Cloud Computing Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

1. Why Cloud Interview Preparation Matters

Organisations are shifting more of their applications, data, and networks to the cloud—relying on platforms like AWS, Microsoft Azure, and Google Cloud to remain competitive. As a result, cloud‑focused roles are in high demand. Here’s why structured preparation is so essential:

1. Demonstrate Technical Depth

   • Hiring managers need to see that you’ve mastered core computer science principles—data structures, algorithms, networking, security—while also being able to apply them in distributed, on‑demand environments.

2. Prove Versatility

   • Cloud engineering may span infrastructure-as-code (Terraform, AWS CloudFormation, Azure Resource Manager), container orchestration (Kubernetes), continuous delivery pipelines (Jenkins, GitLab CI), and more.

   • Be prepared to show comfort with multiple tools and how they fit together in a holistic DevOps approach.

3. Emphasise Design for Scalability & Resilience

   • Architectural questions often involve redundancy, disaster recovery, multi‑region deployments, and microservices.

   • Companies want to know you can design systems that meet SLAs and rapidly adapt to changes in demand.

4. Optimise Cost & Performance

   • Part of being a cloud specialist is understanding pricing models and performance trade‑offs.

   • Show how you’d pick the right instance types, design effective auto-scaling, and implement efficient storage strategies.

5. Highlight Security & Compliance

   • The cloud environment demands strong IAM (Identity and Access Management) policies, encryption, and compliance with data regulations (GDPR, ISO standards).

   • Employers look for candidates who prioritise security-by-design.

Proper preparation ensures you’ll handle both coding and system design questions with confidence. Below, we’ll cover 15 coding interview prompts and 15 architecture scenarios you might encounter in a cloud interview.

2. 15 Real Coding Interview Questions

Even in cloud‑centric interviews, coding prowess is crucial. From automating infrastructure tasks to writing robust, scalable applications, you’ll need a firm grasp of data structures, algorithms, and best practices. Below are 15 coding questions that interviewers frequently ask when hiring cloud engineers or developers.

Coding Question 1: Implement a Scalable File Upload Service

Question: Write the back‑end logic (in the language of your choice) for a service that accepts file uploads and stores them in a cloud storage bucket (e.g., AWS S3, Azure Blob Storage).
What to focus on:

• Handling multipart file uploads.

• Generating pre‑signed URLs or using direct uploads.

• Error handling, including large file edge cases.

Coding Question 2: Circular Buffer for Log Management

Question: Implement a circular buffer data structure to store logs. Once the buffer is full, it overwrites the oldest logs.
What to focus on:

• Efficient enqueue and dequeue operations.

• Ensuring thread safety if logs come from multiple sources.

• Potential usage in real‑time cloud logging.

Coding Question 3: Rate Limiter

Question: Create a rate limiter function (e.g., token bucket or sliding window) to throttle incoming API requests.
What to focus on:

• Time complexity and concurrency (thread-safe if needed).

• Handling burst traffic.

• Integration with cloud gateway solutions (e.g., Amazon API Gateway).

Coding Question 4: Query a Relational Database in Batches

Question: Write a method that queries large datasets from a cloud database (e.g., Amazon RDS) in configurable batch sizes to avoid memory overruns.
What to focus on:

• Database pagination strategies.

• Error handling if a batch fails.

• Minimising round‑trip latency to the database.

Coding Question 5: Simple Job Scheduler

Question: Implement a simplified version of a job scheduler that runs tasks at given intervals.
What to focus on:

• Data structures for task scheduling.

• Handling tasks that might overrun their time slot.

• Potential integration with AWS Lambda or Azure Functions.

Coding Question 6: Network‑Intensive App

Question: Write a function that parallelises API calls to multiple endpoints and aggregates the results.
What to focus on:

• Use of threads, async/await, or promises (depending on language).

• Handling timeouts, retries, and partial failures.

• Relevance to cloud microservices architecture.

Coding Question 7: Microservice Health Check

Question: Develop a snippet that checks the health of multiple microservices and returns an aggregated status.
What to focus on:

• Clear indication of healthy, unhealthy, or degraded states.

