Top 25 DevOps questions you need to know

DevOps is a way of working where people, practices and automation come together to deliver software faster with higher stability. It connects planning, coding, testing, releasing and operating into one continuous flow. The business outcome is shorter time to value and fewer incidents.

For .NET applications, DevOps standardises builds with repeatable pipelines, removes manual deployment risk and gives clear feedback from production. Azure DevOps and GitHub pair naturally with the .NET toolchain, so you spend less time wiring tools and more time shipping value.

A DevOps engineer builds and maintains the toolchain and processes that move code from idea to production. Typical work includes pipeline design, environment provisioning, configuration, monitoring, incident response and improving developer experience. The value is reliable releases and a calmer on‑call life.

Yes. You do not need to be a full‑stack developer, but you will write scripts, define pipelines as code and review pull requests. PowerShell, Bash and YAML are table stakes. C# or another language helps you understand how apps behave in production.

Agile plans and prioritises the work. DevOps makes delivery continuous and safe. Together they reduce batch sizes, shorten feedback loops and focus teams on outcomes rather than handoffs.

• DevOps is not a single role or tool. It is a way of working.
• You do not “finish” DevOps. You keep improving flow, quality and safety.
• More deployments do not mean more incidents. High performers deploy often with fewer failures, supported by good testing and automation. (Source: DORA)

Continuous integration merges small changes frequently with automated tests to catch regressions early. Continuous delivery or deployment automates the release process so you can ship to users on demand. For .NET, CI/CD removes fragile manual steps and makes releases a routine event.

• Use one build that promotes through environments. Avoid rebuilding per stage.
• Cache NuGet packages to speed builds and pin versions.
• Run unit tests in parallel, then integration and component tests.
• Publish versioned artefacts, not source.
• Use environment variables and Key Vault for secrets, never store secrets in repos.
• Add quality gates for PRs: build, tests, code coverage and security scans.
• Use blue‑green or rolling strategies for zero‑downtime releases on App Service or AKS.
• Treat infrastructure as code to keep environments consistent.

Track the four widely used DORA metrics: deployment frequency, lead time for changes, change failure rate and mean time to restore. These highlight speed, quality and resilience, and correlate with better business performance. (Source: DORA)

• Deployment frequency: count successful production deployments per day or week. Automate this by emitting a release event from your pipeline.
• MTTR: timestamp when an incident starts and when service is restored. Use your incident tool to calculate MTTR automatically and review it in post‑incident reports. Trend these over time to see improvement.

Start small with clear outcomes and evolve structure as throughput grows.

• Development: build features, write tests, review PRs, fix defects.
• QA: design test strategy, automate where it pays off, explore new changes before production.
• DevOps: own CI/CD, environments, observability, incident response and platform hygiene.

Operating model to adopt in month one:

• One shared backlog with clear definitions of ready and done.
• Trunk‑based development with short‑lived branches and mandatory reviews.
• A single production‑like staging environment for end‑to‑end testing.
• Daily 15‑minute delivery stand‑up to unblock releases.
• A weekly operations review that looks at deployment frequency, change failure rate and top incidents.

The value is fewer handoffs and a team that ships together.

Product owners and analysts set outcomes and acceptance criteria. Developers design and implement. QA and DevOps make quality and delivery systemic through automation and feedback. Work flows as small slices from backlog to production with clear acceptance checks. This reduces risk and shortens lead time.

• Repos: one repo per application or logical service. Keep shared libraries separate.
• Branching: trunk‑based with feature branches, or short‑lived GitFlow if releases need hardening.
• Boards: map epics to business goals, features to slices of value and user stories to implementable changes.
• Packages: use Azure Artifacts for private NuGet feeds to version components across apps. (Source: Microsoft Learn)

Azure Pipelines supports YAML pipelines that version alongside code. Use build stages for compile and test, then release stages for deploy, approvals and gates. (Source: Microsoft Learn)

Example minimal pipeline for a web API:

trigger:
  branches:
    include:
      - main

pool:
  vmImage: 'windows-latest'

variables:
  buildConfiguration: 'Release'

stages:
- stage: Build
  jobs:
  - job: Build
    steps:
    - task: NuGetToolInstaller@1
    - task: NuGetCommand@2
      inputs:
        restoreSolution: '**/*.sln'
    - task: VSBuild@1
      inputs:
        solution: '**/*.sln'
        configuration: '$(buildConfiguration)'
    - task: VSTest@2
      inputs:
        testSelector: 'testAssemblies'
        testAssemblyVer2: '**/*tests*.dll'
    - task: PublishBuildArtifacts@1
      inputs:
        PathtoPublish: '$(Build.SourcesDirectory)/publish'
        ArtifactName: 'drop'

