'event-driven' 검색 결과

Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub. Use when ", gcp, cloud-run, serverless, containers, pubsub" mentioned.

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Expert guide for Composable MACH Architecture (Microservices, API-first, Cloud-native, Headless) — dynamic UI composition, federated API mesh, Backend-for-Frontend patterns, plugin/extension architectures, event-driven composition, and composable AI routing / Panduan ahli Arsitektur MACH Komposabel — komposisi UI dinamis, API mesh federasi, pola Backend-for-Frontend, arsitektur plugin/ekstensi, komposisi event-driven, dan routing AI komposabel.

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Evaluates regulatory decision impact with approval probability, timeline analysis, and outcome scenario modeling for event-driven positions. Use when analyzing regulatory events, evaluating FDA/FCC/DOJ decisions, or modeling regulatory outcomes.

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AWS serverless and event-driven architecture expert based on Well-Architected Framework. Use when building serverless APIs, Lambda functions, REST APIs, microservices, or async workflows. Covers Lambda with TypeScript/Python, API Gateway (REST/HTTP), DynamoDB, Step Functions, EventBridge, SQS, SNS, and serverless patterns. Essential when user mentions serverless, Lambda, API Gateway, event-driven, async processing, queues, pub/sub, or wants to build scalable serverless applications with AWS best practices.

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Ensure event-driven designs specify delivery guarantees, ordering, idempotency, schema evolution, and replay/backfill strategy.

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Inngest expert for serverless-first background jobs, event-driven workflows, and durable execution without managing queues or workers. Use when: inngest, serverless background job, event-driven workflow, step function, durable execution.

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Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub.

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Inngest expert for serverless-first background jobs, event-driven workflows, and durable execution without managing queues or workers. Use when: inngest, serverless background job, event-driven workflow, step function, durable execution.

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Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub.

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Quarkus 3.x LTS의 기능 추가와 오류 수정을 테스트부터 진행합니다. API, 이벤트, 비동기 처리를 검증하고 테스트를 통과하는 구현과 커버리지 확인을 지원합니다.

• 테스트부터 작성해 REST API 추가
• 오류 재현 및 수정
• Apache Camel 경로와 이벤트 처리 검증

Java의 Quarkus 서비스 설계와 검토를 지원합니다. REST API 구성, Panache 데이터 접근, Camel 메시지 연계와 비동기 처리의 구현 패턴을 제공합니다.

• REST API의 책임 분리
• Camel과 RabbitMQ 연계
• Panache 저장 처리 검토

Notion 페이지와 데이터베이스를 검색하고 수정하며 Markdown 읽기와 쓰기, 파일 업로드를 수행합니다. 외부 데이터 정기 동기화와 이벤트 연동용 Workers도 만듭니다.

• 회의 메모를 Notion에 저장합니다
• 지정한 상태의 데이터를 찾습니다
• 이미지와 자료를 업로드합니다

Claude Code의 도구 실행 전후와 종료 시 작동하는 훅을 만들도록 돕습니다. 위험한 작업 검증, 완료 확인, 시작 시 정보 불러오기를 설정하고 테스트까지 다룹니다.

• 실행 전 명령과 파일 쓰기 확인
• 에이전트 종료 전 작업 완료 확인
• 시작 시 프로젝트 정보 불러오기

Coordinate groups of AI agents in the cloud with Flow Nexus. Assign research or development tasks, automate workflows triggered by events or schedules, and monitor execution, queues, and agent capacity through the platform's tools.

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• Split research and analysis across multiple agents
• Coordinate development across repositories
• Automate testing, builds, and deployment

Build and test SimPy models of queues, production, logistics, and other event-driven systems. Set execution limits, monitor waiting times and resource use, and analyze repeated runs with recorded random seeds for reproducible results.

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• Comparing waiting times with different staffing levels
• Modeling shared equipment in production or logistics
• Testing priority queues and interrupted work

Design AWS applications that run without managing servers and respond to events. Get guidance on Lambda APIs, asynchronous workflows, retries, monitoring, and scaling, with implementation patterns based on the AWS Well-Architected Framework.

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• Designing APIs backed by Lambda
• Building asynchronous job processing
• Coordinating services with Step Functions

Design connections between APIs and services, including webhooks, which notify other systems when events occur. Define event formats, retries, duplicate prevention, and recovery steps for workflows such as order processing and data pipelines.

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• Designing webhook notifications between services
• Connecting authentication, orders, and payments
• Planning recovery when a multi-service workflow fails

Review system architecture and major design changes for scalability, resilience, and maintainability. Identify risks, compare design tradeoffs, and document recommendations and next steps across services, APIs, data storage, security, and deployment.

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• Reviewing microservice boundaries
• Assessing a move to event-driven architecture
• Comparing serverless and container deployment

Build Claude Code plugin hooks: automated checks triggered by tool use or session events. Get guidance on prompt and command hooks for validating actions, checking task completion, loading context, and testing configurations.

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• Checking dangerous commands before execution
• Verifying completion before the agent stops
• Loading project context when a session starts

Move slow Python operations into background jobs so requests can return promptly. Use task queues and workers, the processes that execute queued work, with retry rules, duplicate handling, time limits, and persistent job status.

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• Send emails and notifications in the background
• Generate reports and data exports asynchronously
• Process uploads and media conversions

Design and implement Saga workflows across services, using compensating actions to undo completed work after failures. Define step deadlines, handle repeated messages safely, and monitor stalled order, booking, or other long-running processes.

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• Coordinating orders across inventory, payment, and shipping services
• Designing compensation for failed bookings
• Investigating workflows stuck during compensation

Plan microservices by defining service responsibilities, communication methods, and data ownership. Use patterns for gradual migration, distributed transactions, and failure isolation to design systems made of independently responsible services.

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• Gradually splitting a monolithic system into services
• Defining service responsibilities and interfaces
• Designing event-based communication and distributed transactions

Structure research on war, sanctions, and supply disruptions using risk indicators and scenarios. Map potential effects across stocks, commodities, and currencies, then examine warning signals, defensive allocations, and possible market reversals as a crisis eases.

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• Organize early warning indicators for geopolitical crises
• Trace sanctions and shipping disruptions through supply chains
• Compare crisis scenarios across asset classes

Build AWS applications with managed services that reduce server administration. Follow patterns for Lambda functions, HTTP APIs, database access, and queued background processing, with guidance on deployment and delays when functions first start.

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• Build HTTP APIs with Lambda and API Gateway
• Read and write application data in DynamoDB
• Process SQS messages with retries and a dead-letter queue