「scaling」の検索結果

Reference guide for the Twelve-Factor App methodology — 15 principles (12 original + 3 modern extensions) for building portable, resilient, cloud-native applications. Use when evaluating application architecture, designing cloud-native services, reviewing codebases for methodology compliance, advising on configuration, scaling, observability, security, and deployment patterns. Incorporates the 2025 open-source community evolution and cloud-native reinterpretations of each factor.

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Manage Alibaba Cloud Redis (Tair / R-KVStore) using the @alicloud/r-kvstore20150101 TypeScript SDK. Use when working with Redis or Tair instances, accounts, backups, security (whitelist/SSL/TDE/audit), parameters, monitoring, cluster scaling, direct connection, Tair Custom instances, and resource tagging. Covers all 157 APIs of the R-KVStore 20150101 version.

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Manage Alibaba Cloud Function Compute (FC) 3.0 using the @alicloud/fc20230330 TypeScript SDK. Use when working with serverless functions on Alibaba Cloud, including function CRUD, invocation, versions, aliases, triggers (HTTP/Timer/OSS/CDN/MNS), async invocation, concurrency and scaling configs, provisioned instances, custom domains, layers, VPC bindings, sessions, and resource tagging. Covers all 67 APIs of the FC 20230330 version.

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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

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Use when operating ProjectClownfish cluster workflows in this repo: reviewing GitHub Actions run artifacts, tuning worker/applicator guardrails, importing ghcrawl clusters, dispatching canaries, scaling batches, or deciding whether autonomous write-mode cluster cleanup is safe to ramp.

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Set up or troubleshoot MotherDuck connections, authentication, client runtimes, and read scaling.

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Expert partnership marketing guidance for building and scaling partner programs, co-marketing campaigns, and channel ecosystems. Use when developing partner strategy, creating co-marketing content, designing partner tiers, building affiliate programs, positioning in integration marketplaces, enabling channel partners, planning joint webinars, or structuring revenue sharing. Use for technology partnerships, reseller programs, strategic alliances, and partner relationship management.

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Strategic sales leadership guidance for B2B SaaS and enterprise software companies. Covers sales strategy, team building, pipeline management, enterprise selling, discovery calls, demos, proposals, negotiations, and sales operations. Use when building sales teams, designing sales processes, improving win rates, or scaling revenue operations. Use for "sales strategy", "sales process", "pipeline review", "deal strategy", "sales hiring", "quota planning".

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Strategic marketing leadership guidance for B2B SaaS and technology companies. Covers go-to-market strategy, product marketing, content marketing, demand generation, SEO, community building, event marketing, PR, partnerships, and pricing strategy. Use when planning marketing strategy, launching products, building brand awareness, driving demand, or scaling marketing operations. Use for "marketing plan", "GTM strategy", "content strategy", "demand gen", "product launch marketing".

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Deploys intelligent web scraping actors on the Apify platform using the Apify SDK with RequestQueue and Dataset APIs. Handles dynamic content via Apify CheerioCrawler and PlaywrightCrawler with automatic scaling.

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Use when working on imp's quantization formats, loaders, or dequant paths - GGUF Q4_0...Q8_0/Q*_K/IQ4/MXFP4, NVFP4 two-level scaling (Modelopt vs compressed-tensors layouts), FP8 E4M3, StorageTier, decode cache, KV-cache dtypes (auto/fp16/fp8/int8/int4/nvfp4/mxfp4), "which quant should I use", "which KV dtype", scale-factor layout, dequant kernel wiring, imp-quantize / AWQ, judging quant quality (PPL). Do NOT use for writing/optimizing GEMM/GEMV kernels (sm120-cuda-expert) or measuring quant perf (benchmark-cuda).

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Kubernetes cluster management and troubleshooting. Query pods, deployments, services, logs, and events. Supports context switching, scaling, and rollout management. Use for Kubernetes debugging, monitoring, and operations.

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Google Imagen image generation via Vertex AI — text-to-image, image editing, inpainting, and upscaling using ImageGenerationModel

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Use when the user needs to deploy, operate, secure, or scale running infrastructure — cloud architecture (multi-region, VPC, FinOps), CI/CD and deployment strategies, secrets/IAM/supply-chain security, observability and SLO alerting, SRE and incident response, Kubernetes vs ECS and autoscaling, Terraform/Pulumi/CDK, or platform engineering and DORA metrics. Also for generating runbooks, pipeline configs, Terraform modules, or Kubernetes manifests. For choosing the system's architecture or stack before it runs (monolith vs microservices, which database), use software-architect.

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Perform capacity planning using historical metrics and growth models. Use predict_linear for forecasting, identify resource constraints, calculate headroom, and recommend scaling actions before saturation. Use before seasonal traffic spikes or product launches, during quarterly capacity reviews, when resource utilization trends upward, or before budget planning cycles.

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Implement a generative diffusion model (DDPM or score-based) with noise scheduling, U-Net architecture, training loop, and sampling procedures including DDIM acceleration. Use when building a generative model for image, audio, or molecular synthesis; implementing DDPM from a research paper; adding a custom noise schedule or conditioning mechanism; replacing a GAN-based generator with a diffusion alternative; or prototyping before scaling with production frameworks like diffusers.

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Conduct a structured cross-project code review between two Claude Code instances via the cross-review-mcp broker. Each agent reads its own codebase, reviews the peer's code, and engages in evidence-backed dialogue — with QSG scaling laws enforcing review quality through minimum bandwidth constraints and phase-gated progression.

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Design sustainable on-call rotations with balanced schedules, clear escalation policies, fatigue management, and handoff procedures. Minimize burnout while maintaining incident response coverage. Use when setting up on-call for the first time, scaling a team from 2-3 to 5+ engineers, addressing on-call burnout or alert fatigue, improving incident response times, or after a post-mortem identifies handoff issues.

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Use when code mixes units, fixed-point precisions, scaling factors, rates, prices, shares, or conversions. Not for type-level unit modeling: use type-driven.

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Plan transition from freelancer to agency with scaling. TRIGGERS - Use when user needs help with agency-builder related tasks.

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Server management principles and decision-making. Process management, monitoring strategy, and scaling decisions. Teaches thinking, not commands.

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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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Creates demand generation campaigns, optimizes paid ad spend across LinkedIn, Google, and Meta, develops SEO strategies, and structures partnership programs for Series A+ startups scaling internationally. Use when planning marketing strategy, growth marketing, advertising campaigns, PPC optimization, lead generation, pipeline generation, or startup marketing budgets. Covers multi-channel acquisition (Google Ads, LinkedIn Ads, Meta Ads), CAC analysis, MQL/SQL workflows, attribution modeling, technical SEO, and co-marketing partnerships for hybrid PLG/Sales-Led motions in EU/US/Canada markets.

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Design, implement, and audit PFC3D 5.0 asphalt wheel-tracking and intersection-rutting simulations using RVE-to-strip-to-full-size scaling, PFC5-compatible vector reaction control, Burger-calibrated contacts, vertical-horizontal coupled loads, rut/shear histories, edition-specific metrics, and explicit surrogate validation.

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。