• Handling HTTP status codes.

• Relevance for Kubernetes readiness/liveness probes.

Coding Question 8: Encrypting Sensitive Data

Question: Given a secret string and a KMS (Key Management Service) key identifier, demonstrate how you’d encrypt/decrypt data securely.
What to focus on:

• Use of a cloud provider’s KMS APIs (AWS KMS, Azure Key Vault, GCP KMS).

• Least privilege principle for key usage.

• Error handling (rotated keys, permission denial).

Coding Question 9: Implement a Caching Layer

Question: Create a function that fetches data from a database but caches results in a distributed cache (e.g., Redis, Memcached) to reduce latency.
What to focus on:

• Cache expiry/invalidation strategies.

• Handling cache miss vs. cache hit.

• Potential race conditions if multiple processes update the cache simultaneously.

Coding Question 10: Auto‑Scaling Simulation

Question: Write a simulation of an auto‑scaling policy where instances scale up or down based on CPU utilisation metrics.
What to focus on:

• Data structures to maintain current CPU usage.

• Trigger thresholds and cool‑down periods.

• Representing cloud compute instances in code.

Coding Question 11: Containerised App Deployment Script

Question: Write a script that pulls a Docker image from a container registry and runs it with specified environment variables.
What to focus on:

• Handling Docker commands programmatically.

• Dealing with environment variable injection.

• Error handling (image not found, port conflicts).

Coding Question 12: Log Parsing and Aggregation

Question: Given a stream of JSON log entries, parse and aggregate them (e.g., count occurrences of a certain field) in near real time.
What to focus on:

• Stream‑based approach (line by line or chunk by chunk).

• Potential usage of concurrency for high throughput.

• Relevance to cloud logging systems (CloudWatch Logs, Azure Monitor).

Coding Question 13: Load Balancing Simulation

Question: Implement a round-robin or weighted load‑balancing algorithm that distributes incoming requests among available servers.
What to focus on:

• Data structures to track server states.

• Weighted vs. standard round‑robin.

• Potential integration with cloud load balancers (ELB, ALB).

Coding Question 14: Cloud Messaging Queue

Question: Show how you’d publish and consume messages from a cloud messaging service (e.g., AWS SQS, Azure Service Bus).
What to focus on:

• Polling mechanism vs. push.

• Handling dead-letter queues.

• Idempotency concerns with repeated messages.

Coding Question 15: Generate Infrastructure as Code

Question: Write a script or snippet to create a virtual machine (EC2 in AWS or VM in Azure) using an SDK or CLI, specifying instance size, network configuration, and security groups.
What to focus on:

• Parameterising resource settings (e.g., instance size).

• Handling authentication with the cloud provider.

• Networking details like subnet or firewall rules.

When practising these coding problems, focus on efficiency, error handling, and clarity. The best solutions blend strong technical fundamentals with the practicalities of cloud environments—especially around concurrency, security, and resilience.

3. 15 System & Architecture Design Questions

Cloud interviewers often spend significant time on architecture questions, gauging your ability to design scalable, secure, and cost‑effective solutions. Below are 15 key system design scenarios you might encounter, each illustrating different aspects of cloud infrastructure and best practices.

System Design Question 1: E‑Commerce Platform

Scenario: Build a scalable e‑commerce platform that can handle flash sales and user spikes.
Key Points to Discuss:

• Microservices for cart, user management, payments.

• Use of serverless for event-driven flows.

• Database choices: relational for transactions vs. NoSQL for catalogue.

System Design Question 2: Multi‑Region Disaster Recovery

Scenario: Design a system for a financial institution that needs near real‑time failover to another region if the primary region fails.
Key Points to Discuss:

• Data replication (synchronous vs. asynchronous).

• RPO (Recovery Point Objective) and RTO (Recovery Time Objective).

• DNS routing (Route 53, Azure Traffic Manager) for automatic failover.

System Design Question 3: Data Warehouse for Analytics

Scenario: A global retailer wants to analyse sales data from multiple sources in near real time.
Key Points to Discuss:

• ETL or ELT pipelines with tools like AWS Glue, Azure Data Factory.

