Top 30 Devops Interview Questions and Answers
30 multiple-choice questions on Devops, drawn from 30 bites out of the 294 tagged Devops on Tezvyn. Answer them here or read straight down. Every question carries the correct option, why it is correct, and a link to the bite it came from.
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Question 1 of 30
A team merges into a shared branch daily with automated builds and tests. What is the single most important goal of this Continuous Integration practice?
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Answer: c · Keeping the integrated codebase in a workable state at all times
The defining goal of CI is maintaining a workable integrated codebase, not deployment, which is the realm of CD. While automation and bug detection are part of the practice, they are mechanisms and secondary benefits rather than the core objective.
Read the full bite: What is CI, and what is its single most important goal?
Question 2 of 30
What problem does cloud computing primarily solve for businesses launching new digital services?
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Answer: c · The high upfront costs and risks of owning physical IT infrastructure.
The card states cloud computing was created to solve "huge upfront capital costs, long procurement times, and the risk of buying too much or too little capacity" associated with owning physical servers. While cloud computing can help with IT personnel challenges (A) and high availability (D), these are not its primary foundational purpose.
Read the full bite: Cloud Computing: Renting Someone Else's Computer
Question 3 of 30
What is the primary distinction that makes MLOps necessary beyond traditional DevOps for machine learning systems?
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Answer: a · Continuously monitoring model performance and orchestrating retraining on new data.
MLOps uniquely addresses the lifecycle of machine learning models and their underlying data, including continuous monitoring for performance decay and automated retraining. Traditional DevOps focuses primarily on the code lifecycle, which is insufficient for the dynamic nature of ML models.
Read the full bite: MLOps vs. DevOps: More Than Just "DevOps for ML"
Question 4 of 30
Which characteristic is most crucial for an effective build automation process?
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Answer: c · It consistently transforms source code into a runnable application, regardless of the environment.
The card emphasizes that build automation makes the process "repeatable, reliable" and ensures "the same result every time, no matter who pushes the 'start' button." Option C directly reflects this core benefit. Option D describes the "it works on my machine" problem that build automation aims to eliminate, not a desired characteristic.
Question 5 of 30
What is the primary goal of integrating Rovo agents into Jira Service Management?
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Answer: c · To significantly decrease the number of repetitive service requests handled by human agents.
The card explicitly states Rovo agents aim to "deflect up to 60% of repetitive service tickets" and "automate resolutions for known issues," directly reducing the workload on human agents for routine requests. While documentation quality is critical for Rovo's success, its main objective is ticket deflection, not direct documentation improvement.
Read the full bite: Jira's Rovo AI Aims to Deflect 60% of Tickets
Question 6 of 30
How does Bitbucket prioritize the deployment status badge when a single commit maps to multiple environments with different states?
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Answer: d · It ranks statuses by urgency and surfaces the highest-priority state
The card explains that badges bubble up by urgency, ranking Failed above Stopped, In Progress, and Successful. Distractor A is tempting because many tools sort by recency, but Bitbucket explicitly uses urgency-based prioritization.
Read the full bite: Bitbucket beta adds live deployment status to PR lists
Question 7 of 30
In large monorepos, why does connecting Claude Code to GitLab Orbit via MCP reduce hallucinations and token usage compared to standard file crawling?
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Answer: b · It lets the agent ask a live graph direct questions about code location, dependencies, and coverage instead of crawling fragmented files
Orbit replaces file crawling with targeted queries to a live graph of relationships, which is why token use and hallucinations drop. The efficiency gains come from graph-based reasoning, not from MCP compression or model swapping.
Read the full bite: GitLab Orbit unifies code lifecycle in live graph
Question 8 of 30
What is the main advantage of GitLab Flex when a team's seat needs and AI usage change in opposite directions during the year?
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Answer: c · It allows monthly rebalancing of a single annual budget across seats, AI, and features without re-procurement.
GitLab Flex lets organizations draw down seats, AI credits, and features from one annual commitment and rebalance monthly without returning to procurement. Option B describes the traditional vendor model that Flex is designed to replace, not Flex itself.
Read the full bite: GitLab Flex merges seats and AI into one budget
Question 9 of 30
When you run a container from an image, how does Docker handle the image layers and runtime file changes?
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Answer: a · It keeps the image layers read-only and adds a writable layer on top for runtime changes.
A container mounts the image's read-only layers and adds a writable layer on top, allowing runtime changes without altering the original image. Option B is wrong because containers are isolated processes that share the host kernel, not mini-VMs that boot their own kernels.
Read the full bite: How do Docker images and containers differ and relate?
Question 10 of 30
A developer pushes to main, triggering a CI pipeline with build, test, and deploy stages. Which outcome best matches typical execution?
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Answer: b · A runner builds the project; then multiple runners execute test jobs in parallel; deployment proceeds only if every test job succeeds.
The card states that runners (not the Git server) execute jobs, that jobs within a stage run in parallel, and that a stage must succeed completely before the next stage begins. Option C is tempting because it correctly mentions sequencing but wrongly assumes everything runs sequentially on one machine and ignores the requirement that all jobs pass.