- stage: Deploy_Staging
  dependsOn: Build
  jobs:
  - deployment: Deploy
    environment: 'staging'
    strategy:
      runOnce:
        deploy:
          steps:
          - task: AzureWebApp@1
            inputs:
              appType: 'webApp'
              WebAppName: 'my-staging-app'
              package: '$(Pipeline.Workspace)/drop/**/*.zip'

Azure Test Plans provides manual and exploratory testing with traceability to requirements and defects. It is integrated with pipelines and reporting. (Source: Microsoft Learn)

Open the user story, add or update tasks and record time in Remaining Work and Completed Work fields. Use the built‑in queries and dashboards to track effort at sprint and team level. (Source: Microsoft Learn)

Yes. Azure DevOps Server is the on‑premises offering, previously known as Team Foundation Server. It includes Boards, Repos, Pipelines, Test Plans and Artifacts for self‑hosted environments. (Source: Microsoft Learn)

If you need tight network isolation or cannot use public cloud, Server fits. If you want speed to value, reduced maintenance and quick feature access, Services is usually the better default. (Source: Microsoft Learn)

Bake security into the pipeline with static analysis, dependency scanning and secret scanning on every PR. Store secrets in Azure Key Vault and inject them at deploy time. Keep audit trails of who changed what, when and why. For UK GDPR, minimise personal data in logs, set data retention policies and ensure vendors provide appropriate safeguards. Azure services include encryption at rest and in transit with configurable retention and access controls. (Source: Microsoft Learn)

Infrastructure as code (IaC) defines environments in templates you version and review like application code. Use Bicep or Terraform to describe App Service plans, AKS clusters, VNets and Key Vaults. The benefit is consistent environments, faster recovery and fewer surprises between staging and production. (Source: Microsoft Learn)

Audit your collections and projects, clean up unused repos and work items, then use Microsoft’s migration tools to move to Azure DevOps Services. Plan cutover for a weekend, freeze changes during migration and validate permissions and pipelines before re‑opening the project. Teams gain faster updates and less server care. (Source: Microsoft Learn)

Instrument applications with OpenTelemetry or the .NET SDK and send telemetry to Azure Monitor and Application Insights for availability, performance and dependencies. Define alerts on error rates, latency and saturation, link them to on‑call schedules and keep runbooks near the dashboards. Use post‑incident reviews to tune alerts, improve tests and update playbooks. (Source: Microsoft Learn)

AI helps in three practical ways:

• Coding assistance to speed up tests, infrastructure templates and pipeline YAML.
• Detection of anomalies in logs and metrics to surface issues earlier.
• Smart runbooks and chat‑based support during incidents to shorten time to restore.

Use AI as a co‑pilot, not an autopilot, and keep humans accountable for approvals and releases.

• Prefer cloud‑hosted agents unless build minutes are very high, then evaluate self‑hosted agents.
• Cache dependencies and run tests selectively to reduce build time.
• Right‑size environments, turn off non‑production out of hours and tag resources for chargeback.
• Track cost per deployment and per service to inform prioritisation. Azure Cost Management helps with visibility when you deploy to Azure. (Source: Microsoft Learn)

Pick one product or service. Map the current delivery path from code to customer. Choose two improvements that reduce risk and increase speed, for example adding CI and automated tests, or introducing blue‑green deployments. Measure deployment frequency and MTTR from week one. Share wins widely.

Yes. Build on your test automation skills, learn pipeline YAML, IaC and monitoring, then take ownership of quality gates. Pair with a DevOps engineer for the first few releases.

Add tasks to the story and update Remaining Work and Completed Work during the sprint. This keeps sprint burndown honest and predictable. (Source: Microsoft Learn)

Deploy smaller changes, improve automated tests, use feature flags to decouple deploy from release and add fast rollback paths. Review each incident to learn, not to blame.

Cut batch size, automate the next manual step and measure from idea to live. A short path and clear metrics remove guesswork.