dynamic pipelines. Masked variables ensure security, supporting complex workflows and compliance in enterprise environments with sensitive data requirements.

17. When do you use GitLab environments?

• Deployment: Tracks staging, production stages.
• Rollback: Manages release versions.
• Monitoring: Integrates with external tools.
• Approvals: Supports manual controls.

Environments organize enterprise deployment workflows.

Explore environments in progressive delivery.

Configuration Management

18. Where are GitLab CI/CD variables defined?

Variables are defined in GitLab UI under Settings > CI/CD > Variables or in .gitlab-ci.yml with the variables keyword. Masked variables secure sensitive data, ensuring safe automation in enterprise pipelines with strict compliance needs.

19. Who handles GitLab security configurations?

Security engineers configure access controls and scanning, DevOps integrates compliance checks, and auditors review pipelines. Collaboration ensures secure, compliant CI/CD workflows in MNC environments with regulatory requirements.

Automated tools streamline security management.

20. Which settings optimize GitLab runner performance?

• concurrent: Limits simultaneous jobs.
• Executor: Docker or Kubernetes for isolation.
• Tags: Assigns jobs to specific runners.
• Cache: Reuses dependencies for speed.

Settings enhance efficiency in enterprise runners.

21. How do you validate .gitlab-ci.yml files?

Validate .gitlab-ci.yml using GitLab’s CI Lint tool in the UI, checking syntax and structure. Test with manual pipeline triggers, review logs for errors, and integrate into CI/CD for automated validation in enterprise workflows.

22. What is the purpose of the include keyword in GitLab?

The include keyword imports external YAML files for reusable pipeline configurations, reducing duplication. It supports templates for common jobs, simplifying maintenance and ensuring consistency across enterprise projects.

23. Why centralize GitLab configurations?

Centralized configurations with Git version control and shared templates ensure uniformity across projects. Tools like Ansible automate updates, streamlining audits and compliance for scalable enterprise CI/CD pipelines.

• Consistency: Uniform pipeline definitions.
• Automation: Tools for config deployment.
• Compliance: Simplifies regulatory reviews.

24. How do you manage GitLab configs for multiple environments?

Manage configs with environment-specific .gitlab-ci.yml includes, using variables for differentiation. Sync via Git, automate with Terraform, ensuring scalability and consistency across dev, staging, and production in enterprise setups.

25. What tools complement GitLab CI/CD?

• Terraform: Manages infrastructure as code.
• Docker: Builds containerized images.
• Kubernetes: Orchestrates deployments.
• Prometheus: Monitors pipeline performance.

These tools enhance enterprise CI/CD workflows.

Discover integrations in policy as code tools.

26. Why use rules in GitLab CI/CD?

Rules control job execution with conditions like branch names or variables, preventing unnecessary runs. They support manual approvals, ensuring secure and efficient pipeline execution in enterprise environments with strict controls.

27. When to use child pipelines in GitLab?

Use child pipelines for dynamic workflows, such as matrix testing across environments. They run as sub-pipelines, supporting complex, modular automation in enterprise development cycles with diverse requirements.

28. Where do you configure GitLab runner tags?

• Location: config.toml or GitLab UI.
• Structure: Tags for job matching.
• Registration: Set during gitlab-runner register.
• Modularity: Multiple tags for flexibility.

Tags ensure precise job execution in enterprises.

29. What are key GitLab CI/CD keywords?

Key keywords include stage, job, script, artifacts, and variables. They define pipeline structure, enabling conditional execution and secure handling of secrets in enterprise automation workflows.

• stage: Groups jobs logically.
• script: Executes shell commands.
• artifacts: Persists job outputs.

30. Why create custom GitLab runners?

Custom runners support specific environments or proprietary tools, ensuring compatibility and security. They’re tailored for enterprise needs, enabling optimized job execution in unique CI/CD workflows.

31. When should you use Docker with GitLab CI/CD?

• Isolation: Containerized job environments.
• Reproducibility: Consistent build runtimes.
• Multi-Language: Supports diverse toolchains.
• Security: Limits host access.

Docker ensures reliable enterprise pipelines.

32. Where can you source GitLab CI/CD templates?

Source templates from GitLab’s official repository or community forums like GitLab.com. Customize for production, validate with CI Lint, ensuring compliance in enterprise CI/CD workflows.

33. Who develops GitLab CI/CD extensions?

GitLab and community developers contribute extensions via GitLab.com, with MNC teams creating custom solutions for proprietary needs, ensuring compatibility with enterprise DevOps requirements.

