'saga' 검색 결과

Event Sourcing and CQRS as DDD implementation patterns — when to use, aggregate event streams, projections, snapshots, sagas, upcasting, conflict resolution

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Message queue patterns with BullMQ, Kafka, RabbitMQ - saga, outbox, dead letter queue, exactly-once semantics.

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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.

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Unified expert guide for async job queues & durable workflows: BullMQ v5 (Redis queues), Trigger.dev v3 (serverless tasks), Inngest, and Temporal.io (distributed sagas) / Panduan ahli terpadu untuk antrean job asinkron & workflow tahan-gagal: BullMQ v5, Trigger.dev v3, Inngest, dan Temporal.io.

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Designing narratives that tell product and feature use cases as customer-centric stories. Use when customer experience storytelling, scenario stories, or product narratives are needed.

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Designing workflows and state machines. Use when state transition design, invalid transition detection, Saga patterns, approval flow design, or scheduling (cron, DST-safe timing, business calendars) is needed.

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Service-oriented and microservices architecture patterns for cloud-scale systems. Covers service boundaries, API versioning and backward compatibility, eventual consistency at the API layer, idempotency keys, saga and choreography patterns, bulkheads, circuit breakers, service meshes, and the Vogels "you build it, you run it" operating principle. Use when designing service decomposition, API contracts, inter-service communication, or reviewing a proposed microservices architecture for coupling and resilience.

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设计事务边界、一致性策略、多租户隔离和数据生命周期时使用。适用于高并发写入、幂等、多租户 SaaS、软删归档和审计字段设计。融合 ACID + Saga + 乐观锁 + RLS + Tenant Per Schema。

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Work with the @upstash/workflow TypeScript/JavaScript SDK for durable, long-running workflows in serverless functions, multi-step processes that survive timeouts, retries, and restarts (built on QStash). Use when defining a workflow endpoint with serve(), running steps with context.run, sleeping for minutes to days without holding a function open, calling external APIs with context.call, waiting for an external event or webhook, invoking other workflows, configuring retries, failure callbacks, and a DLQ, controlling concurrency, rate, and parallelism, triggering, cancelling, or inspecting runs with the Workflow client, building AI agents and orchestrators, human-in-the-loop approvals, realtime updates, local development with the QStash dev server, adding middleware, or migrating workflows safely. Also use when the user asks for durable execution, step functions, saga or orchestration patterns, background jobs with checkpoints, or long-running tasks on Vercel, Next.js, Cloudflare Workers, or other serverless platforms.

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Decompose systems into microservices and apply canonical distributed-systems patterns. Use this skill whenever the user wants to split a monolith into services, design service boundaries, choose between microservices and a modular monolith, implement sagas or the outbox pattern, set up CQRS or event sourcing, configure an API gateway or BFF, add resilience (circuit breakers, retries, timeouts), or implement distributed tracing with OpenTelemetry. Also trigger for distributed transactions, service discovery, event-driven architecture, contract testing with Pact, canary releases, and idempotent consumers.

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Especialista em event sourcing, CQRS e padrões de arquitetura orientada por eventos. Domina design de event store, construção de projeções, orquestração de sagas e padrões de consistência eventual. Use PROATIVAMENTE para sistemas baseados em event sourcing, requisitos de trilha de auditoria ou modelagem de domínio complexa com consultas temporais.

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Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.

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Design durable workflows with Temporal for distributed systems. Covers workflow vs activity separation, saga patterns, state management, and determinism constraints. Use when building long-running processes, distributed transactions, or microservice orchestration.

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Expert knowledge of SED/EESSI integration in melosys-api. Use when: (1) Understanding SED document types (A001, A003, H-series, X008), (2) Debugging SED sending/receiving flows and RINA integration, (3) Working with BUC (Business Use Case) creation and management, (4) Understanding saga steps for SED handling (SEND_VEDTAK_UTLAND, SED_MOTTAK_RUTING), (5) Troubleshooting mottakerinstitusjoner (recipient institutions) issues.

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Expert knowledge of vedtak (verdict) processing in melosys-api using the saksflyt saga pattern. Use when: (1) Debugging vedtak-related issues or failures in IVERKSETT_VEDTAK_* processes, (2) Investigating race conditions where vedtak fails due to concurrent operations, (3) Understanding how fattVedtak triggers MEDL updates, letters, invoices, and case closure, (4) Tracing why vedtak got stuck or failed at specific steps, (5) Understanding the relationship between VedtakService classes and Prosessinstans, (6) Debugging issues with brev (letters), fakturering (invoicing), or MEDL registration.

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Expert knowledge of MEDL (Medlemskapsregister) integration in melosys-api. Use when: (1) Debugging MEDL period creation/update failures, (2) Understanding data mapping between domain entities and MEDL API, (3) Working with saga steps that write to MEDL (LagreMedlemsperiodeMedl, LagreLovvalgsperiodeMedl), (4) Understanding MEDL enums (PeriodestatusMedl, LovvalgMedl, DekningMedl, GrunnlagMedl), (5) Troubleshooting Article 13 provisional vs final period logic.

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Expert knowledge of Oppgave (task management) integration in melosys-api. Use when: (1) Creating, updating, or closing oppgaver (tasks), (2) Understanding task types (BEH_SAK_MK, VUR, JFR) and priorities, (3) Debugging task assignment or reuse logic, (4) Working with saga steps for oppgave handling, (5) Understanding sensitive case routing (NAV Viken vs Melosys unit).

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Expert knowledge of Altinn A1 application processing for posted workers in melosys-api. Use when: (1) Understanding Altinn søknad/skjema processing, (2) Debugging MedlemskapArbeidEOS form mapping, (3) Understanding SoeknadMapper transformations, (4) Investigating posted worker application issues, (5) Understanding the MOTTAK_SOKNAD_ALTINN saga flow.

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Expert knowledge of Behandling (case treatment) domain in melosys-api. Use when: (1) Understanding the behandling lifecycle and status transitions, (2) Debugging issues with behandling creation, status changes, or closure, (3) Understanding relationships between Fagsak, Behandling, and Behandlingsresultat, (4) Investigating why a behandling is stuck or has wrong status, (5) Understanding Behandlingstyper, Behandlingstema, Behandlingsstatus enums, (6) Debugging journalføring or SED-triggered behandling creation, (7) Understanding behandling creation via saksflyt sagas.

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Master Temporal workflow orchestration with Python SDK. Implements durable workflows, saga patterns, and distributed transactions. Covers async/await, testing strategies, and production deployment. Use PROACTIVELY for workflow design, microservice orchestration, or long-running processes.

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Expert in event sourcing, CQRS, and event-driven architecture patterns. Masters event store design, projection building, saga orchestration, and eventual consistency patterns. Use PROACTIVELY for event-sourced systems, audit trail requirements, or complex domain modeling with temporal queries.

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Builds event-driven systems. Pub/sub, competing consumers, DLQ, sagas, delivery guarantees.

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