Familiarity with Modern Tech Stacks: Interview Questions to Ask

Hiring skilled developers is harder than ever, with 87% of tech leaders in the U.S. struggling to find qualified candidates. Modern technologies like React, Kubernetes, and Python dominate the industry, but traditional hiring practices often fail to assess real expertise. This article breaks down how to craft interview questions that reveal practical skills, problem-solving abilities, and hands-on experience with modern tech stacks.

Key takeaways:

• Modern tech stacks include tools like React, Python, and Kubernetes, focusing on scalability and performance.
• Effective interview questions should test practical knowledge (e.g., debugging Kubernetes Pods or optimizing Python scripts) rather than theoretical familiarity.
• Platforms like daily.dev Recruiter streamline hiring by connecting you with developers already active in modern ecosystems.

Here’s how to ask targeted, skill-based questions for React, Kubernetes, Python, and full-stack roles to find candidates who can handle complex challenges.

::: @figure {Modern Tech Stack Interview Questions: Key Statistics and Hiring Insights}

Interview Questions for React Developers

React commands about 40.14% of the web framework market share . Instead of simply asking, "Do you know React?" focus on questions that reveal how candidates apply React to solve real-world problems.

Core React Concepts and Features

Start with the basics to test a candidate's understanding of React's core mechanisms. For example, you could ask: "Can you explain how the Virtual DOM works and why it improves performance?" A well-rounded answer should cover how React uses an in-memory representation of the DOM, employs a diffing algorithm to identify changes, and updates only the necessary DOM nodes. This approach avoids costly full-page re-renders, making React applications faster and more efficient .

For state management, consider asking: "When would you use the Context API instead of Zustand or Redux, and why?" A good response should highlight that the Context API is suitable for low-frequency updates like authentication or theme data but may cause performance issues with high-frequency updates due to widespread re-rendering. Candidates should also compare the lightweight, hook-based structure of Zustand with Redux Toolkit's ability to handle complex state management scenarios.

Once you've covered these foundational topics, you can move on to more performance-focused questions.

Advanced React Topics

To gauge a candidate's expertise in optimization, ask: "How would you identify and fix performance bottlenecks in a React application?" A strong candidate might mention using the React DevTools Profiler to analyze render times and locate inefficient components . They should also discuss techniques like using React.memo to minimize unnecessary re-renders, useMemo to cache expensive calculations, and useCallback to stabilize function references. However, they should also acknowledge that overusing these tools can increase complexity and memory usage .

Project-Based React Questions

Project-based questions are a great way to explore a developer's hands-on experience. For instance: "Can you describe a time when you built a reusable component library? How did you manage prop validation, set default values, and document the components?" This question sheds light on their architectural skills and their focus on creating a seamless developer experience.

Another insightful question is: "How did you handle rendering 10,000 items in a list within a React application?" A solid answer should include strategies like windowing or virtualization, using tools such as react-window to render only the visible items in the viewport . If a candidate suggests rendering all items at once, it may indicate a lack of experience with large-scale applications.

Interview Questions for Kubernetes Knowledge

Kubernetes expertise is highly sought after, with approximately 26,000 job openings in the U.S. and average salaries ranging from $144,030 to $202,202 . Misconfigurations are a major issue, contributing to about 70% of production incidents . When interviewing candidates, it's important to evaluate their skills in deployment, scaling, and troubleshooting. These questions can help uncover the depth of their knowledge.

Core Kubernetes Concepts

Start by gauging their understanding of Kubernetes fundamentals. For instance, ask: "Can you explain the role of the API Server, etcd, and the Scheduler in a Kubernetes cluster?" A strong answer should include an explanation of the API Server as the central point for all REST commands, the role of etcd in storing the entire cluster state as the single source of truth, and the Scheduler's responsibility for assigning Pods to nodes based on resource needs. Candidates should also mention how the Kubelet ensures containers run as specified and how Kube-proxy manages network rules for Pod communication.