Learn about contributions in trunk-based development.

Plugins and Extensions

34. Which executor is best for GitLab runners?

• Docker: Isolated container environments.
• Shell: Simple local execution.
• Kubernetes: Scalable cloud-native jobs.
• Virtualbox: VM-based isolation.

Executors align with enterprise infrastructure needs.

35. How do you define a custom GitLab CI/CD job?

Define custom jobs in .gitlab-ci.yml with a job name, stage, script for commands, and rules for conditions. Include before_script for setup and artifacts for outputs, ensuring structured execution in enterprise pipelines.

build-job: stage: build before_script: - npm install script: - npm run build artifacts: paths: - dist/

36. What is the structure of .gitlab-ci.yml?

The .gitlab-ci.yml uses YAML with top-level keys like stages, jobs, and variables. Indented hierarchy defines relationships, supporting comments for clarity in enterprise pipeline configurations.

37. What are GitLab CI/CD stages?

• Build: Compiles code or images.
• Test: Runs unit and integration tests.
• Deploy: Releases to environments.
• Review: Manual approval steps.

Stages organize enterprise CI/CD workflows.

38. Why use artifacts in GitLab CI/CD?

Artifacts store build outputs like binaries or test reports, shared across jobs or persisted for deployment. They ensure reproducibility and traceability, critical for enterprise pipelines with multi-stage workflows.

• Sharing: Passes files between jobs.
• Persistence: Stores for later use.
• Traceability: Tracks build outputs.

39. When do pipelines trigger in GitLab?

Pipelines trigger on commits, merge requests, schedules, or webhooks. Manual triggers support approvals, ensuring automated and controlled execution in enterprise development cycles.

40. Where do you configure GitLab pipeline schedules?

• UI: Settings > CI/CD > Schedules.
• API: POST /projects/:id/pipeline_schedules.
• Timing: Cron-based syntax.
• Validation: Check logs in UI.

Schedules automate enterprise tasks.

41. Who uses GitLab for compliance?

Compliance officers leverage GitLab for audit trails, DevOps for secure pipelines, and auditors for reviewing logs. Built-in scanning ensures regulatory adherence in MNC environments.

Explore compliance in SBOM compliance.

Notifications and Alerts

42. Which features support GitLab CI/CD notifications?

GitLab CI/CD notifications integrate with Slack, email, and webhooks for events like pipeline failures or successes. Configured in project settings, they support custom messages, ensuring enterprise teams stay informed of critical build statuses.

Notifications enable proactive issue resolution.

43. How do you set up GitLab webhooks?

Configure webhooks in project settings with a URL and events like push or merge. Use secret tokens for authentication, test with curl, ensuring reliable integrations with enterprise tools like Slack.

curl -X POST -H "X-Gitlab-Token: token" https://webhook.site/test

44. What is the GitLab API used for?

• Pipelines: Trigger and monitor workflows.
• Runners: Register and manage agents.
• Variables: Set or retrieve secrets.
• Projects: Access repository metadata.

The API supports enterprise automation and integration.

45. Why use merge request pipelines?

Merge request pipelines validate code changes before merging, running automated tests to ensure quality. They support review workflows, critical for secure and reliable enterprise development processes.

46. What is GitLab Auto DevOps?

GitLab Auto DevOps automates CI/CD with templates for build, test, deploy, and security scanning. It’s ideal for rapid setups, customizable for enterprise compliance and scalability requirements.

47. When to use GitLab merge trains?

• Merging: Sequential merge request handling.
• Conflicts: Automatically resolves issues.
• Compliance: Maintains audit trails.
• Integration: Works with CI pipelines.

Merge trains streamline enterprise releases.

48. Where do you define deployment jobs in GitLab?

Define deployment jobs in .gitlab-ci.yml with environment: name and when: manual for controlled releases. Use scripts for tools like kubectl, ensuring auditable deployments in enterprise environments.

49. Who configures GitLab security scanning?

Security teams configure SAST and DAST in .gitlab-ci.yml, DevOps integrates scans into pipelines, and auditors review reports. This ensures compliance and vulnerability detection in MNC codebases.

Learn about scanning in container scanning tools.

50. Which features enhance GitLab CI/CD scalability?

• Autoscaling Runners: Dynamically add capacity.
• Parallel Jobs: Distribute workload efficiently.
• Child Pipelines: Modular workflow execution.
• Cloud Integration: AWS, Google Cloud runners.

