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Microsoft·Software Engineer·Onsite - System Design / Architecture·Senior

Senior
Jun 2026

Summary

System design round at Microsoft for a software engineering role. One meaty question about building an incident management agent, and they pushed into some tricky territory around role-based content and scale.

Questions Asked (1)

Q1

Design an agent that handles incident management, where different roles see different content. How would you handle scale and potential abuse?

System DesignTechnical Trade-offsAdaptability & Ambiguity
Author's notes

The role-based content part I felt okay about, access control layers, scoping what each role can see or act on.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints, then propose a high-level architecture that separates concerns: role-based access control, scalable data storage, and abuse prevention. Discuss trade-offs and how you would handle scale and abuse through layered defenses and monitoring.

Pro tip: Emphasize the importance of auditing and logging for incident management, and how you would design for least privilege and defense in depth to mitigate abuse. Also, mention that you would consider using existing Microsoft services like Azure AD for authentication and authorization to avoid reinventing the wheel.

1. Clarify Requirements

Ask questions to understand the scale (number of users, incidents per day), roles, and what 'abuse' means in this context. Clarify non-functional requirements like latency, availability, and compliance.

2. High-Level Design

Outline the main components: API gateway, authentication/authorization service, incident service, notification service, and data stores. Explain how role-based access control (RBAC) is enforced at each layer.

3. Scalability Strategy

Discuss horizontal scaling of stateless services, partitioning/sharding of data, caching, and asynchronous processing. Mention using cloud services like Azure Kubernetes Service, Azure Functions, and Cosmos DB for elasticity.

4. Abuse Prevention

Describe measures like rate limiting, input validation, anomaly detection, and audit logging. Explain how to handle malicious insiders and external attackers, and how to enforce least privilege.

5. Trade-offs and Monitoring

Summarize key trade-offs (e.g., consistency vs. availability, security vs. usability) and how you would monitor the system (metrics, alerts) to detect and respond to issues.

Key Points to Mention

  • Role-Based Access Control (RBAC) and attribute-based access control (ABAC) for fine-grained permissions.
  • Scalability patterns: horizontal scaling, sharding, caching, and asynchronous messaging.
  • Abuse prevention: rate limiting, anomaly detection, audit trails, and least privilege.
  • Use of cloud-native services (e.g., Azure AD, Azure Monitor) to leverage existing solutions.
  • Trade-offs between consistency, availability, and partition tolerance (CAP theorem) in incident data.
  • Monitoring and alerting for both performance and security incidents.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.