Another key question is: "What's the difference between a Deployment, StatefulSet, and DaemonSet?" Candidates should clarify that Deployments are used for stateless applications where Pods are interchangeable, StatefulSets handle stateful applications that require stable network identities and persistent storage (like databases), and DaemonSets ensure one Pod runs on each node for cluster-wide tasks such as logging or monitoring.

Scaling and Optimization

To test their understanding of scaling, ask: "How does the Horizontal Pod Autoscaler calculate the desired number of replicas?" A well-informed candidate should reference the formula:

desiredReplicas = ceil(currentReplicas * (currentMetricValue / desiredMetricValue))

. They should also explain that the HPA controller syncs every 15 seconds and includes a 5-minute stabilization period to prevent frequent scaling changes .

Follow up with: "What's the difference between horizontal and vertical scaling in Kubernetes, and when would you avoid using both together?" Candidates should explain that horizontal scaling increases the number of Pod replicas, making it ideal for stateless applications, while vertical scaling adjusts the CPU and memory requests for existing Pods, which is more suitable for stateful workloads. They should also note that using both HPA and VPA simultaneously on the same resource can cause instability .

Troubleshooting in Kubernetes

Troubleshooting questions are a great way to assess practical experience. For example, ask: "Walk me through your process for debugging a Pod stuck in CrashLoopBackOff." A thoughtful response would include using kubectl describe pod to review Events, kubectl logs --previous to check for crash causes, and examining exit codes (e.g., 137 for OOMKilled) . As Jason Miller, Career Coach at Verve AI, advises:

"I'd start by checking pod events and logs, then verify resource requests and liveness/readiness probes; many CrashLoopBackOffs are app-level crashes or misconfigured probes" .

Another practical scenario to explore is: "How would you diagnose why a Pod is running but not receiving traffic from its Service?" Candidates should highlight the importance of checking the readinessProbe configuration, as Kubernetes only routes traffic to Pods that pass their readiness checks .

Interview Questions for Python Developers

Python continues to dominate the programming world, with over 50% of developers using it by 2025 and job opportunities growing by 27% year over year. Yet, traditional resume screening still overlooks 73% of skilled developers . To better identify candidates who can deliver production-ready code, consider adjusting your interview strategy to focus 70% on scenario-based questions - like debugging, scaling, and optimization - and 30% on theoretical knowledge . As Prit Bakraniya from Utkrusht.ai puts it:

"Great Python devs know more than syntax - they excel at problem-solving, scaling, testing, and writing clean, maintainable code" .

Frameworks and APIs

Start by testing candidates on their understanding of frameworks through real-world scenarios. For example, ask: "Can you explain the difference between Django's Model-View-Template architecture and Flask's Blueprint pattern?" Candidates should highlight how Django's MVT structure integrates components like its ORM, admin, and authentication seamlessly , while Flask uses Blueprints with explicit integrations such as SQLAlchemy . Jason Lewis, a hiring manager, notes:

"Django's components work together seamlessly, making it a popular choice among Python developers for web development projects" .

To assess API skills, try this: "How would you optimize a FastAPI endpoint that's experiencing slow response times?" Strong candidates might suggest strategies like caching with Redis, adding database indexing, preventing N+1 query issues with eager loading, and leveraging FastAPI's async capabilities . Follow up with a security question: "How do you implement CSRF protection and secure password hashing in your applications?" Look for mentions of using JWT for authentication and tools like werkzeug.security for password hashing .

Once you've covered frameworks and APIs, shift the focus to how candidates handle data and use Python libraries effectively.

Data Handling and Libraries

To test data-handling abilities, ask: "What would you do if you need to process a 10GB CSV file, but your system only has 8GB of RAM?" Candidates should mention using pd.read_csv() with chunksize or tools like Dask for processing large datasets . They might also bring up the usecols parameter to load only necessary columns or optimizing memory usage by converting data types (e.g., int64 to int32) .

Another insightful question is: "When would you use vectorized operations instead of a for loop in Pandas?" Candidates should explain that vectorization leverages optimized C and Fortran libraries in NumPy to process entire arrays faster than Python loops . You could even ask them to refactor a loop-based operation into a vectorized one. For handling missing data, see if they know how to use fillna() for filling gaps or interpolate() for estimating missing values in time-series data .

