Technical essentials

1. 01
   Your service handles requests with threads and a colleague proposes processes instead. What would you compare, and when would you push back?

   Why selected Checks concurrency fundamentals and contextual trade-offs.

2. 02
   When two transactions modify the same data at once, what anomalies can occur? What does each isolation level prevent, and what does it cost?

   Why selected Connects database fundamentals with concurrent behavior.

3. 03
   Implement a small cache that evicts the least recently used entry when full. What time cost does each operation need, and which tests do you write first?

   Why selected Examines implementation, complexity, and test design.

4. 04
   Your endpoint works in local tests, but during integration a frontend colleague insists it errors or returns nothing. What means do you use to locate the problem, and how do you produce evidence the other person will accept?

   Why selected Tests how the candidate uses evidence from both sides to debug an integration.

5. 05
   After reads move to replicas, users sometimes cannot see a change immediately after a successful write. How would you define and handle stale reads?

   Why selected Practices defining consistency expectations and architectural boundaries.

6. 06
   The local database has updated, but syncing the cache or sending a downstream message fails. How would you make the systems converge and handle retries, compensation, or manual recovery?

   Why selected Explores options, failure paths, and trade-offs in cross-system consistency.

7. 07
   The application can be rolled back, but a database migration removed an old field and the previous version can no longer start. How would you redesign release order and rollback?

   Why selected Examines rollout order, compatibility, and rollback strategy.

8. 08
   After a foundation-model change, the average score improves, but outcomes worsen for a few important customers. How would you decide whether to ship, stage, or roll back?

   Why selected Uses a model change to examine segment risk, release decisions, and rollback.

9. 09
   After code changes, the build system sometimes misses affected apps and sometimes rebuilds the entire repository. How would you validate the dependency graph and cache invalidation rules?

   Why selected Covers build graphs and selective validation in a large monorepo.

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