「rollout」の検索結果

Validate system resilience through controlled fault injection. Covers hypothesis-driven chaos experiments, failure injection types (network, service, infrastructure, dependency), LitmusChaos/Chaos Mesh/AWS FIS/Gremlin/toxiproxy tooling, automated abort gating, game day planning, and progressive chaos adoption. Use when: "chaos engineering," "fault injection," "resilience test," "game day," "failure recovery," "system reliability," "blast radius." Not for: safe rollout flags/canary/dark launch during a release — use testing-in-production; designing new tests from production telemetry — use observability-driven-testing. Related: testing-in-production, observability-driven-testing, performance-testing, release-readiness, test-environments.

日本語の概要は準備中です。原文の説明を表示しています。

Scheduled probes that run CONTINUOUSLY after release. Covers probe design for critical user journeys, alerting integration, SLA validation, multi-region monitoring, and the boundary between QA and SRE. Use when: "synthetic monitoring," "uptime testing," "scheduled probes," "SLA validation," "availability monitoring," "post-deploy checks." Not for: safe-release techniques during rollout — use testing-in-production. Not for: designing tests from prod telemetry — use observability-driven-testing. Not for: a one-shot post-deploy smoke gate tied to a release — use release-readiness. Related: testing-in-production, release-readiness, performance-testing, qa-metrics.

日本語の概要は準備中です。原文の説明を表示しています。

Test AI/LLM features that ship in your product. Covers prompt regression testing, response quality evaluation, tool-call validation, hallucination and RAG grounding checks, nondeterministic-output strategies, red-team/safety scans, eval frameworks, and agent-as-target injection (indirect injection via tool output / RAG / scan reports, self-propagating payloads, data exfiltration via an agent) plus a bundled detector for untrusted content. Use when: "test our LLM feature," "prompt regression test," "eval framework," "hallucination test," "RAG grounding," "nondeterministic output," "AI feature testing," "red-team our chatbot," "indirect prompt injection," "agent reading untrusted tool output," "production AI quality." Not for: using AI to generate your own test code — use ai-test-generation. Not for: classifying CI failures with AI — use ai-bug-triage. Not for: EU AI Act / GDPR conformity of an AI feature — use compliance-testing. Not for: canary/flag rollout of an AI feature — use testing-in-production. Related: ai-test-generation, ai-qa-review, api-testing, compliance-testing, security-testing, risk-based-testing, test-data-management.

日本語の概要は準備中です。原文の説明を表示しています。

Use production telemetry as INPUT to design new tests. Covers OpenTelemetry integration with tests, trace-based assertions, log-informed test creation, production-error analysis for coverage gaps, and telemetry-driven test prioritization. Use when: "trace-based testing," "design tests from logs," "OpenTelemetry assertions," "production errors point to test gaps," "telemetry-driven testing." Not for: safe rollout techniques (flags, canary) during release — use testing-in-production. Not for: scheduled post-deploy probes — use synthetic-monitoring. Not for: triaging CI failures — use ai-bug-triage. Related: testing-in-production, synthetic-monitoring, qa-metrics, ai-bug-triage.

日本語の概要は準備中です。原文の説明を表示しています。

Mine AI coding-agent session transcripts into structured, gate-validated GPU-kernel optimization records for the wiki. Use when asked to turn vibe-coding sessions, Codex rollout logs, or Claude Code project transcripts into wiki records; to summarise what a kernel-optimization session achieved; to build or extend a session-trace store; or to re-run and validate one. Also use when asked how a session-derived record's number, snippet, or provenance was established.

日本語の概要は準備中です。原文の説明を表示しています。

Plan feature flag rollout and cleanup. Use when a mid-level developer needs controlled release guidance.

日本語の概要は準備中です。原文の説明を表示しています。

Suede Labs skill that prepares a song for sync pitching: scene and emotional angles, a supervisor-facing one-sheet, an exists/missing/unknown asset checklist covering master, instrumental, clean, and stems, screened lyric flags, mood tags, and the open clearance questions kept in their own labeled pile. Use when a track is headed for film, TV, ads, games, trailers, or creator campaigns; when a music supervisor, sync agent, or brand asks what a song is and whether it can be used; or when someone asks for a one-sheet, pitch email, or sync package for a release. Prepares review-ready materials only: never claims clearance, promises placement, or sends outreach. NOT FOR: finding and organizing the rights gaps behind an open clearance question (use suede-rights-audit); building the rights transfer package (use suede-rights-passport); linting the release folder itself (use suede-release-linter); a full rollout campaign (use suede-campaign-in-a-box).

日本語の概要は準備中です。原文の説明を表示しています。

Suede-owned programmatic SEO discipline. Use when designing data-backed keyword, location, directory, integration, or comparison pages at scale, including templates, index-worthiness gates, internal links, and rollout checks. NOT FOR: auditing an existing site (use suede-seo-audit), planning editorial content (use suede-content-strategy), or publishing bulk pages without approval.