These features support high-volume enterprise pipelines.

51. How do you scale GitLab runners?

Scale runners by setting concurrent jobs in config.toml, using autoscaling with Kubernetes or cloud providers. Monitor via GitLab UI, ensuring capacity for enterprise pipeline demands and high throughput.

concurrent = 10 [[runners]] executor = "kubernetes" [runners.kubernetes] namespace = "gitlab"

52. What role do artifacts play in GitLab notifications?

Artifacts like test reports are used in notifications, providing failure details via webhooks or email. They enable detailed alerting, critical for debugging in enterprise CI/CD workflows.

53. Why use GitLab webhooks?

• Events: Trigger on push, merge, or failures.
• Security: Token-based authentication.
• Integration: Connects to Slack, Jira.
• Validation: Test via curl commands.

Webhooks enable real-time enterprise notifications.

54. How does GitLab handle pipeline failures?

GitLab handles failures with retry options, detailed logs, and notifications via email or Slack. Manual jobs and on_stop scripts support recovery, ensuring minimal disruption in enterprise CI/CD pipelines.

Advanced Features and Integration

55. What common errors occur in GitLab CI/CD?

• Syntax Errors: Invalid YAML in .gitlab-ci.yml.
• Runner Issues: Unavailable or misconfigured executors.
• Variable Errors: Undefined or unmasked secrets.
• Validation: Use CI Lint for checks.

Logs in UI aid enterprise troubleshooting.

56. When to restart GitLab runners?

Restart runners after config changes with gitlab-runner restart, or reload for minor tweaks. Schedule during low-traffic periods to ensure enterprise pipeline stability and minimal downtime.

57. Where are GitLab CI/CD logs stored?

CI/CD logs are accessible in GitLab UI under job details or /var/log/gitlab-runner/ on runner hosts. Use grep for errors, integrate with Prometheus for enterprise monitoring and debugging.

Explore logging in change failure rate.

58. Who troubleshoots GitLab pipelines?

Senior DevOps engineers troubleshoot using job logs and API, collaborating with developers for code issues. MNCs use monitoring tools to ensure proactive maintenance in CI/CD environments.

Standardized docs aid teams.

59. Which commands verify GitLab runner status?

• gitlab-runner status: Checks runner service.
• gitlab-runner list: Lists registered runners.
• curl /api/v4/runners: Queries runner API.
• UI: Admin > Runners dashboard.

Commands ensure runner health in enterprises.

60. How do you debug a failing GitLab pipeline?

Debug pipelines by reviewing job logs in GitLab UI, checking variables, and using trace mode. Add debug scripts in before_script, test in staging, ensuring reliable enterprise troubleshooting.

61. What best practices optimize GitLab pipelines?

• Parallel Jobs: Run tasks concurrently.
• Cache: Reuse dependencies for speed.
• Artifacts: Limit size for efficiency.
• Monitoring: Use GitLab analytics.

Practices ensure high-performance enterprise pipelines.

62. Why backup GitLab configurations?

Backing up .gitlab-ci.yml and runner configs with Git prevents data loss. In MNCs, automate backups with cron and store in S3, ensuring quick recovery and compliance in CI/CD workflows.

63. How to handle high job volume in GitLab?

Handle high job volume with autoscaling runners, parallel jobs, and optimized caching. Monitor with Prometheus, adjusting concurrency to maintain performance in enterprise pipelines with large workloads.

Troubleshooting and Best Practices

64. What is GitLab’s role in cloud DevOps?

GitLab integrates with cloud platforms like AWS, using cloud runners for CI/CD. It supports Kubernetes for deployments, ensuring scalable, unified workflows for enterprise cloud and hybrid environments.

• Runners: Cloud-based autoscaling.
• Integrations: Helm, Terraform.
• Scalability: Handles cloud workloads.

65. When to use self-hosted GitLab runners?

Use self-hosted runners for control over infrastructure, compliance, or cost efficiency in high-security environments. They require maintenance but offer customization for enterprise-specific CI/CD needs.

Understand self-hosting in multi-cloud deployments.

66. Where does GitLab fit in CI/CD pipelines?

• CI: Automates testing on commits.
• CD: Deploys to staging, production.
• Integration: Connects with Jira, Slack.
• Automation: Streamlines workflows.

GitLab enhances enterprise DevOps efficiency.

67. Who benefits from GitLab certifications?

DevOps engineers and CI/CD professionals gain from GitLab certifications, validating pipeline and repository management skills. Certified staff excel in MNC roles, optimizing enterprise workflows.