Read the full bite: Describe the typical CI pipeline sequence from push to deploy
Question 11 of 30
Which of the following best exemplifies 'toil' in an engineering context?
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Answer: c · Manually running a script to provision resources for each new customer
Option C perfectly matches the definition of toil: it is manual, repetitive, automatable, tactical, provides no lasting value, and scales linearly with service growth. Option A, attending meetings, is explicitly categorized as 'overhead' rather than toil, as it doesn't scale with service load in the same way.
Read the full bite: Toil: The Repetitive Work That Kills Engineering Velocity
Question 12 of 30
What is Docker's primary method for resolving the 'Works on My Machine' problem?
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Answer: a · It bundles the application with all its specific dependencies into a portable, consistent unit.
The card explicitly states Docker solves this by "packaging an application with all of its dependencies... into a single, isolated unit called a container image." This ensures the environment is consistent everywhere. While related to isolation, containers are distinct from full virtual machines, which are heavier and emulate entire hardware systems.
Question 13 of 30
Which scenario would trigger an automated MLOps deployment but typically not a traditional DevOps pipeline?
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Answer: b · Production monitoring detecting drift in input data distributions
The card states that MLOps deployments add triggers like data drift detection, unlike DevOps pipelines that react to code commits, dependency patches, or infrastructure changes. The GPU driver update is a tempting distractor because a common misconception is that MLOps is simply DevOps plus GPUs.
Read the full bite: What are the primary differences between traditional DevOps and MLOps?
Question 14 of 30
Which statement best captures the relationship between SRE and DevOps?
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Answer: a · SRE is a prescriptive implementation of the broader DevOps philosophy
SRE provides concrete practices, SLOs, error budgets, blameless postmortems, that implement the abstract DevOps principles. They are complementary, not competing, and they operate at different levels of abstraction.
Question 15 of 30
What is the key feature that distinguishes a private cloud from a traditional, on-premises data center?
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Answer: d · It offers on-demand, self-service access to resources through a management software layer.
A private cloud's defining characteristic is the cloud management software stack that provides self-service, on-demand access and automation, differentiating it from a traditional data center which may also own its hardware and use virtualization but lacks these cloud-like capabilities. While option B is often true for private clouds, it's also true for traditional data centers, so it's not the distinguishing factor.
Read the full bite: Private Cloud: Cloud Computing on Your Terms
Question 16 of 30
What is a key advantage of automated testing in modern software development?
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Answer: a · It allows for rapid and confident deployment of code changes by detecting regressions early.
The card highlights that automated testing "provides the confidence needed to deploy changes frequently" and is "the foundation for catching regressions." Option B is incorrect because the card explicitly states automated testing is "not suited for exploratory testing... or for assessing subjective user experience."
Read the full bite: Automated Testing: Catch Bugs Before They Ship
Question 17 of 30
A company automatically deploys its internal tools to production but requires manual sign-off for its customer-facing payment service. What does this mixed strategy best demonstrate?
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Answer: d · Different applications may require different pipeline models based on business risk and compliance needs.
The card stresses that the choice between Continuous Delivery and Continuous Deployment is driven by business context, regulatory requirements, and blast radius, and that organizations often run a mixed model. Option A reflects the common misconception that Delivery is just an inferior version of Deployment, while the correct answer captures the intentional, risk-based pipeline design described in the card.
Question 18 of 30
Which scenario best demonstrates the appropriate use of an artifact repository?
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Answer: a · Publishing a newly built Java .jar file to be consumed by other internal projects.
An artifact repository is designed to store and share binary outputs like compiled code (.jar files) from a build process for consumption by other systems or teams. Storing source code is for version control systems, while archiving unstructured logs or serving static assets are roles for general file storage or web servers, not artifact repositories.
Read the full bite: Artifact Repository: Your CI/CD's Private Library
Question 19 of 30
Which approach aligns with the 'build once, deploy many' principle when handling environment-specific database URLs?
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Answer: d · Build the container image once, then provide the database URL via environment variables at deployment time
The correct answer preserves artifact immutability by externalizing configuration and deploying the same binary everywhere. Option C is tempting because build arguments appear to parameterize deployments cleanly, but they force per-environment rebuilds that can introduce unverified dependency changes.
Read the full bite: What is a build artifact and why build once deploy many crucial?
Question 20 of 30
In an Infrastructure as a Service (IaaS) model, which aspect of the computing environment is the user primarily responsible for managing?
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Answer: b · The operating system, applications, and data.
The card states that in IaaS, "you're still responsible for managing the OS and all software" and compares it to bringing your "OS, applications, and data." Option D describes a Platform as a Service (PaaS) or Serverless model, which IaaS is explicitly contrasted with for users who want to avoid server management.
Read the full bite: Infrastructure as a Service (IaaS): Renting the Data Center
Question 21 of 30
Which scenario best describes a genuine shift-left practice rather than a common misconception?
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Answer: b · Integrating static analysis into pull request builds so vulnerabilities are caught before merge
Integrating static analysis into pull request builds moves security feedback to the coding phase, which is the essence of shift left. Hiring more QA staff to test before release only increases test volume at the same late stage, confusing more testing with earlier feedback.