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Suede Labs Android app factory: plan, build, test, and release a production-grade native Android app from a product idea through Google Play. Use for requests to create, ship, submit, monetize, or modernize an Android app. Covers Kotlin and Jetpack Compose architecture, API-level policy verification, accessibility, privacy and Data Safety, Play Billing, Play Integrity, account deletion, testing, performance, store assets, signing, staged rollout, and a release evidence gate. NOT FOR: iOS work (private Suede Labs companion, not in this pack: ios-app-factory), a review-only pass on an existing app (use suede-code-review), or live Play listing and keyword audits on a shipped app (use suede-aso).

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Use when a model is served online (FastAPI, BentoML) or scored in batch, when changing how a model artifact is loaded or versioned, or when adding drift, quality or prediction monitoring and a rollout plan for a new model

日本語の概要は準備中です。原文の説明を表示しています。

Prove a deploy landed — the served revision is the commit you meant, its env is present, and the product does its job — instead of trusting the deploy command's exit code. Also catches server drift before a pull or deploy. Use after any deploy, rollout, restart or server-side fix ("задеплой", "выкати", "проверь на проде", "почему не обновилось"). Loaded by devops, l3-support, infra-provisioner.

日本語の概要は準備中です。原文の説明を表示しています。

Planning releases and reporting delivery work from GitHub PR history. Use when versioning, CHANGELOGs, rollout or rollback plans, engineering metrics, retrospectives, or stakeholder reports are needed.

日本語の概要は準備中です。原文の説明を表示しています。

AI Automation Strategist: Decide what to automate: opportunity mapping, ROI, build vs buy, rollout and change management.

日本語の概要は準備中です。原文の説明を表示しています。

Prepares production launches. Use when preparing to deploy to production, or when asking what needs to be in place before shipping. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.

日本語の概要は準備中です。原文の説明を表示しています。

Launch your AI product to global attention — the playbook behind Manus, Devin, and AFFiNE's breakout launches. Covers AI-specific GTM strategy, hype cycle management, waitlist tactics, and multi-market rollout for maximum day-one impact.

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Diagnose problems before solving them: turn "X is broken and we don't know why" into a precise problem statement, verified root causes, solutions traced to those causes, and a rollout plan. Use whenever the user reports something failing, breaking, slowing, or recurring without a known cause: "sales dropped and we don't know why", "this keeps happening", "why does X keep failing", "find the root cause", "run a post-mortem", "5 whys"; Vietnamese "sao cứ bị vậy hoài", "tìm nguyên nhân gốc", "X đang hỏng mà không rõ vì sao". Trigger even when the user asks for solutions directly: "give me ideas to fix falling sales" is a diagnosis request. Not for open-ended ideation when nothing is broken (brainstorm-coach), understanding user needs (design-thinking), or company-level strategic bets (strategy-board).

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Expert guide for Feature Flags & Progressive Rollout (PostHog, LaunchDarkly, GrowthBook), A/B testing orchestration, and canary releases / Panduan ahli Feature Flags, A/B testing, dan rilis bertahap.

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MLOps and the production ML lifecycle -- model packaging and serving, CI/CD for ML, experiment tracking, model registries, reproducibility, production monitoring for data and concept drift, retraining pipelines, A/B and shadow deployment, and rollback. Covers batch vs online/real-time inference, REST endpoints, feature stores, data and version pinning, deterministic pipelines, performance-decay detection, and retraining triggers. Use when deploying models to production, serving predictions, monitoring for data or concept drift, setting up ML CI/CD, tracking experiments, managing a model registry, or planning retraining, shadow rollout, and rollback.

日本語の概要は準備中です。原文の説明を表示しています。

Manages feature implementation task state via SAM MCP tools. Use when querying task status, listing ready tasks, dispatching tasks for execution, updating task timestamps, or coordinating multi-task feature rollout. Activated by the /dh:execution orchestrator to track progress — also activates directly when managing tasks.

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设计数据库迁移、回填、灰度切换和回滚方案时使用。适用于生产表结构变更、大表迁移、数据修复和上线前评审。融合 Strangler Pattern + Expand/Contract + 双写校验 + 在线 DDL。

日本語の概要は準備中です。原文の説明を表示しています。

Run a real-task benchmark suite against OpenClaw agents so model or harness changes can be compared before they hit production workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Manages ArgoCD application syncs using the argocd CLI and the Argo CD REST API (v1alpha1). Supports progressive delivery with Argo Rollouts integration and automated health checks via Kubernetes readiness probes.

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Manages ArgoCD Application and ApplicationSet resources for Kubernetes GitOps deployments. Uses the ArgoCD REST API and argocd CLI to automate sync waves, health checks, and progressive rollout configurations.

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Manages ArgoCD application sync waves and hooks using the ArgoCD API and argocd CLI. Coordinates multi-application deployment ordering with sync-wave annotations, health checks, and progressive rollout gates.

日本語の概要は準備中です。原文の説明を表示しています。