▸case-01 We are designing an event-driven payment and order processing system from scratch. Could you produce a detailed architectural specification that details individual service responsibilities, inter-service API contracts, distributed transaction handling, resilience mechanisms, and operational guidelines for deployment? | fail→fail | 44,323 | 38,736 | -13% | 1 | 1 | 0% | 8,237 | 6,842 | -17% | 0 | 0 | — |
▸case-02 We have an existing e-commerce monolith handling orders, inventory, and billing where all modules query a single shared SQL database. Provide a database refactoring plan to decouple these modules into independent microservices. | pass→pass | 16,640 | 28,569 | +72% | 1 | 1 | 0% | 3,106 | 4,562 | +47% | 0 | 0 | — |
▸case-03 Our payment service calls an external gateway API over HTTP. High latency from the payment gateway during peak hours causes worker pool exhaustion and cascades failures across upstream order services. Design a mitigation mechanism for this inter-service dependency. | pass→pass | 18,668 | 26,981 | +45% | 1 | 1 | 0% | 2,979 | 4,556 | +53% | 0 | 0 | — |
▸case-04 We are building an order execution flow requiring sequential updates across Order, Inventory, Payment, and Shipping services. Synchronous 2-phase commit protocol is causing severe latency locks. Provide an architectural pattern to maintain consistency across these services without global locks. | pass→pass | 21,567 | 20,583 | -5% | 1 | 1 | 0% | 3,049 | 3,377 | +11% | 0 | 0 | — |
▸case-05 Our Order service must save order details to PostgreSQL and publish an OrderCreated event to Apache Kafka. We must guarantee that the event is never lost if the process crashes after the DB commit. What design pattern ensures atomic persistence and messaging? | pass→pass | 13,374 | 14,872 | +11% | 1 | 1 | 0% | 2,019 | 2,786 | +38% | 0 | 0 | — |
▸case-06 We are migrating a legacy monolithic web application to microservices. We cannot afford a total system rewrite or extended downtime. Design a migration strategy that incrementally routes incoming HTTP traffic from the monolith to new services. | pass→pass | 18,033 | 18,134 | +1% | 1 | 1 | 0% | 3,004 | 3,236 | +8% | 0 | 0 | — |
▸case-07 A mobile application currently makes 12 separate REST calls directly to individual microservice endpoints to build the user home screen, resulting in high latency and payload over-fetching. What architectural component should be placed between clients and backend services? | pass→pass | 6,564 | 11,095 | +69% | 1 | 1 | 0% | 1,104 | 2,015 | +83% | 0 | 0 | — |
▸case-08 In our auto-scaling cloud environment, microservice container instances are assigned dynamic IP addresses upon startup. How should service instances dynamically locate network addresses of dependent services? | pass→pass | 12,548 | 18,975 | +51% | 1 | 1 | 0% | 2,094 | 3,070 | +47% | 0 | 0 | — |
▸case-09 When an end-user request fails across a call chain of 6 microservices communicating via gRPC and REST, engineers struggle to trace the request execution path. Detail how to instrument these microservices to track individual requests end-to-end. | pass→pass | 23,820 | 20,483 | -14% | 1 | 1 | 0% | 3,872 | 4,400 | +14% | 0 | 0 | — |
▸case-10 Intermittent packet loss between internal microservices causes immediate request failures during transient network blips. How should client libraries structure retry behavior to prevent hammering struggling target services? | pass→pass | 16,236 | 18,090 | +11% | 1 | 1 | 0% | 2,689 | 3,385 | +26% | 0 | 0 | — |
▸case-11 Our analytics queries require complex aggregation across millions of records, slowing down transactional OLTP write operations on the primary order table. How can we separate heavy read workloads from high-frequency write operations? | pass→pass | 16,336 | 14,122 | -14% | 1 | 1 | 0% | 2,583 | 2,671 | +3% | 0 | 0 | — |
▸case-12 A slow recommendation engine service is consuming all available HTTP client threads on the API Gateway, preventing critical authentication requests from processing. What resilience pattern isolates thread pools per target dependency? | pass→pass | 7,037 | 9,840 | +40% | 1 | 1 | 0% | 884 | 1,489 | +68% | 0 | 0 | — |
▸case-13 We need to select a high-performance inter-service communication protocol for internal microservice calls where low latency, binary serialization, and bi-directional streaming are required over synchronous HTTP/JSON. What technology should be evaluated? | pass→pass | 13,883 | 17,178 | +24% | 1 | 1 | 0% | 1,977 | 2,672 | +35% | 0 | 0 | — |
▸case-14 Teams frequently break downstream integration environments when changing microservice API request payloads without notifying consumer teams. What automated testing methodology verifies API compatibility without deploying full end-to-end environments? | pass→pass | 13,231 | 16,329 | +23% | 1 | 1 | 0% | 2,045 | 3,039 | +49% | 0 | 0 | — |
▸case-15 Our engineering department is struggling to split a large enterprise application into logical microservice boundaries. What strategic domain analysis technique should be used to establish service responsibility boundaries? | pass→pass | 15,653 | 15,328 | -2% | 1 | 1 | 0% | 2,192 | 2,132 | -3% | 0 | 0 | — |
▸case-16 We need a release strategy for our Inventory microservice that routes 5% of production traffic to the new software release while monitoring error rates before rolling it out to 100% of instances. What deployment strategy matches this requirement? | pass→pass | 9,508 | 11,031 | +16% | 1 | 1 | 0% | 1,312 | 2,030 | +55% | 0 | 0 | — |
▸case-17 When a user changes their profile address in User Service, three independent services (Billing, Shipping, Marketing) must be notified without creating synchronous HTTP runtime dependencies between User Service and the rest of the system. What interaction pattern should be implemented? | pass→pass | 7,060 | 8,537 | +21% | 1 | 1 | 0% | 1,277 | 1,718 | +35% | 0 | 0 | — |
▸case-18 Microservice instances across multiple cloud regions need consistent feature flags and database connection pool settings that can be updated dynamically without triggering container restarts. What infrastructure pattern addresses this? | pass→pass | 14,165 | 17,925 | +27% | 1 | 1 | 0% | 1,945 | 2,842 | +46% | 0 | 0 | — |
▸case-19 Uncontrolled bursts of client traffic are overwhelming downstream internal microservices, leading to memory exhaustion and crash loops. What traffic management strategy should be enforced at ingress? | pass→pass | 11,404 | 15,075 | +32% | 1 | 1 | 0% | 1,720 | 2,357 | +37% | 0 | 0 | — |
▸case-20 We are building an internal administrative dashboard for 10 internal employees to manage user permission flags on a single PostgreSQL database. Should we architect this system as a suite of 5 distributed microservices? | pass→pass | 11,890 | 8,801 | -26% | 1 | 1 | 0% | 1,795 | 1,492 | -17% | 0 | 0 | — |
▸case-21 Our team is competing in a 48-hour hackathon to build a proof-of-concept concept app. Should we setup an API Gateway, event-driven Sagas, distributed tracing, and separate microservice repositories? | pass→pass | 15,390 | 13,418 | -13% | 1 | 1 | 0% | 1,985 | 1,953 | -2% | 0 | 0 | — |
▸case-22 We are a startup with 2 junior backend engineers and no DevOps or infrastructure personnel. We want to decompose our simple REST API into 15 microservices across a Kubernetes cluster. What architecture should we choose? | pass→pass | 17,150 | 18,425 | +7% | 1 | 1 | 0% | 2,626 | 2,861 | +9% | 0 | 0 | — |