Technology Stack Knowledge Questions

Assess a candidate's practical and conceptual understanding of technology stacks, including major programming languages, application frameworks, databases, infrastructure, and supporting tools. Candidates should be able to explain common use cases and trade offs for languages such as Python, Java, Go, Rust, C plus plus, and JavaScript, including differences between compiled and interpreted languages, static and dynamic type systems, and performance characteristics. They should discuss application frameworks and libraries for frontend and backend development, common web stacks, service architectures such as monoliths and microservices, and application programming interfaces. Evaluate understanding of data storage options and trade offs between relational and non relational databases and the role of structured query language. Candidates should be familiar with cloud platforms such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure, infrastructure components including containerization and orchestration tools such as Docker and Kubernetes, and development workflows including version control, continuous integration and continuous delivery pipelines, testing frameworks, automation, and infrastructure as code. Assess operational concerns such as logging, monitoring and observability, deployment strategies, scalability, reliability, fault tolerance, security considerations, and common failure modes and mitigations. Interviewers may probe both awareness of specific tools and the candidate's depth of hands on experience, ability to justify technology choices by evaluating trade offs, constraints, and risk, and willingness and ability to learn and evaluate new technologies rather than claiming mastery of everything.

MediumTechnical

0 practiced

List concrete measures to harden container images and runtime in Kubernetes. Cover image selection and scanning, minimal base images, avoiding root user, filesystem restrictions, network policies, runtime security tools (AppArmor/seccomp), and secure secrets handling. For each measure briefly explain how you'd implement it operationally.

EasyTechnical

0 practiced

Describe common logging levels (debug, info, warning, error, critical). For each level give guidance on what kind of information to include, how to avoid logging sensitive data, and how to structure logs (fields/labels) so they are easy to parse and correlate across services.

HardSystem Design

0 practiced

Multiple services maintain local caches of shared data and update the authoritative store occasionally. Design a consistency protocol to keep caches coherent across services and regions. Discuss options such as event-driven invalidation, write-through/read-through caches, distributed leases, and eventual consistency trade-offs including user-facing staleness and performance.

EasyTechnical

0 practiced

Explain the role of a Dockerfile and the container lifecycle: build, image, registry, run. For a simple Node.js app describe the build and run commands you would use and list three practical ways to reduce image size and improve container security.

MediumTechnical

0 practiced

You plan to migrate a normalized relational product catalog to a document store for schema flexibility. Describe a migration plan: data extraction, transformation, verification, versioning of documents, handling queries that previously used joins, and rollback/validation strategies if issues occur in production.

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