68. Which integrations are trending for GitLab?

Trending integrations include Kubernetes for deployments, Terraform for IaC, and Prometheus for monitoring. These support cloud-native architectures, ensuring relevance in enterprise DevOps workflows.

Integrations drive modern automation.

69. How does GitLab support containerized CI/CD?

GitLab supports containerized CI/CD with Docker-in-Docker for builds and Kaniko for secure image creation. Integrate with Kubernetes for deployments, ensuring scalability in enterprise container workflows.

build: stage: build image: docker:latest services: - docker:dind script: - docker build -t $CI_REGISTRY_IMAGE .

70. What challenges arise in scaling GitLab CI/CD?

• Runner Load: High job concurrency issues.
• Costs: Infrastructure scaling expenses.
• Maintenance: Runner and config updates.
• Solution: Autoscaling with cloud providers.

Scaling requires strategic planning for enterprises.

71. Why adopt GitLab Premium for DevOps?

GitLab Premium offers advanced features like unlimited runners, compliance reports, and enhanced security scanning, ideal for MNCs. It supports scalability, while the free tier suits smaller teams.

72. How to customize GitLab for enterprise needs?

Customize GitLab with self-hosted instances, custom runners, and integrations like Jira. Use group permissions and templates for scalability, ensuring compliance in enterprise DevOps environments.

Enterprise and Future Trends

73. What is GitLab’s role in microservices?

• Pipelines: Multi-project workflows.
• Deployments: Kubernetes integration.
• Tracing: Tracks service interactions.
• Scalability: Supports distributed systems.

GitLab streamlines microservices in enterprises.

Explore microservices in self-service platforms.

74. When to use GitLab for security analytics?

Use GitLab for security analytics with SAST and DAST in pipelines, detecting vulnerabilities early. It supports compliance with automated reports, ideal for enterprise security workflows.

75. Where to find GitLab community resources?

Find resources on forum.gitlab.com, GitLab documentation, and Stack Overflow, offering templates, troubleshooting guides, and best practices for enterprise DevOps professionals.

76. Who contributes to GitLab development?

GitLab’s core team and community developers contribute via GitLab.com, with MNC teams adding custom integrations for enterprise needs, ensuring continuous innovation in DevOps tools.

Contributions drive platform evolution.

77. Which security features protect GitLab?

• Masked Variables: Secure secrets handling.
• SAST/DAST: Automated vulnerability scans.
• RBAC: Role-based access controls.
• Audit Logs: Track user actions.

Features safeguard enterprise CI/CD pipelines.

78. How to optimize GitLab for IoT pipelines?

Optimize GitLab for IoT with lightweight Docker runners, minimizing resource usage. Use efficient pipelines with caching, ensuring scalability for enterprise IoT deployments with low-bandwidth devices.

iot-build: stage: build image: docker:light script: - docker build -t iot-image .

79. What GitLab trends are expected in 2025?

Trends for 2025 include AI-driven pipeline optimization, serverless runners, and enhanced multi-cloud support. Security and automation advancements ensure GitLab’s relevance in enterprise DevOps workflows.

80. Why use GitLab in hybrid environments?

• Unified: Supports on-prem and cloud.
• Consistency: Standardized pipeline configs.
• Integrations: AWS, Azure, Kubernetes.
• Scalability: Manages hybrid complexity.

GitLab unifies enterprise hybrid DevOps.

81. How to measure GitLab CI/CD performance?

Measure performance with pipeline duration, failure rate, and deployment frequency via GitLab Analytics. Monitor runner utilization and artifact sizes, optimizing for enterprise efficiency and reliability.

Learn about metrics in DORA metrics.

82. What is GitLab’s compliance framework?

GitLab’s compliance framework enforces policies like mandatory approvals and security scans. It generates audit reports, ensuring regulatory adherence in enterprise CI/CD pipelines with strict standards.

83. When to use GitLab for monorepo pipelines?

Use GitLab for monorepo pipelines to manage multiple services in one repository, using child pipelines for modularity. It supports complex workflows, ideal for enterprise monorepo architectures.

84. Where to store GitLab backups?

• Git Repos: Version .gitlab-ci.yml files.
• S3: Store runner configurations.
• Automation: Use cron for backups.
• Retention: Policy-based deletion.

Backups ensure enterprise data resilience.

85. Who is responsible for GitLab pipeline performance?

DevOps engineers optimize pipelines and runners, while SREs monitor health with tools like Prometheus. Collaboration ensures uptime and efficiency in MNC CI/CD environments.

