「serverless」の検索結果

Run SQL against Amazon Redshift — submit statements, poll status, page through results, and browse databases/schemas/tables. Use this whenever the user wants to query Redshift (provisioned cluster or Serverless), ask "what tables are in this schema", check a query's status, or mentions `redshift-data`, a Redshift cluster identifier / workgroup name, or a `redshift-data.{region}.amazonaws.com` endpoint. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.

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Cloud control-plane exploitation for AWS, Azure/Entra, GCP, and Alibaba Cloud: IAM/RAM privilege escalation, impersonation, cross-account trust, serverless/compute control, and cloud-native persistence. Host OS persistence/C2 after root/SYSTEM belongs to /post. K8s RBAC belongs to /k8s. Operator chooses next modules; new identities default to /cloud-recon first.

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Applies general rules for Convex development, emphasizing schema design, validator usage, index-first query patterns, function registration, and correct handling of system fields.

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。

Google Cloud Run deployment, service management, traffic splitting, and log inspection. Use when deploying containerized apps to Cloud Run, managing services, or inspecting Cloud Run logs.

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Use when the user is deciding, reviewing, or second-guessing a software architecture or tech-stack choice — monolith vs microservices vs serverless vs event-driven, backend language, database type, caching, CQRS/event sourcing, polyglot, or a migration like Strangler Fig. Triggers on "should I use microservices", "which database", "tech stack for", "system design", or "architecture review". For how to deploy, operate, and scale that design (CI/CD, cloud, Kubernetes, IaC), use devops.

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Create multi-stage Dockerfiles that separate build and runtime environments for minimal production images. Covers builder/runtime stage separation, artifact copying, scratch/distroless/alpine targets, and size comparison. Use when production images are too large, when build tools are included in the final image, when you need separate dev and prod images from one Dockerfile, or when deploying to constrained environments like edge or serverless.

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Build and deploy full-stack web and mobile apps with AWS Amplify Gen2 (TypeScript code-first). Covers auth (Cognito), data (AppSync/DynamoDB including schema modeling, enum types, relationships, authorization rules), storage (S3), functions, APIs, and AI (Amplify AI Kit with Bedrock). Supports React, Next.js, Vue, Angular, React Native, Flutter, Swift, and Android. Always use this skill for Amplify Gen2 topics — even for questions you think you know — it contains validated, version-specific patterns that prevent common mistakes. TRIGGER when: user mentions Amplify Gen2; project has amplify/ directory or amplify_outputs; code imports @aws-amplify packages; user asks about defineBackend, defineAuth, defineData, defineStorage, or npx ampx. SKIP: Amplify Gen1 (amplify CLI v6), standalone SAM/CDK without Amplify (use aws-serverless), direct Bedrock without Amplify AI Kit (use bedrock).

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Work with the @upstash/search TypeScript/JavaScript SDK, a serverless full-text and semantic search database with built-in reranking. Use when adding search to an app or site, creating a search index, upserting documents with searchable content and filterable metadata, running keyword, semantic, or hybrid search queries, reranking results, filtering with SQL-like or structured filter syntax, paginating with range, fetching or deleting documents, resetting an index, or checking index info. Also use when the user asks for site search, product, document, or knowledge-base search, or a managed search service that needs no cluster to run.

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Work with the @upstash/vector TypeScript/JavaScript SDK, a serverless vector database for embeddings, similarity search, semantic search, and RAG (retrieval-augmented generation). Use when upserting, querying, fetching, ranging, or deleting vectors, upserting raw text against an index with a built-in embedding model, choosing dense, sparse, or hybrid indexes, filtering by metadata, organizing data with namespaces, running resumable queries, or connecting Upstash Vector to an AI or LLM application. Also use when the user asks for a vector store, vector search, nearest-neighbor or kNN search, embeddings storage, semantic cache, recommendations or similarity features, or a hosted vector index that needs no infrastructure.

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Rate limiting for serverless and edge apps with the @upstash/ratelimit TypeScript/JavaScript SDK backed by Upstash Redis. Use when adding a rate limiter or throttling to an API route, Next.js middleware, Vercel Edge, Cloudflare Workers, or any HTTP endpoint; returning 429 Too Many Requests; choosing between fixed window, sliding window, and token bucket algorithms; limiting per user, IP, API key, or tenant with prefixes and custom keys; protecting login, signup, form, or AI endpoints from abuse, bots, and brute force; using deny lists, ephemeral caching, analytics, timeouts, and multi-region rate limits; or estimating the Redis command cost of rate limiting. Also use when the user says rate limit, rate-limiting, throttle, quota, request limits, or traffic protection.

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Use when upgrading an existing TypeScript codebase from Inngest SDK v3 to v4, or when fixing mixed v3/v4 API usage. Covers detecting current SDK usage, moving triggers into createFunction options, replacing EventSchemas with eventType/staticSchema, moving serve options to the client, updating realtime imports, rewriting step.invoke string IDs, checkpointing/serverless runtime settings, Connect option changes, and verification.

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Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native applications.

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Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.

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系统架构图绘制。当需要绘制任何系统架构图、云架构设计图、微服务架构图、Serverless架构图、混合云架构图时使用此技能，支持腾讯云及通用架构场景。基于 Draw.io XML 生成 .drawio 文件，支持二次可视化编辑。

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Optimize cloud and AI costs for modern SaaS stacks (Vercel, Supabase, Neon, Stripe, and AI APIs). Covers token efficiency, serverless database scaling, edge function optimization, and burn rate monitoring. Use when planning infrastructure, investigating high bills, or auditing API usage.

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Exploit misconfigurations in AWS Cognito, specifically focusing on unauthorized identity pool access, user pool self-registration issues, and privilege escalation via custom attributes to access broader AWS infrastructure.

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Cloud security posture assessment for AWS, Azure, and GCP. Tests IAM privilege escalation paths, public storage exposure, serverless attack surface, database exposure, logging gaps, container registry security, and cloud-specific attacks. Both authenticated (with cloud credentials) and unauthenticated (external) modes. Uses nuclei cloud templates, Prowler, ScoutSuite, manual IMDS/metadata probing, and deep AWS/Azure/GCP CLI enumeration. Produces: cloud architecture diagram, attack path map, findings per category, compliance mapping (SOC 2, PCI DSS 4.0, HIPAA, CIS), PoCs for confirmed exploits. Chains into /gh-export for issue filing.

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Vercel deployment platform — project configuration, serverless/edge functions, Routing Middleware, cron jobs, environment variables, monorepo setup

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SST (Ion) infrastructure-as-code — TypeScript-first serverless on AWS with Pulumi, resource linking, and live Lambda dev

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Netlify deployment platform — serverless functions, edge functions, redirects, forms, Blobs, build plugins

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。

Pinecone serverless vector database -- index management, vector operations, metadata filtering, namespaces, hybrid search, inference API

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。

Serverless Redis-compatible key-value store via Upstash REST API -- edge-compatible, automatic JSON serialization, TTL-based caching

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。

Serverless PostgreSQL on Vercel with edge-compatible SDK

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Serverless PostgreSQL with branching, autoscaling, and edge-compatible driver

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。