Microsoft Azure
Interview Questions

Look for phased scaling approach — horizontal scaling, caching layers, database optimization, and Microsoft Azure/Azure Functions-specific patterns.

Should mention OWASP top 10 risks relevant to Microsoft Azure and Azure Functions, authentication, authorization, and input validation.

Tests data architecture skills — should consider query patterns, consistency requirements, and how Azure Functions interacts with the data layer.

Look for Microsoft Azure/Azure Functions-specific code review criteria beyond generic best practices — framework conventions, performance gotchas, and security patterns.

Tests understanding of both Azure Functions and AKS — look for nuanced comparison based on use cases, not just features.

Assess real-world Azure Functions experience — depth of knowledge, problem-solving, and results achieved.

Look for scalability thinking — performance considerations, user management, and AKS-specific best practices.

Tests practical Azure DevOps knowledge — implementation steps, dependencies, and troubleshooting experience.

Reveals the candidate's specialization, passion, and ability to articulate the strategic value of their expertise.

Tests learning agility — look for structured learning approach, resource utilization, and ability to deliver while learning.

Look for professional communication — evidence-based advocacy, willingness to compromise, and focus on outcomes over ego.

Assess continuous learning habits — official documentation, community involvement, conferences, certifications, and personal projects.

Tests leadership potential — structured knowledge sharing, patience, and ability to adjust communication to skill level.

Look for load balancing, auto-scaling, database replication, CDN, and disaster recovery planning specific to Microsoft Azure.

Should mention reserved instances, right-sizing, spot/preemptible instances, and automated scaling policies.

Look for modular approach, state management, environment isolation, Azure Functions-specific patterns, and CI/CD integration.

Tests incident response skills: diagnosis, logs analysis, rollback procedures, root cause analysis, and post-mortem practices.

Should cover golden signals (latency, traffic, errors, saturation), SLOs/SLIs, AKS-specific dashboards, and escalation procedures.

Tests debugging methodology — distributed tracing, log correlation, metric analysis, and understanding of transient failures.

Look for systematic cost analysis — billing breakdown, resource utilization review, idle resource identification, and optimization plan.

Should cover blue-green deployments, rolling updates, database migration strategies, and feature flags.

Assess practical Terraform proficiency — look for specific use cases, not just surface-level familiarity.

Look for integration patterns, error handling, data validation, and experience with REST/GraphQL APIs.

Reveals professionalism and efficiency — look for version control, code review, automation, and collaboration tools.

Tests analytical decision-making — should consider team familiarity, project requirements, long-term maintenance, and community support.