CI CD Interview Questions Wiki - cloudops-code/Interview_question_answers GitHub Wiki

1. Code Quality What is code quality, and why is it important?

Code quality refers to the attributes that determine how well code is written and maintained. High-quality code is readable, maintainable, efficient, and free of bugs. It's crucial for reducing technical debt and facilitating easier updates and scaling.

In this context, technical debt refers to the future cost of fixing or improving code that was written quickly or poorly in the present—often to meet a deadline or ship a feature faster.

Think of it like taking a shortcut in coding that “works for now,” but isn’t the best or cleanest solution. Over time, these shortcuts pile up and make your system harder to maintain, debug, and extend. Just like financial debt, technical debt "accumulates interest"—the longer you leave it unaddressed, the more expensive and risky it becomes to fix.

Examples of Technical Debt: Poorly written or unrefactored code that’s hard to understand.

Lack of tests, making changes risky.

Hardcoded values that should be configurable.

Copy-paste code instead of modular, reusable components.

Using outdated libraries or tech that needs migration later.

Why Code Quality Helps: High-quality code helps minimize or control technical debt by ensuring the codebase is clean, modular, well-tested, and easy to work with—so future developers (including you!) can make changes without breaking things or wasting time.

How do you ensure code quality in a CI/CD pipeline?

By integrating tools like linters (e.g., ESLint, Pylint), static code analyzers (e.g., SonarQube), and enforcing code reviews and coding standards within the CI/CD process.

What are some common code quality metrics?

Metrics include cyclomatic complexity, code duplication, code coverage, maintainability index, and technical debt ratio.

Code Duplication What it is: Code duplication happens when the same (or very similar) blocks of code appear in multiple places in your codebase.

Why it's bad:

Increases maintenance effort (change in one place → must change everywhere).

Makes bugs harder to fix.

Reduces readability and reusability. How it's measured: By tools like SonarQube, PMD, or CodeClimate, which scan for repeated code blocks (usually % duplication or number of duplicated lines/files).

Code Coverage What it is: The percentage of your code that is executed by automated tests.

Why it's useful:

Indicates how well your code is tested.

Helps identify untested areas that might hide bugs.

Types of coverage:

Statement Coverage: Are all lines run?

Branch Coverage: Are all if/else paths tested?

Function Coverage: Are all functions called?

Condition Coverage: Are all Boolean conditions evaluated?

Tools: JaCoCo (Java), Istanbul (JavaScript), Coverage.py (Python), etc.

. Maintainability Index What it is: A score (usually 0–100) that reflects how easy it is to maintain the code. Higher scores mean better maintainability.

Calculated using:

Cyclomatic complexity (code complexity)

Lines of code

Halstead volume (code comprehension effort)

Code comments

Ranges (roughly):

85–100: Highly maintainable

65–84: Moderate maintainability

<65: Hard to maintain

Why it matters: Maintainable code is easier to modify, test, and debug. Low scores often point to technical debt.

Tools: Visual Studio, SonarQube, CodeClimate, etc.

Technical Debt Ratio What it is: A measure of how much extra effort is required to fix issues in the code, compared to the effort of writing the code from scratch.

Formula:

pgsql Copy Edit Technical Debt Ratio = Remediation Cost / Development Cost Remediation Cost = estimated time to fix all issues (bugs, smells, poor structure)

Development Cost = estimated time to build the system cleanly

Example: If it took 100 hours to develop a module, and fixing all issues would take 20 hours:

ini Copy Edit TDR = 20 / 100 = 0.20 or 20% Good practice: Try to keep the Technical Debt Ratio < 5%. Higher ratios signal growing maintenance risks.

Tools: SonarQube is the most common tool that reports this.

How do code reviews contribute to code quality?

Code reviews allow peers to examine code for potential issues, adherence to standards, and opportunities for improvement, thereby enhancing overall code quality. razorops.com

What is the role of static code analysis in maintaining code quality?

Static code analysis tools automatically examine code for potential errors, code smells, and adherence to coding standards without executing the program.