Accountability aligns with goals.

86. Which metrics are critical for GitLab monitoring?

• Pipeline Duration: Time to completion.
• Job Failure Rate: Success percentage.
• Deployment Frequency: Release cadence.
• Runner Usage: Resource efficiency.

Metrics drive enterprise pipeline optimization.

87. How to monitor GitLab runner performance?

Monitor runners via GitLab UI for CPU and memory usage, integrating with Prometheus for detailed metrics. Set alerts for anomalies, ensuring efficiency in enterprise CI/CD pipelines.

curl -H "PRIVATE-TOKEN: token" "https://gitlab.com/api/v4/runners"

88. What is the role of GitLab group runners?

Group runners execute jobs across multiple projects in a GitLab group, simplifying management. They support shared configurations, enhancing scalability and consistency in enterprise CI/CD setups.

89. Why use GitLab for multi-project pipelines?

• Dependency: Triggers across repositories.
• Modularity: Child pipelines for tasks.
• Scalability: Manages complex workflows.
• Integration: Supports monorepos.

Multi-project pipelines streamline enterprise automation.

Explore multi-project in Kubernetes provisioning.

90. When to use GitLab for container orchestration?

Use GitLab for container orchestration with Kubernetes integration, deploying via Helm charts in pipelines. It’s ideal for enterprise microservices requiring scalable, automated deployments.

91. Where to configure GitLab pipeline triggers?

• UI: Settings > CI/CD > Pipeline Triggers.
• API: POST /projects/:id/triggers endpoint.
• Security: Token-based authentication.
• Validation: Test with curl commands.

Triggers automate enterprise pipeline execution.

92. Who maintains GitLab documentation?

GitLab maintains official docs on docs.gitlab.com, with community contributions via merge requests. MNC teams create internal guides for enterprise-specific CI/CD practices.

Documentation supports adoption.

93. Which plugins enhance GitLab integrations?

• Docker: Builds container images.
• Helm: Deploys to Kubernetes.
• Terraform: Manages infrastructure.
• Jira: Tracks issues.

Plugins enable seamless enterprise connectivity.

94. How to integrate GitLab with Kubernetes?

Integrate GitLab with Kubernetes using the GitLab Agent or Helm charts in pipelines. Deploy with kubectl, configure CI/CD for cluster access, ensuring secure enterprise container deployments.

deploy: stage: deploy image: bitnami/kubectl script: - kubectl apply -f deployment.yaml

95. What is the role of GitLab cache?

GitLab cache stores dependencies like node_modules, reused across jobs to speed up builds. Configured in .gitlab-ci.yml, it optimizes performance in enterprise pipelines with frequent builds.

96. Why use GitLab for security scanning?

• SAST: Detects code vulnerabilities.
• DAST: Scans running applications.
• Reports: Generates compliance audits.
• Integration: Built into pipelines.

Scanning ensures secure enterprise codebases.

97. When to use GitLab for infrastructure as code?

Use GitLab for IaC with Terraform in pipelines, automating infrastructure provisioning. It’s ideal for enterprise environments requiring consistent, auditable infrastructure deployments.

Learn about IaC in git hooks.

98. Where to find GitLab pipeline metrics?

Pipeline metrics are in GitLab UI under Analytics > CI/CD, tracking duration, success rates. Use API or Prometheus for custom dashboards, optimizing enterprise performance monitoring.

Metrics guide improvements.

99. Who is responsible for GitLab runner maintenance?

Operations and DevOps teams maintain runners, updating versions and monitoring health. Security reviews configurations, ensuring reliability in enterprise CI/CD environments with high availability needs.

100. Which tools integrate with GitLab for monitoring?

• Prometheus: Collects runner metrics.
• Grafana: Visualizes pipeline performance.
• Slack: Sends failure alerts.
• API: Custom monitoring scripts.

Tools enhance enterprise visibility.

101. How to optimize GitLab pipeline execution?

Optimize pipelines with parallel jobs, caching dependencies, and minimal artifacts. Monitor with Prometheus, adjust runner concurrency, and use child pipelines for modularity in enterprise CI/CD workflows.

cache: key: $CI_COMMIT_REF_SLUG paths: - node_modules/

102. What is the role of GitLab’s Auto DevOps?

Auto DevOps automates CI/CD with prebuilt templates for build, test, deploy, and security scans. It’s customizable for enterprise compliance, ideal for rapid setup in complex DevOps environments.