'scalable' 검색 결과

Build data processing pipelines for machine learning, from preprocessing to batch predictions. Uses Ray Data to handle datasets larger than memory, distribute work across CPUs and GPUs, and feed data into training frameworks.

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• Preprocessing datasets larger than memory
• Running batch predictions across multiple GPUs
• Preparing image and tabular data for training

Build data processing pipelines for machine learning, from preprocessing to batch predictions. Uses Ray Data to handle datasets larger than memory, distribute work across CPUs and GPUs, and feed data into training frameworks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preprocessing datasets larger than memory
• Running batch predictions across multiple GPUs
• Preparing image and tabular data for training

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Authentication & Authorization Implementation Patterns workflow skill. Use this skill when the user needs Build secure, scalable authentication and authorization systems using industry-standard patterns and modern best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Authentication & Authorization Implementation Patterns workflow skill. Use this skill when the user needs Build secure, scalable authentication and authorization systems using industry-standard patterns and modern best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Authentication & Authorization Implementation Patterns workflow skill. Use this skill when the user needs Build secure, scalable authentication and authorization systems using industry-standard patterns and modern best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create clear educational diagrams for scientific concepts, physical structures, workflows, and data. Output SVG, a scalable vector image format, inside one standalone HTML file with consistent styling and automatic light and dark modes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Illustrating scientific concepts for teaching materials
• Explaining object structures with cross-sections and layers
• Visualizing workflows and data movement

Turn a system description into a dark-themed architecture diagram in a single HTML file. It uses SVG, a scalable graphics format, to show components, connections, cloud boundaries, and security flows in a browser.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Explaining frontend, backend, and database connections
• Mapping cloud regions and subnets
• Visualizing microservice connections

Create static SVG diagrams, scalable images for lessons, READMEs, and manuals. It uses real system names, nine diagram types, and consistent colors and arrows, with checks for readable labels, accessible descriptions, and valid markup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add a diagram of system interactions to a README
• Explain state transitions in a manual
• Illustrate data flow from logs or specifications

Build reusable interface components with Tailwind CSS v4, using shared design values for colors, corners, and themes. Covers buttons, forms, responsive layouts, accessibility, and dark mode to help standardize interfaces across a project.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a reusable UI component library
• Standardize colors and component styles
• Add responsive layouts and dark mode

Create a Dubai weather card from a supplied temperature and unit. The skill writes an SVG, a scalable image format, and a Markdown summary to designated files, preserving the provided temperature exactly.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning a Dubai temperature reading into a weather card
• Saving a temperature summary in Markdown
• Updating weather image and summary files in a workflow

Organize PyTorch models and data pipelines with PyTorch Lightning, automate training, save checkpoints, and track experiments. Includes templates and guidance for configuring training across multiple GPUs or TPUs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Restructure PyTorch training code into LightningModules
• Build reusable data preparation and loading pipelines
• Configure checkpoints, early stopping, and experiment logs

Plan backend architecture using Clean Architecture, Hexagonal Architecture, or Domain-Driven Design. Clarify business boundaries, choose a suitable structure, define how modules depend on each other, and outline migration steps and validation checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Design the structure of a new backend
• Reduce tight coupling in a monolithic application
• Define shared architecture standards for a team

Design REST or GraphQL APIs by defining who will use them, what data they expose, and how requests behave. Establish error formats, versioning, pagination, and authentication, then review examples for consistency before implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing a new REST or GraphQL API
• Reviewing API specifications before implementation
• Establishing shared API design standards

Build consistent interface foundations with design tokens, named values for colors, spacing, and typography. Covers light and dark themes, multiple brands, reusable components, and workflows that keep design definitions aligned with application code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Organizing shared colors, typography, and spacing
• Implementing light and dark theme switching
• Sharing interface components across multiple brands

Set up and maintain a monorepo, a single repository containing multiple apps and packages. Use Turborepo, Nx, and pnpm workspaces to organize shared code, manage dependencies, improve builds, and plan package releases.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting up a repository for multiple apps and packages
• Moving separate repositories into a monorepo
• Reviewing build caches and test performance

Build a consistent interface foundation with Tailwind CSS v4 using shared design values and reusable components. Covers responsive layouts, dark mode, accessibility, and component variations to help standardize UI patterns across a codebase.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building a reusable UI component library
• Standardizing colors, corner radii, and themes
• Creating responsive and accessible components

Build GitLab workflows that automate building, testing, and deployment. The skill covers pipeline stages, dependency caching, runners that execute jobs, and manual approval before production deployment, with examples for Docker, Kubernetes, and Terraform.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Automating builds and tests in GitLab
• Reviewing caches to improve pipeline performance
• Separating staging and production deployments

Design and review REST and GraphQL APIs with consistent naming, data structures, error responses, pagination for large result sets, and versioning strategies. Helps teams define shared standards and plan changes that existing clients can adopt gradually.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing a new REST or GraphQL API
• Reviewing API specifications before implementation
• Establishing shared API design standards

Design separate paths for updating and reading data using CQRS, an approach that splits these responsibilities. Organize read models, event handling, and validation to support complex queries and scale reads independently from writes.

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• Separating data updates from queries
• Scaling reads independently from writes
• Optimizing complex reporting queries

Plan and implement user login and access permissions using sessions, JWT tokens, or OAuth2. Apply role-based permissions, protect APIs, and review common weaknesses in password handling, cookies, token expiration, and server-side checks.

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• Implementing user login and logout
• Adding social login or enterprise SSO
• Controlling access by user role

Design a database layer from business requirements, access patterns, and expected growth. Compare database technologies, define tables and relationships, and plan indexes, caching, scaling, migrations, backups, and recovery with clear reasons and trade-offs.

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• Choosing a database for a new service
• Designing tables, relationships, and indexes
• Planning database migrations and rollback procedures

Plan backend systems with clear module boundaries and dependency rules. This skill helps select architecture patterns, organize business logic, and outline migration steps for systems that are easier to maintain and test.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing a new backend system
• Restructuring a monolithic application
• Defining shared architecture standards