After testing their data skills, evaluate their familiarity with modern tools and debugging techniques.

Python Development Tools

Ask: "What is the advantage of using Poetry over a requirements.txt file?" Candidates should explain that Poetry automates dependency resolution, creates a poetry.lock file for version pinning, and simplifies the build, packaging, and publishing process .

For asynchronous programming, try: "When would you use asyncio, and what's the benefit of the yield keyword in Python?" Candidates should identify asyncio as ideal for high-performance, I/O-bound tasks and explain that yield enables memory-efficient generators that produce values one at a time instead of returning full lists . Finally, test their debugging skills with: "How would you use the Python Debugger (PDB) to troubleshoot a complex 500 error in production?" This question reveals their practical problem-solving abilities and familiarity with essential debugging tools .

Behavioral and Cross-Stack Questions

When assessing full-stack developers, it’s not just about their technical skills. Their ability to work across different tech stacks and make informed decisions is what sets exceptional developers apart. With full-stack roles now among the top 15% of in-demand tech jobs , and web development positions projected to grow by 7% between 2024 and 2034, it’s crucial to ask questions that uncover their cross-stack expertise and problem-solving abilities .

Working Across Multiple Stacks

"How do you ensure smooth collaboration when working with multiple tech stacks on a single project?" This question helps gauge a candidate’s approach to managing complexity. Strong answers might include using RESTful APIs or GraphQL for consistent communication between components , adhering to principles like SOLID, KISS, and DRY to maintain clean and efficient code , or employing CI/CD pipelines to automate builds and quickly identify integration issues .

"What are the trade-offs between using MERN versus MEAN for a real-time streaming application?" Candidates should highlight that MERN, with React, offers a modular and component-based architecture, while MEAN, featuring Angular, provides a unified JavaScript environment better suited for handling real-time data streaming .

"When would you choose PostgreSQL over MongoDB?" This question tests their understanding of database strengths. PostgreSQL excels in scenarios requiring strong data integrity and complex queries, while MongoDB is better for handling unstructured data efficiently .

These types of questions naturally lead into discussions about broader project-level decision-making.

Project Decision-Making

"Describe a project where you chose a tech stack and explain your reasoning." A good response will go beyond listing technologies, explaining the logic behind their choices - such as picking a database for its ability to handle read-heavy workloads or selecting a framework based on the team’s familiarity . They might also weigh trade-offs like balancing "Time to Market" with "Long-term Sustainability", noting that while some tools speed up development with extensive libraries, they could come with higher maintenance demands or steep learning curves .

"When would you start with a monolithic architecture versus microservices?" This question reveals their strategic thinking. Candidates should recognize that a modular monolith is often ideal for early-stage startups, allowing them to achieve product-market fit quickly. Transitioning to microservices should only occur when scaling demands it. As DistantJob aptly puts it:

"The overhead of microservices (managing multiple codebases, deployment pipelines, and operational complexity) is a massive distraction that can kill a company [at the early stage]" .

"Describe a situation where you debugged issues across multiple tech stacks. How did you identify and resolve it?" This question probes their troubleshooting skills. Look for structured approaches, such as isolating the problem to the UI layer, API communication, or server-side logic . Candidates might share examples like resolving issues with optimistic updates, where the frontend temporarily reflects changes before backend confirmation, requiring logic to revert the state if the API returns an error .

These questions not only assess technical acumen but also provide insight into how candidates approach complex, real-world challenges.

Conclusion

The Value of Structured Technical Evaluation

Crafting effective interview questions is key to uncovering a developer's problem-solving abilities and practical expertise. While whiteboard tests might fall short of reflecting real-world scenarios, questions rooted in actual job challenges provide a clearer picture of how well a candidate fits the role . For instance, asking candidates to explain their technology choices or how they would debug complex issues across different tech stacks helps you assess their decision-making and hands-on experience - concepts highlighted in the React, Kubernetes, and Python examples earlier.

