Service decomposition & bounded contexts
Domain boundaries, business capabilities, bounded contexts, ownership, coupling, cohesion, service size, and decomposition trade-offs.
Microservices skill assessment
Measure distributed-system design and service-architecture judgement with a Microservices Assessment Test.
Assess service decomposition, bounded contexts, APIs, gateways, discovery, messaging, event-driven design, data ownership, consistency, resilience, observability, security, deployment, scaling, and architecture trade-offs.
Service boundaries & bounded contexts
APIs, gateways & service discovery
Messaging, events & data consistency
Resilience, observability & deployment
Skill signals
What this Microservices Assessment Test helps you evaluate
Measure how candidates define service boundaries, coordinate distributed workflows, manage data consistency, design for failure, observe production systems, and make practical architecture trade-offs.
API design, gateways & service discovery
REST and RPC contracts, versioning, gateways, routing, discovery, load balancing, configuration, backward compatibility, and client integration.
Synchronous & asynchronous communication
Request-response, queues, publish-subscribe, brokers, delivery guarantees, idempotency, ordering, retries, and communication trade-offs.
Event-driven architecture & messaging
Domain events, event choreography, orchestration, event schemas, consumers, dead-letter handling, replay, and event-processing design.
Data ownership & distributed consistency
Database per service, shared-database risks, sagas, outbox patterns, eventual consistency, distributed transactions, compensation, and data boundaries.
Resilience & fault tolerance
Timeouts, retries, circuit breakers, bulkheads, rate limits, graceful degradation, failover, backpressure, and failure isolation.
Observability, security & operations
Centralised logging, metrics, distributed tracing, health checks, correlation IDs, service identity, authentication, authorisation, secrets, and incident diagnosis.
Deployment, scaling & real-world scenarios
Containers, orchestration, CI/CD, rolling releases, canary deployment, autoscaling, service mesh, migrations, production failures, and practical judgement.
Assessment flow
A practical structure for fair microservices screening
Run a consistent assessment with realistic distributed-system scenarios, structured scoring, and decision-ready reports.
Set the architecture context
Choose system scale, domain complexity, service count, communication model, operational maturity, and scenario difficulty.
Run realistic microservices tasks
Candidates define service boundaries, select communication patterns, model data ownership, design resilience, and diagnose production issues.
Auto-evaluate
Score decomposition quality, pattern selection, consistency reasoning, failure handling, observability, security, and operational judgement.
Review detailed reports
Compare competency breakdowns, architecture decisions, response quality, question analysis, and evidence-based recommendations.
Score breakdown
Example microservices score areas
Boundary
Service boundaries & decomposition
92
Gateway
APIs, gateways & discovery
90
Events
Messaging & event-driven design
88
Saga
Data ownership & consistency
86
Circuit
Resilience & fault tolerance
84
Architecture scoring evaluates both design quality and failure behaviour, including how candidates trace requests, isolate faults, and preserve service reliability.
Use cases
Where this assessment fits best
Backend and microservices hiring
Evaluate service decomposition, APIs, messaging, data ownership, resilience, observability, security, deployment, and distributed-system judgement.
Senior engineering and architecture screening
Assess candidates who design service platforms, lead migrations, choose communication patterns, and manage reliability trade-offs.
Internal cloud-native development
Identify gaps in event-driven design, consistency patterns, fault tolerance, observability, delivery automation, and production operations.
Use realistic microservices scenarios, automated evaluation, and explainable score reports to improve backend, architecture, platform, cloud-native, and senior engineering hiring.
Identify candidates who can design independently deployable services that remain reliable under real-world failure.
Use structured tasks, automated evaluation, and clear reports to shortlist stronger engineering candidates faster.