• Columnar storage (Redshift, BigQuery, Synapse).

• Partitioning strategies, data lifecycle management.

System Design Question 4: CI/CD Pipeline for a SaaS App

Scenario: Construct a fully automated deployment pipeline, from code commit to production release.
Key Points to Discuss:

• Version control triggers (GitHub, GitLab).

• Unit/integration tests, container builds, vulnerability scans.

• Deployment strategies (blue-green, canary releases).

System Design Question 5: Messaging‑Based Microservices

Scenario: An IoT platform streams sensor data to the cloud for processing and analytics.
Key Points to Discuss:

• Publish‑subscribe models (Kafka, AWS SNS/SQS).

• Data ingestion using serverless or streaming services (AWS Kinesis, Azure Event Hubs).

• Downstream processing (Lambda functions, Databricks notebooks).

System Design Question 6: High‑Throughput API Gateway

Scenario: Your organisation needs an API layer that handles millions of requests daily, with minimal latency.
Key Points to Discuss:

• Edge caching (CloudFront, Azure Front Door).

• Global load balancing to route traffic to the nearest region.

• Authentication and authorisation (OAuth2, JWT, OpenID Connect).

System Design Question 7: Zero Downtime Database Migration

Scenario: Migrate from an on‑premises database to a cloud database with no downtime.
Key Points to Discuss:

• Change data capture (CDC) or replication tools (AWS DMS).

• Cutover plan, DNS updates.

• Possible use of read replicas before switching write operations.

System Design Question 8: Container Orchestration Platform

Scenario: Implement a multi‑tenant Kubernetes cluster to deploy microservices for different product teams.
Key Points to Discuss:

• Namespace isolation and resource quotas.

• Deployment strategies (rolling updates, blue‑green).

• Integration with a service mesh (Istio, Linkerd) for observability and security.

System Design Question 9: Event‑Driven Serverless Architecture

Scenario: Build a serverless application that processes user‑uploaded images (thumbnail generation, metadata extraction).
Key Points to Discuss:

• Trigger from cloud object storage (S3, Azure Blob).

• Lambda or Functions approach for on‑demand processing.

• Potential concurrency limits and cost monitoring.

System Design Question 10: Secure Multi‑Layer Network

Scenario: You need to design a VPC (Virtual Private Cloud) or VNet with private subnets, NAT gateways, bastion hosts, and multiple tiers of security groups.
Key Points to Discuss:

• Segregating public and private layers.

• Minimising exposure (no direct SSH to private servers).

• Centralised logging (VPC flow logs, firewall logs).

System Design Question 11: Hybrid Cloud Setup

Scenario: A company wants to maintain part of its infrastructure on‑premises but use the cloud for bursting workloads.
Key Points to Discuss:

• VPN or Direct Connect for secure connectivity.

• Load balancing across on‑prem and cloud resources.

• Synchronising data stores, identity management (Active Directory, etc.).

System Design Question 12: Monitoring & Alerting

Scenario: You must create a monitoring and alerting stack for a large microservices architecture.
Key Points to Discuss:

• Metrics collection (Prometheus, CloudWatch, Azure Monitor).

• Alert rules and escalation policies (PagerDuty, OpsGenie).

• Logging strategies (centralised log aggregation, distributed tracing).

System Design Question 13: Data Lake for Unstructured Data

Scenario: Your team is responsible for storing, processing, and analysing vast amounts of raw data.
Key Points to Discuss:

• Object storage solutions (S3, Azure Data Lake).

• Schema‑on‑read approach vs. schema‑on‑write.

• Tools (Hadoop, Spark, Athena, Databricks).

System Design Question 14: Global SaaS Product

Scenario: Architect a globally accessible SaaS platform with data residency compliance (GDPR, etc.).
Key Points to Discuss:

• Multi‑region or multi‑account strategy.

• Local data storage for compliance (EU region).

• Handling user data requests (right to be forgotten).