Structured evaluations not only make the hiring process more efficient but also reduce bias by focusing on practical, role-specific skills. Senior engineers might tackle architectural problem-solving, while junior developers face simpler, task-oriented challenges . As Team CodeSignal puts it:

"Traditional algorithm questions can be useful for assessing core problem-solving skills, but don't fully simulate the job of a software developer" .

With the U.S. Bureau of Labor Statistics projecting a 7% growth in web development jobs from 2024 to 2034 - more than double the average job growth rate - the demand for skilled full-stack developers remains high . A sharp, practical, and candidate-friendly interview process is essential to attract top talent. This underscores the importance of tools and platforms that connect you directly with qualified developers.

Using daily.dev Recruiter for Targeted Hiring

To address the challenges of finding the right talent, daily.dev Recruiter offers a solution tailored for hiring in today’s competitive market. Even the best interview questions won’t matter if you don’t have access to skilled candidates. With daily.dev Recruiter, you’re connected to pre-qualified developers through warm, double opt-in introductions, cutting out the inefficiencies of traditional outreach.

Unlike platforms that depend on outdated resumes or scraped data, daily.dev Recruiter is built on an active professional network where developers engage daily. This means higher reply rates, precise targeting, and a hiring experience designed with developers in mind. When you pair structured technical evaluations with a platform that delivers the right talent, you're not just filling vacancies - you’re building teams capable of thriving in the modern tech landscape.

FAQs

What are the main differences between the MERN and MEAN stacks for building real-time applications?

The MERN and MEAN stacks share the same back-end technologies - MongoDB, Express, and Node.js - making both capable of handling real-time features like WebSockets or Socket.io with ease. The main difference lies in their front-end frameworks: MERN integrates React, while MEAN uses Angular.

React’s one-way data flow and virtual DOM allow for precise control over user interface updates, which is especially useful in applications requiring high-frequency, real-time rendering. However, React often needs additional tools like Redux to manage state effectively. On the flip side, Angular offers two-way data binding and comes with built-in component libraries, making it easier to handle server-pushed updates without extra dependencies. That said, Angular's larger framework can sometimes introduce extra overhead.

In short, MERN is a go-to choice for lightweight, flexible apps with tailored UI requirements. Meanwhile, MEAN suits developers looking for a more structured framework with built-in features for real-time applications.

What steps should I take to troubleshoot a Kubernetes Pod stuck in CrashLoopBackOff?

To troubleshoot a Kubernetes Pod stuck in a CrashLoopBackOff state, here’s what you can do:

• Find the problematic pod: Use the following command to list pods and locate the one in a CrashLoopBackOff state:

  kubectl get pods | grep CrashLoopBackOff
  

  Note down the pod name and its namespace for further investigation.

• Examine pod details: Run this command to get a detailed description of the pod:

  kubectl describe pod <pod-name> -n <namespace>
  

  Look for clues like restart counts, error messages, or reasons such as OOMKilled or failed health probes.

• Check container logs: Logs can reveal common issues like syntax errors, missing environment variables, or runtime exceptions. Use the command:

  kubectl logs <pod-name> -n <namespace> --previous
  

• Review resource settings: If the pod is being terminated due to resource constraints, you may need to adjust its CPU or memory allocation. For instance:

  resources:
    requests:
      memory: "256Mi"
      cpu: "250m"
    limits:
      memory: "512Mi"
      cpu: "500m"
  

• Inspect liveness and readiness probes: Misconfigured probes can cause unnecessary restarts. Check their settings and, if needed, temporarily disable them to confirm they’re the issue.

Once you’ve pinpointed the problem, update the pod configuration and redeploy it. Keep an eye on the pod to ensure it successfully transitions to a Running state.

Why is hands-on experience more important than theoretical knowledge in tech stack interviews?

Hands-on experience plays a key role in showcasing a candidate's ability to put their skills into action. It highlights how well they can tackle real-world challenges using the tools and frameworks required in practical settings, moving beyond just a theoretical grasp of concepts.

By prioritizing practical knowledge, interviewers can gain deeper insights into a candidate's problem-solving abilities, flexibility, and preparedness to contribute to real projects. This method ensures that candidates are equipped to navigate the intricacies of modern tech stacks in a professional setting.