In depth knowledge of Microsoft Azure platform services, architecture trade offs, operational considerations, and best practices. Candidates should be able to discuss compute options such as Azure Virtual Machines sizing, availability sets and zones, maintenance windows, and scale sets; storage options including Azure Storage account types, redundancy and replication choices, and backup strategies; database offerings such as Azure SQL Database, managed instances, high availability and replication patterns; networking fundamentals including Azure Virtual Network design, subnetting, network security groups, peering, service endpoints and private links, and load balancing with Application Gateway and Azure Load Balancer; container orchestration and related considerations such as Azure Kubernetes Service concepts, cluster sizing, upgrades, and networking models; serverless and platform services such as Azure Functions and event driven architectures; infrastructure as code and deployment pipelines using Azure DevOps and templates; identity and secrets management with Azure Active Directory and Azure Key Vault including secret rotation; monitoring, logging, and cost optimization strategies; and security, compliance, and disaster recovery planning across these services. Interview evaluation focuses on architectural reasoning, trade off analysis, operational runbook concerns, scaling and performance tuning, failure modes and recovery, and automation using provider native tooling.
MediumTechnical
93 practiced
Design node pool sizing and scaling strategy for an AKS cluster that must run both stateless microservices and heavy nightly batch jobs. Discuss node pool segmentation, spot/preemptible node usage, GPU node handling, use of taints/tolerations, cluster-autoscaler and HPA settings, and safe upgrade strategies to reduce disruption during maintenance.
MediumTechnical
95 practiced
You're creating a repeatable, low-cost demo environment for customer product demos. Describe how you'd provision, automate, and teardown demo environments using Azure services and IaC; include recommended resource sizing, cost caps, sample data generation strategies, techniques to simulate production-like latency/scale, and steps to ensure security and isolation for customer access.
HardSystem Design
100 practiced
Design a production-grade observability strategy using Azure Monitor, Log Analytics, Application Insights, and OpenTelemetry for a microservices app. Specify which telemetry to collect (traces, metrics, logs), sampling and retention policies to control cost, SLO/SLA definitions, alerting strategy, and how to instrument services for distributed tracing cross-language.
EasyTechnical
79 practiced
You are preparing a customer demo. Explain how you'd choose an Azure Virtual Machine (VM) series and size for a compute-heavy application that runs nightly batch jobs. Include considerations such as CPU-to-memory ratios, disk I/O and disk types, network bandwidth, pricing models (on-demand, reserved, spot), potential bursting behavior, and any telemetry/benchmarks or tooling you'd request from the customer to make a final recommendation. Frame your answer as you would to a technical application owner.
MediumTechnical
91 practiced
A finance stakeholder asks how to reduce the customer's monthly Azure bill without degrading performance. Propose a practical roadmap including rightsizing, Reserved Instances and Savings Plans, Azure Hybrid Benefit, autoscaling, spot VMs for noncritical workloads, storage tiering and lifecycle policies, and detecting cost anomalies. Explain how you'd quantify and present potential savings and associated risks.
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