System Design Question 15: Serverless Chat Application

Scenario: Create a near real‑time chat application that scales based on the number of active users, with minimal operational overhead.
Key Points to Discuss:

• WebSocket or real‑time streaming using services like AWS AppSync, Azure Web PubSub.

• Data store for user sessions (DynamoDB, Cosmos DB).

• Handling message ordering and ephemeral vs. persistent chat history.

When addressing system design questions, make sure to discuss:

• Service selection: Why you’d choose specific managed services or architectures.

• Scalability & fault tolerance: Multi‑AZ or multi‑region strategies, load balancing, container orchestration.

• Security & cost: The interplay between strong security posture and budget constraints.

4. Tips for Conquering Cloud Job Interviews

Conquering a cloud interview requires more than just technical know‑how. It demands effective communication, problem‑solving, and the ability to demonstrate real‑world experience. Here are some tips to help you succeed:

1. Revise Core CS Fundamentals

   • Many cloud challenges boil down to data structures, algorithms, and operating systems fundamentals.

   • Brush up on networking (TCP, HTTP, load balancing) and distributed systems (consistency models, eventual consistency, partition tolerance).

2. Focus on Practical Cloud Skills

   • Showcase hands‑on experience with CI/CD, container orchestration (Kubernetes/ECS), infrastructure‑as‑code (Terraform/CloudFormation), and logging/monitoring solutions.

   • If you have side projects or open‑source contributions, highlight them to show your real‑world skills.

3. Explain Design Choices Clearly

   • When describing architecture decisions (e.g., AWS Lambda vs. EC2, or microservices vs. monolith), walk the interviewer through your rationale.

   • Emphasise trade‑offs (performance vs. cost, complexity vs. flexibility).

4. Prepare for Behavioural Questions

   • “Tell me about a time you handled an outage” or “Describe a conflict with a teammate” are common.

   • Use the STAR method (Situation, Task, Action, Result) to give concise, structured answers.

5. Emphasise Security Best Practices

   • Cloud roles often involve dealing with production workloads that handle sensitive data.

   • Bring up encryption at rest, encryption in transit, principle of least privilege, and network segmentation.

6. Practice Whiteboarding & Live Coding

   • Many interviews include a whiteboard or online code editor portion. Speak your thoughts aloud to show logical reasoning.

   • Even partial solutions can impress if you demonstrate solid thought processes.

7. Highlight Observability

   • Discuss how you’ve monitored logs, metrics, and traces, plus how you’ve alerted on anomalies.

   • Observability is crucial in diagnosing cloud system issues quickly.

8. Stay Current with Cloud Trends

   • The cloud space changes rapidly—keep up with new services, popular patterns (serverless, containers, ephemeral environments).

   • Reading official blogs (AWS, Azure, GCP) and relevant trade press can give you conversation‑starting knowledge.

9. Ask Relevant Questions

   • End the interview by asking about the organisation’s cloud adoption, future roadmap, or ongoing architectural challenges.

   • Shows genuine interest and helps you gauge if it’s the right environment for you.

10. Show Enthusiasm & Adaptability

• Cloud computing is dynamic. Employers value candidates who embrace learning new tools, pivot quickly, and drive innovation.

• Convey how you adopt and experiment with emerging cloud services.

A thoughtful balance of technical acumen, strong communication, and real-world insight can help you shine in any cloud interview.

5. Final Thoughts

Cloud computing continues to transform how businesses operate, offering unmatched scalability, innovation, and speed to market. In turn, cloud careers are both rewarding and demanding—requiring a blend of software engineering, system architecture, and DevOps expertise.

By working through these 30 real coding & system-design questions, you can hone the skills you need to excel in interviews. From coding tasks that test concurrency and reliability, to architectural scenarios exploring multi‑region failover and serverless patterns, your preparedness will set you apart in a competitive job market.

When the time comes to find your next role, look no further than www.cloud-jobs.co.uk. It’s an excellent resource for discovering the latest openings in the UK’s cloud ecosystem—whether you’re aiming for a Cloud Solutions Architect position or a DevOps Engineer slot in a fast‑growing start‑up.

Best of luck, and may your next cloud interview be the gateway to an inspiring new chapter in your career!