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Found 14 Skills
Production-grade fault tolerance for distributed systems. Use when implementing circuit breakers, retry with exponential backoff, bulkhead isolation patterns, or building resilience into LLM API integrations.
Circuit breaker, retry, and DLQ patterns for .NET using Polly and Brighter. Use when implementing fault tolerance, handling transient failures, configuring retry strategies, or setting up dead letter queues. Includes Polly HttpClient patterns and Brighter message handler resilience.
Use when designing distributed systems, decomposing monoliths, or implementing microservices patterns. Invoke for service boundaries, DDD, saga patterns, event sourcing, service mesh, distributed tracing.
Build microservices - Spring Cloud, service mesh, event-driven, resilience patterns
Design microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.
Apply when implementing retry logic, rate limit handling, or resilience patterns in VTEX API integrations. Covers VTEX rate limit headers (X-RateLimit-Remaining, X-RateLimit-Reset, Retry-After), 429 status handling, exponential backoff with jitter, circuit breaker patterns, and request queuing. Use for any VTEX marketplace integration that must gracefully handle API throttling and maintain high availability.
Distributed systems patterns for locking, resilience, idempotency, and rate limiting. Use when implementing distributed locks, circuit breakers, retry policies, idempotency keys, token bucket rate limiters, or fault tolerance patterns.
Implement the circuit breaker pattern to prevent cascade failures in distributed systems. Use when adding resilience to API clients, external service calls, or any operation that can fail and should fail fast.
Expert in integrating third-party APIs with proper authentication, error handling, rate limiting, and retry logic. Specializes in Auth.js v5, GPT-5 model orchestration, Stripe SDK v13+, and architectural context packing for large codebases. Optimized for 2026 standards with Edge-first performance and autonomous agent integration.
Apply cloud-native architecture patterns. Use when designing for scalability, resilience, or cloud deployment. Covers microservices, containers, and distributed systems.
When designing distributed systems for scalability, reliability, and consistency. Covers CAP/PACELC theorems, consistency models (strong, eventual, causal), replication patterns (leader-follower, multi-leader, leaderless), partitioning strategies (hash, range, geographic), transaction patterns (saga, event sourcing, CQRS), resilience patterns (circuit breaker, bulkhead), service discovery, and caching strategies for building fault-tolerant distributed architectures.
Guides microservice design and delivery—bounded contexts, service boundaries, REST/gRPC/event APIs, sync vs async tradeoffs, resilience (timeouts, retries, circuit breakers, bulkheads), per-service data ownership, saga and outbox patterns, twelve-factor containers, observability (logs, metrics, trace propagation), API versioning at gateways/meshes, and contract testing. Use for microservices developer, service boundary, bounded context, gRPC between services, circuit breaker, saga pattern, outbox pattern, twelve-factor, contract testing microservices, service decomposition, or event-driven microservice—not K8s platform ops (platform-engineer, site-reliability-engineer), enterprise iPaaS (enterprise-integration-api-developer), monolith-first apps (senior-software-engineer), or classified pipelines (classified-software-devsecops-engineer).