クラウド、CI/CD、監視、デプロイ（6,730 件）
概要と使いどころ
Production readiness checklist for Apify Actor deployments. Use when deploying an Actor to production, preparing for launch, or validating Actor configuration, scheduling, monitoring, and rollback before going live. Trigger with "apify production", "deploy actor to prod", "apify go-live", "apify launch checklist", "actor production ready".
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。
Deploy Apollo.io integrations to production. Use when deploying Apollo integrations, configuring production environments, or setting up deployment pipelines. Trigger with phrases like "deploy apollo", "apollo production deploy", "apollo deployment pipeline", "apollo to production".
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。
Optimize Apify platform costs through memory tuning, compute unit management, and proxy budgeting. Use when analyzing Apify billing, reducing Actor run costs, or implementing usage monitoring and budget alerts. Trigger with "apify cost", "apify billing", "reduce apify costs", "apify pricing", "apify expensive", "apify budget", "compute units".
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。
Deploy Apify Actors and integrate scraping into external applications. Use when deploying an Actor to the platform, integrating Actor results into a web app (Next.js, Express), wiring webhooks, or scheduling scraping pipelines. Trigger with "deploy apify actor", "apify Vercel integration", "apify production deploy", "integrate apify results", "apify API endpoint".
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。
Set up observability for Claude API integrations with metrics, logging, and alerting for latency, cost, errors, and token usage. Trigger with phrases like "anthropic monitoring", "claude observability", "anthropic metrics", "track claude usage", "claude dashboard".
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。
Production-grade architecture patterns for Apify-powered applications. Use when designing scraping infrastructure, building multi-Actor pipelines, or integrating Apify into a larger system architecture. Trigger with "apify architecture", "apify best practices", "apify project structure", "scraping architecture", "apify system design".
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。
Choose and implement Claude API architecture patterns for different scales: serverless, microservice, event-driven, and edge deployment. Trigger with phrases like "anthropic architecture", "claude serverless", "claude microservice design", "edge claude deployment".
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。
Configure CI/CD pipeline for automated Figma-to-code generation with Anima. Use when automating design-to-code in GitHub Actions, setting up PR-based component generation, or integrating Anima into design handoff workflows. Trigger with: "anima CI", "anima GitHub Actions", "anima automated generation".
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。
Optimize Anthropic Claude API costs with model routing, prompt caching, batching, and spend monitoring. Use when analyzing Claude API billing, reducing costs, or implementing cost controls and budget alerts. Trigger with phrases like "anthropic cost", "claude billing", "reduce claude spend", "anthropic budget", "claude pricing optimize".
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。
Deploy Anima design-to-code service as a backend API endpoint. Use when building a design-to-code microservice, deploying Anima SDK as a serverless function, or creating an internal design tool API. Trigger with: "deploy anima", "anima service deploy", "anima serverless".
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。
Production readiness checklist for Anima design-to-code pipelines. Use when deploying automated design-to-code services, preparing CI/CD Figma-to-code automation, or validating output quality before production. Trigger with: "anima production", "anima go-live", "anima prod checklist".
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。
Deploy Claude API integrations to production cloud environments. Use when deploying Claude-powered services to Docker, Cloud Run, ECS, or Kubernetes with proper secret management and health checks. Trigger with phrases like "deploy anthropic", "claude production deploy", "ship claude integration", "anthropic cloud deployment".
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。
Instrument an Algolia integration for actionable availability, latency, freshness, relevance, and event-health signals. Use when defining dashboards, alerts, traces, or service objectives. Trigger with "monitor Algolia", "Algolia metrics", or "search observability".
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。
Aggregate and centralize performance metrics from applications, systems, databases, caches, and services. Use when consolidating monitoring data from multiple sources. Trigger with phrases like "aggregate metrics", "centralize monitoring", or "collect performance data".
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。
Deploy an Alchemy-backed service through environment-scoped credentials, chain assertions, canaries, and rollback gates. Use when promoting an integration to hosted environments. Trigger with "deploy Alchemy integration", "Alchemy production deploy", or "promote an Alchemy service".
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 and verify deployment of an Algolia-backed application with separated browser and server credentials. Use when releasing search code, index configuration, or event instrumentation. Trigger with "deploy Algolia", "Algolia production rollout", or "search release checklist".
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。
Issue an evidence-backed production decision across Adobe auth, entitlements, API versions, data custody, async reliability, spend, observability, and rollback. Use before launch or a material integration change. Use when the task requires adobe production readiness decision. Trigger with "Adobe production checklist", "approve Adobe launch", or "Adobe go-live review".
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。
Deploy an Adobe-backed service or App Builder application with isolated environments, immutable artifacts, canaries, observability, and rollback. Use when the task requires adobe integration deployment. Trigger with "deploy Adobe integration", "aio app deploy", or "promote Adobe app".
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 and control a staged Abridge rollout across clinical cohorts and EHR workflows without pretending to deploy vendor infrastructure. Use when preparing an Abridge pilot or expansion. Trigger with "plan the Abridge rollout".
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。
Instrument Adobe integrations with redacted structured logs, request/job/activation correlation, service-level indicators, alerts, and evidence retention. Use when the task requires adobe content-safe observability. Trigger with "monitor Adobe API", "Adobe observability", or "App Builder logs".
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。
Deploy and orchestrate Vertex AI ADK agents using A2A protocol. Manages AgentCard discovery, task submission, Code Execution Sandbox, and Memory Bank. Use when asked to "deploy ADK agent" or "orchestrate agents". Trigger with phrases like 'deploy', 'infrastructure', or 'CI/CD'.
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。
Scaffold production-ready AI agents on Google's Agent Development Kit (ADK): ReAct-style single agents, multi-agent orchestration (Sequential/Parallel/Loop), tool wiring, evaluation, and optional Vertex AI Agent Engine deployment. Use when building, scaffolding, or deploying ADK agents on Google Cloud, or when wiring ADK tools and orchestration patterns. Trigger with "build an ADK agent", "scaffold an agent on ADK", or "deploy to Agent Engine".
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。
Execute use when provisioning Vertex AI ADK infrastructure with Terraform. Trigger with phrases like "deploy ADK terraform", "agent engine infrastructure", "provision ADK agent", "vertex AI agent terraform", or "code execution sandbox terraform". Provisions Agent Engine runtime, 14-day code execution sandbox, Memory Bank, VPC Service Controls, IAM roles, and secure multi-agent infrastructure.
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 whenever datasets, cloud storage buckets, or data pipelines are mentioned — creating, saving, querying, listing, exploring, deleting, or processing data in S3, GCS, Azure Blob, or local storage. Also use when running any script that may create datasets as a side effect. Maintains a knowledge base at dc-knowledge/ (JSON + markdown). ALWAYS use this skill when the user creates a dataset, saves pipeline output, runs a data script, or references any storage bucket.
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。