architecture-serverless

Estrelas7

Forks0

Atualizado17 de fevereiro de 2026 às 08:24

Serverless architecture workflow for event-driven and bursty workloads using managed compute and platform services. Use when elasticity and reduced platform operations justify managed-service constraints; do not use when workload shape requires long-lived stateful control loops.

Instalação

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

Fonte

KentoShimizu

KentoShimizu/sw-agent-skills

Abrir repositório GitHub Ver repositórios do creator

Download

Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Administradores de redes e sistemas de computadorInformática e Matemática·SOC 15-1244

SKILL.md

readonly

name	architecture-serverless
description	Serverless architecture workflow for event-driven and bursty workloads using managed compute and platform services. Use when elasticity and reduced platform operations justify managed-service constraints; do not use when workload shape requires long-lived stateful control loops.

Architecture Serverless

Overview

Use this skill to design serverless systems that are cost-aware, failure-tolerant, and operationally predictable.

Scope Boundaries

Traffic is variable or bursty and elastic scaling is valuable.
Team capacity for infrastructure operations is limited.
Workloads are naturally event-driven or request/response with bounded execution.

Core Judgments

Compute model: function granularity, execution time bounds, and concurrency profile.
State model: where session/process state lives outside function runtime.
Integration model: event source guarantees, retry semantics, and idempotency.
Cost model: invocation frequency, cold-start impact, data transfer/storage economics.

Practitioner Heuristics

Keep functions narrow by business action, not by tiny technical helpers.
Externalize state deliberately (DB/cache/object store) and design for retries.
Control concurrency at event source and downstream dependency limits.
Treat timeouts as business behavior decisions, not only platform defaults.

Workflow

Profile workload shape and latency/cost sensitivity.
Design event and request paths with explicit idempotency rules.
Choose managed services for state, orchestration, and messaging.
Define concurrency limits and backpressure behavior.
Model cost and failure behavior under peak and degraded conditions.
Record escape hatches for workloads that outgrow serverless constraints.

Common Failure Modes

Hidden coupling through shared environment variables and broad IAM policies.
Unbounded retries causing duplicate side effects.
Cost surprises from chatty event chains and storage/egress growth.

Failure Conditions

Stop when critical workflows cannot tolerate at-least-once delivery semantics.
Stop when latency SLOs are incompatible with runtime startup behavior.
Escalate when concurrency or cost risk cannot be bounded.

Mais deste repositório

mesmo repositório

debug-root-cause

KentoShimizu/sw-agent-skills

Systematic debugging workflow for isolating software root causes, implementing proportional fixes, and verifying recovery with reproducible evidence. Use when application/runtime failures, regressions, or flaky behavior are observed and the task requires both diagnosis and remediation. When specialized skills are available in the environment, defer GitHub Actions failure triage to `github-fix-ci`, commit-introduction isolation to `git-bisect-debugging`, profiler-led hotspot analysis to `performance-profiling`, active security incident command to `security-incident-response`, and postmortem-only reporting to `incident-postmortem`. Do not use for broad feature implementation or speculative hardening without evidence.

2026-03-027

api-design-rest

KentoShimizu/sw-agent-skills

Resource-oriented REST/OpenAPI contract design for URI/method semantics, idempotency, pagination, and HTTP status behavior. Trigger when REST contract diffs are detected in paths, methods, schemas, or status semantics, or when request-response transport choice is still unresolved before implementation. Do not use for GraphQL schema authoring, error-taxonomy-only changes, version lifecycle governance, or consumer-provider contract test implementation.

2026-02-177

ab-testing

KentoShimizu/sw-agent-skills

Controlled online experiment workflow for product changes with causal inference, randomization integrity checks, and pre-registered decision criteria. Trigger when ship/no-ship decisions require causal evidence under uncertainty and KPI trade-offs must be quantified. Do not use for feature-flag rollout policy without experiment design, deterministic functional verification, or observability-only analysis.

2026-02-177

testing-contract

KentoShimizu/sw-agent-skills

Provider-consumer compatibility testing for service interface changes. Use when APIs or event schemas evolve and executable contract checks must guard compatibility before release; do not use for UI-only validation or architecture topology decisions.

2026-02-177

testing-e2e

KentoShimizu/sw-agent-skills

End-to-end test planning for critical user journeys across integrated systems. Use when release confidence depends on browser/API/dependency behavior as one flow; do not use for isolated unit behavior or pure contract checks.

2026-02-177

testing-regression-strategy

KentoShimizu/sw-agent-skills

Risk-based regression suite curation for release gating under time and budget limits. Use when teams must decide what runs always versus conditionally by impact and risk; do not use for implementing a single test type in isolation.

2026-02-177

name	architecture-serverless
description	Serverless architecture workflow for event-driven and bursty workloads using managed compute and platform services. Use when elasticity and reduced platform operations justify managed-service constraints; do not use when workload shape requires long-lived stateful control loops.

Architecture Serverless

Overview

Use this skill to design serverless systems that are cost-aware, failure-tolerant, and operationally predictable.

Scope Boundaries

Traffic is variable or bursty and elastic scaling is valuable.
Team capacity for infrastructure operations is limited.
Workloads are naturally event-driven or request/response with bounded execution.

Core Judgments

Compute model: function granularity, execution time bounds, and concurrency profile.
State model: where session/process state lives outside function runtime.
Integration model: event source guarantees, retry semantics, and idempotency.
Cost model: invocation frequency, cold-start impact, data transfer/storage economics.

Practitioner Heuristics

Keep functions narrow by business action, not by tiny technical helpers.
Externalize state deliberately (DB/cache/object store) and design for retries.
Control concurrency at event source and downstream dependency limits.
Treat timeouts as business behavior decisions, not only platform defaults.

Workflow

Profile workload shape and latency/cost sensitivity.
Design event and request paths with explicit idempotency rules.
Choose managed services for state, orchestration, and messaging.
Define concurrency limits and backpressure behavior.
Model cost and failure behavior under peak and degraded conditions.
Record escape hatches for workloads that outgrow serverless constraints.

Common Failure Modes

Hidden coupling through shared environment variables and broad IAM policies.
Unbounded retries causing duplicate side effects.
Cost surprises from chatty event chains and storage/egress growth.

Failure Conditions

Stop when critical workflows cannot tolerate at-least-once delivery semantics.
Stop when latency SLOs are incompatible with runtime startup behavior.
Escalate when concurrency or cost risk cannot be bounded.