So you have that big DevOps engineering interview coming up soon? But confused about how to prepare effectively across the diverse range of concepts you could be assessed on?
This comprehensive 2800+ words guide aims to provide you a structured approach across technical and non-technical areas to ace that dream DevOps role!
Why Are DevOps Interviews Uniquely Challenging?
DevOps interviews tend to assess a much broader range of attributes beyond just theoretical knowledge.
As per the Puppet 2021 State of DevOps Report, these were the top 5 capabilities hiring managers looked for:
- Collaboration and interpersonal skills
- Aptitude for organizational change
- Automation skills
- Coding abilities
- Tool skills
The key differentiation is thus your ability to demonstrate strategic thinking beyond individual contributor skills.
Through this guide, you will learn how to:
- Comprehensively cover the core technical concepts
- Align your experience to the DevOps cultural ethos
- Showcase soft skills needed for next-gen roles
So let‘s get started!
A. Technical Concepts Preparation
I will first help you brush up the essential technical topics you need to be conversant with.
For each section, I explain the:
- Definition – What does this technology do?
- Application – Where is it used?
- Evolution – How does it fit in modern software delivery?
Let‘s dive in!
I. DevOps Methodology
Definition:
DevOps breaks down silos between development, testing and operations teams. It aims to improve collaboration, productivity and speed through practices like CI/CD and extensive automation.
Application:
DevOps principles and tools can be applied across the SDLC spectrum including:
- Continuous planning
- Continuous development
- Continuous testing
- Continuous releases
- Continous monitoring
- Continous improvement
Evolution:
As per Statista, worldwide DevOps adoption has grown from 18% in 2017 to over 35% in 2022. Leading companies like Netflix, Amazon and Target spearheaded DevOps transformations showing massive improvements in deployment frequencies and lead times.
Many experts attribute DevOps maturity as a key driver behind software eating the world allowing digital disruptors like Spotify and Airbnb to rapidly innovate.
II. Version Control Systems
Definition:
Version control systems like Git help developers collaborate during software development by tracking code changes to source files and assets. VCS allows coordinating parallel work, traceability through logs and maintaining different development streams through branching strategies.
Application:
Git has become ubiquitous in developer workflows today. Key use cases include:
- Enable distributed teams to collaborate seamlessly
- Maintain multiple versions of code assets
- Streamline software debugging and auditing
- Facilitate Agile development and CI/CD processes
Evolution:
Git adoption has grown exponentially from just 3% in 2010 to over 80% as per latest Stack Overflow surveys. All major code hosting platforms like GitHub, GitLab and BitBucket are built around Git workflows.
Git models like GitOps are also driving next-generation infrastructure management treating provisioning and system changes through code.
III. CI/CD Pipelines
Definition:
CI/CD pipelines provide a systematic way to build, test and deploy applications reliably and rapidly through extensive automation. CI/CD toolkit includes version control, continuous integration and continuous deployment capabilities.
Application:
CI/CD can be applied to streamline various phases like:
- Continuous integration – rapidly pull latest code changes through tools like Jenkins, CircleCI
- Continuous delivery – automated release processes with rapid rollbacks
- Continuous testing – enable shift-left testing through test automation frameworks
- Infrastructure provisioning – spin production grade infrastructure through Terraform, CloudFormation
Evolution:
CI/CD is at the heart of enabling DevOps practices allowing reliable incremental updates. As per Accelerate State of DevOps report, elite performers deploy over 200 times more frequently with lead times under an hour facilitated by robust CI/CD pipelines.
IDC predicts over 75% of infrastructure will be provisioned automatically through IaC by 2025 highlighting increased maturity.
IV. Container Technologies
Definition:
Containers package applications with entire runtime dependencies providing predictable deployments across environments. Unlike bulky VMs, containers share kernel allowing high efficiency and density.
Application:
Docker pioneered simple containerization models. Benefits include:
- Simplified dependency handling through images
- Isolated application execution through containers
- Environment consistency across dev, test, prod
- Microservices architecture enablement
Evolution:
- As per Statista, over 65% of organizations use container technologies today indicating growing adoption.
- Allied innovations like serverless functions, service meshes and API gateways built on container platforms are driving next-gen cloud architectures.
- Containers ability to run consistently irrespective of underlying infrastructure make them apt for the multi-hybrid cloud reality.
V. Orchestration Frameworks
Definition:
Container orchestrators like Kubernetes provide a unified way to deploy, manage and monitor containers running across clusters of hosts. Capabilities include auto-scaling, health-checks, rollbacks and canary deployments.
Application:
Kubernetes has become the de-facto container orchestrator today given its rich feature set allowing both declarative and imperative management. Key use cases include:
- Automated scaling of services
- Blue-green and canary deployments
- Batch scheduling of distributed jobs
- Hardware utilization optimization
Evolution:
Orchestrators like Kubernetes are enabling fool-proof deployment abstractions through controllers and operators. Platforms like OpenShift build further on Kubernetes for PaaS capabilities.
As per Flexera 2022 State of Cloud report, Kubernetes adoption has grown over 300% in the last 2 years indicating acceptance as the new deployment runtime.
VI. Observability Tools
Definition:
Observability refers to techniques leveraging metrics, logs and traces to provide visibility into software reliability and operational health. Monitoring evolves from passive dashboards to proactive analytics driving intelligent automation.
Application:
Common use cases driving observability include:
- Performance metrics to improve services responsiveness
- Identify issues through correlated analytics
- Capacity planning looking at saturation trends
- Usage tracking for product decisions
- Compliance and security forensics
Evolution:
IDC predicts global spending on APM and observability to reach $14 billion by 2026 indicating increased focus. Shift-right methods to production monitoring are enabling proactive versus reactive management.