Read the full bite: What does shift left mean in CI/CD, and give two concrete examples?
Question 22 of 30
What is the primary problem Infrastructure as Code (IaC) aims to solve in managing IT infrastructure?
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Answer: a · Preventing configuration drift and ensuring consistent, repeatable environments.
The card explicitly states IaC was created to combat 'configuration drift' and ensure 'consistent, repeatable environments.' While IaC can contribute to cost efficiency, its main purpose is not cost reduction, and it does not eliminate all human involvement, but rather automates the provisioning process through code, not GUIs.
Read the full bite: Infrastructure as Code: Manage Servers with Code, Not Clicks
Question 23 of 30
What key characteristic separates Infrastructure as Code from traditional imperative server scripting?
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Answer: d · IaC defines the desired end state and achieves idempotence through automated reconciliation
True IaC is defined by its declarative, idempotent model that lets the platform reconcile to a desired state, not by the file format used. While IaC definitions are often written in JSON or YAML, simply using those formats without declarative idempotence is still just scripting.
Read the full bite: What is Infrastructure as Code (IaC), and how does it support CI/CD?
Question 24 of 30
What is the primary advantage of implementing a Blue-Green deployment strategy?
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Answer: d · It ensures continuous service availability and provides immediate rollback capabilities during deployments.
The card states that Blue-Green deployment enables "zero-downtime releases and instant rollbacks," which directly translates to continuous service availability and immediate rollback. Option C is incorrect because this strategy temporarily doubles infrastructure costs.
Read the full bite: Blue-Green Deployment: Zero-Downtime Releases
Question 25 of 30
What is the primary distinction between a canary release and A/B testing?
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Answer: a · A canary release primarily validates the technical stability and performance of a new version, whereas A/B testing evaluates user engagement and business outcomes.
The card states that a canary's goal is to quickly validate stability, while an A/B test is a longer-running experiment to test a business hypothesis. Option B describes a feature of canary releases but not its primary distinguishing purpose from A/B testing.
Read the full bite: Canary Release: Test New Code on Real Users, Safely
Question 26 of 30
Which is the primary advantage of Pipeline as Code over configuring CI/CD processes via a graphical user interface?
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Answer: a · It enables version control, peer review, and auditability of the build and deployment logic.
The core benefit of Pipeline as Code is treating the pipeline definition as a version-controlled file, which allows for reviewable changes and a complete audit history. Option D is incorrect because Pipeline as Code explicitly involves defining the pipeline through code, such as a Jenkinsfile.
Read the full bite: Pipeline as Code: Versioning Your Build Process
Question 27 of 30
Which situation best indicates that Value Stream Mapping would be a beneficial tool?
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Answer: a · A company suspects its complex software delivery process is slow but doesn't know where the major delays occur.
Value Stream Mapping is most effective when a complex process is slow, and the specific bottlenecks or sources of waste are unknown. It helps visualize the entire system to pinpoint where delays occur. Option C is tempting, but VSM focuses on the entire system's flow and waste, not just optimizing individual active work, and option B suggests the bottlenecks are already known, which makes VSM less critical.
Read the full bite: Value Stream Mapping: Find the Waste in Your Process
Question 28 of 30
Which scenario best illustrates a fundamental CI/CD difference between monoliths and microservices regarding blast radius and artifact indivisibility?
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Answer: a · A microservice team deploys a signed container side-by-side with the previous version, while a monolith rollback requires reverting the entire application
This captures the core idea that monoliths produce a single indivisible artifact requiring full rollback, while microservices support independent side-by-side deployments with signed images. Option C reverses these architectures and promotes the shared-pipeline anti-pattern the card explicitly warns destroys team autonomy.
Read the full bite: How does your CI/CD strategy differ between monoliths and microservices?
Question 29 of 30
A software team identifies its code review process as the primary constraint. According to the Theory of Constraints, which action should they prioritize before considering hiring more reviewers?
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Answer: a · Implement stricter coding standards and encourage smaller pull requests to improve review efficiency.
The Theory of Constraints (TOC) dictates that after identifying a constraint, the next step is to 'exploit' it by making the most of existing resources, such as improving review efficiency through better standards and smaller PRs (Option A). 'Elevating' the constraint, like hiring more reviewers (Option B), is a later step, only considered after exploiting and subordinating. Options C and D represent common misconceptions: focusing on local utilization or attempting to fix multiple bottlenecks at once, rather than the single primary constraint.
Read the full bite: How would you identify and elevate your team's primary constraint?
Question 30 of 30
A software team implements an Andon Cord for their main branch. Which action indicates a fundamental misunderstanding of its core principle?
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Answer: d · The team creates a high-priority ticket for the developer who introduced the bug to fix it by the next stand-up.
The card explicitly states that creating a high-priority ticket, assigning individual blame, or scheduling the fix for later are common mistakes that miss the point of an Andon Cord. The principle requires an immediate, collective, all-hands-on-deck response, not a scheduled, individual task.
Read the full bite: How would you implement an Andon Cord for a software team?
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