2. Code Coverage What is code coverage, and why is it important?

Code coverage measures the percentage of source code executed during testing. Higher coverage indicates more thorough testing, which can lead to fewer bugs and more reliable software. crsinfosolutions.com

What are the different types of code coverage?

Types include statement coverage, branch coverage, function coverage, and condition coverage, each measuring different aspects of code execution during tests. crsinfosolutions.com

Is 100% code coverage necessary?

While 100% coverage ensures all code paths are tested, it's not always practical or necessary. Focus should be on critical and complex parts of the codebase. lambdatest.com

How do you measure code coverage in your projects?

By using tools like JaCoCo for Java, Istanbul for JavaScript, or Coverage.py for Python, which integrate with CI/CD pipelines to provide coverage reports.

How can code coverage metrics be misleading?

High coverage doesn't guarantee code quality or absence of bugs; tests might not assert correct behavior, leading to a false sense of security.

3. CI/CD Pipeline Flow What are the key stages of a CI/CD pipeline?

Stages typically include source code management, build, automated testing, deployment, and monitoring. lambdatest.com

How do you implement continuous integration?

By automatically building and testing code changes upon each commit to the version control system, ensuring early detection of issues.

What is continuous delivery, and how does it differ from continuous deployment?

Continuous delivery ensures code is always in a deployable state, requiring manual approval for production releases. Continuous deployment automates the release to production without manual intervention. mentorcruise.com

How do you handle environment-specific configurations in a CI/CD pipeline?

By externalizing configurations using environment variables, configuration files, or tools like HashiCorp's Vault, and managing them separately from the application code.

What strategies do you use for zero-downtime deployments?

Techniques include blue-green deployments, canary releases, and rolling updates to minimize or eliminate downtime during deployments.

How do you ensure the security of your CI/CD pipeline?

By implementing access controls, encrypting sensitive data, regularly updating tools, and integrating security scanning tools into the pipeline. razorops.com

What tools have you used for CI/CD, and what are their pros and cons?

Common tools include Jenkins, GitLab CI/CD, CircleCI, and Travis CI. Each has its strengths and weaknesses regarding ease of use, scalability, and community support.

How do you monitor and maintain a CI/CD pipeline?

By setting up logging, alerting, and monitoring tools to track pipeline performance and quickly address failures or bottlenecks.

✅ 1. What is CI/CD? • CI (Continuous Integration): Automatically tests and integrates code after every commit. • CD (Continuous Deployment/Delivery): Automates deployment of tested code to staging or production.

✅ 2. Why is CI/CD important? • Ensures faster testing and deployment. • Detects issues early in the development cycle. • Reduces manual effort and increases software reliability.

✅ 3. Name some popular CI/CD tools. • Jenkins, GitHub Actions, GitLab CI/CD, Travis CI, CircleCI, ArgoCD.

✅ 4. What is the role of CI/CD tools? • Automates build, test, and deployment workflows. • Ensures code changes are validated before integration. • Improves collaboration between development, QA, and operations teams.

✅ 5. What is a CI/CD pipeline? • An automated workflow that includes: 1. Build → Test → Deploy. 2. Ensures rapid and reliable software delivery.

✅ 6. How can CI/CD be used for different domains (QA, ML, DevOps, etc.)? • QA: Automates testing and reports failures. • ML: Automates model training, validation, and deployment. • DevOps: Manages infrastructure as code and automates deployments.

✅ 7. What is the difference between Continuous Delivery and Continuous Deployment? • Continuous Delivery: Requires manual approval before deployment. • Continuous Deployment: Deploys automatically without manual intervention.

✅ 8. What happens if a build or test fails in CI/CD? • Deployment is halted. • Failure notifications are sent. • Logs are analyzed, and issues are fixed before retrying.

✅ 9. What is the role of containerization (Docker/Kubernetes) in CI/CD? • Packages code and dependencies into a standardized container. • Ensures consistency across different environments. • Enables scalable deployment with Kubernetes.

✅ 10. How does CI/CD improve software quality? • Automates testing and validation. • Reduces human errors in deployment. • Provides faster feedback and issue detection.