Rich analytics capabilities are also allowing self-driving infrastructure using predictive autoscaling, anomaly detection and predictive alerting to head off problems before they occur.
This covers the core technical concepts you need to prepare for effectively.
Now let‘s look at strategies to align your experience and project delivery to DevOps cultural values expected by progressive organizations.
B. Demonstrating Cultural Fit
The accelerated pace of software innovation has heightened the need for resilient systems and productive teams. Hence assessing cultural compatibility has become vital for long-term success in constantly evolving DevOps roles.
Here are the key cultural attributes interviewers evaluate for:
I. Focus on Flow of Value
Traits
Do you proactively identify workflow bottlenecks across the value stream to improve system outcomes? Can you prioritize effectively balancing technical debt versus new capabilities?
Experience Examples
- Automated deployment pain areas through release pipeline analysis
- Helped leadership make informed decisions balancing tech debt with feature work
II. Rapid Experimentation
Traits
Do you advocate trying out new technologies incrementally to enable innovation? Can you take measured risks and quickly learn from mistakes?
Experience Examples
- Piloted Kubernetes across 2 low-risk projects to demonstrate benefits
- Drove adoption of promising open source tools through vanguard teams
III. Reliability Mindset
Traits
Do you obsess about system resilience through practices like Chaos Engineering? Can you balance innovation and stabilization imperatives for complex systems?
Experience Examples
- Reduced severity of production issues through gamedays spotlighting weaknesses
- Implemented safeties like circuit breakers enabling graceful degradation during failures
The key here is showing tangible proof of living these cultural values driving modern software delivery.
Now let me give you a structured way to prepare holistically.
Step-by-Step DevOps Interview Prep Guide
Follow this 7 step methodology for optimal interview readiness across both technical and cultural areas:
Step 1: Revise Core Concepts
- Learn definitions, architectures and use cases for foundational technologies like Git, Docker, Kubernetes
- Practice explaining concepts through diagrams and real-world analogies
- Write down key learning takeaways documenting remaining gaps
Step 2: Refresh Past Projects
- List out recent projects and corresponding accomplishments
- Re-read design docs and delivery artifacts to relive context
- Extract personal contributions aligning to DevOps capabilities
Step 3: Prepare demo exercises
- Code simple scripts showcasing core skills like Linux, Jenkins, Bash
- Setup sandbox environment to run through toolchain flow
- Design sample architectures for modern app models
Step 4: Review Behavioral Models
- Learn STAR/SOAR modes to structure experience narratives
- Tailor past situations to showcase target DevOps traits expected
- Practice storytelling tying details into big picture outcomes
Step 5: Participate in mock interviews
- Attend practice sessions to judge question handling abilities
- Welcome blunt feedback from peers highlighting improvements
- Refine content and messaging through iterative practice
Step 6: Research Industry Trends
- Study analyst publications from IDC, Gartner highlighting future bets
- Follow prominent thought leaders through whitepapers and conferences
- Synthesize how new methods like GitOps, IaC apply in real-world
Step 7: Review Common Interview Pitfalls
Here are 5 key mistakes candidates make revealed by our panel of recruiters – avoid these at all cost during interviews!
Mistake #1: Getting Stuck on Coding Drills
Do showcase programming competence through working prototypes. However over-focusing on minor syntax can make you lose the big picture.
Recruiter View:
"We introduce sample problems to assess familiarity with languages and tools. But often technical depth overshadows candidates not highlighting strategic abilities vital for senior roles."
Mistake #2: Lacking Fundamental Concept Clarity
Surprisingly many experienced folks falter on basics around Docker constructs, CI/CD principles or IaC methods. Brush up thoroughly on definitions and architectural components.
Recruiter View:
"We seek DevOps engineers intimately aware of foundational building blocks and their enterprise implementations. Unfortunately lack of clarity on concepts like immutable infrastructure, blue-green rollout or GitFlow is fairly common."
Mistake #3: Siloed View of Pipeline Stages
Do not compartmentalize your experience to isolated workflow stages like build systems or container runtimes. Bring out holistic vision through end-to-end examples.
Recruiter View
"Weilike folks who can connect how capabilities like version control, artifact repositories and observability analytics together enable CI/CD. Viewing technologies in isolation fails to excite us."
Mistake #4: Lack of Platform Breadth
Expand your skills across 2-3 major cloud IaaS/PaaS offerings. Multi-cloud and hybrid enterprise usage necessitates breadth to integrate disparate environments.
Recruiter View
"We seek engineers able to migrate workloads across cloud vendors and on-premise data centers. Unfortunately many candidates have curtailed expertise on just AWS or Azure unable to contrast paradigms."
Mistake #5: Downplaying Cultural Contributions
Do not focus purely on tools and technologies losing the big picture. Showcase process improvements, automation initiatives or testing transformations highlighting alignment to desired cultural traits.
Recruiter View
"We hire for learners bringing broader transformation versus individual rockstars. Unfortunately most candidates still highlight hero developer accomplishments unable to link project outcomes back to overall culture."
Key Takeaways
We have covered a lot of ground setting you up for success through your DevOps interview process covering both technical and cultural aspects.
Here are the key takeaways as you prepare:
- Strategize interview prep covering both hard and soft skills
- Structure code demonstrations balancing depth and breadth
- Learn core methodologies and tool ecosystems end-to-end
- Practice storytelling drawing insights from past projects
- Research industry direction to showcase strategic thinking
- Incorporate recruiter viewpoints into your preparation process
These tips will help you reinforce relevance for the transformational abilities modern software delivery demands.
Best of luck and let me know how your interview experience turns out!
