Design idempotent APIs and operations. Outputs idempotency keys, deduplication strategies, and retry-safe implementations.
원문 언어: 영어
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Design idempotent APIs and operations. Outputs idempotency keys, deduplication strategies, and retry-safe implementations.
원문 언어: 영어
Design alerting rules for production monitoring with Prometheus, Grafana, PagerDuty. Outputs alert definitions, severity levels, escalation policies, and runbooks.
원문 언어: 영어
Optimize ML model hyperparameters with grid search, random search, Bayesian optimization. Outputs tuning strategy, search spaces, and best parameters.
원문 언어: 영어
Design penetration testing plans with scope, methodology, tools, and reporting. Outputs test scenarios, OWASP Top 10 coverage, and remediation priorities.
원문 언어: 영어
Design scalability strategies for horizontal and vertical scaling. Outputs capacity planning, bottleneck analysis, and scaling triggers.
원문 언어: 영어
Setup monitoring with Prometheus, Grafana, alerting. Outputs metrics collection, dashboards, alert rules, and SLO tracking.
원문 언어: 영어
Design secrets management with Vault, AWS Secrets Manager, encrypted storage. Outputs rotation policies, access controls, and audit logging.
원문 언어: 영어
Design analytics dashboards with Tableau, PowerBI, Looker, Metabase. Outputs metric definitions, visualizations, filters, and user flows.
원문 언어: 영어
Design data quality validation with Great Expectations, custom checks, and automated monitoring. Outputs validation rules, anomaly detection, and data lineage.
원문 언어: 영어
Design real-time streaming pipelines with Kafka, Flink, Spark Streaming. Outputs producer/consumer patterns, windowing, state management, and exactly-once semantics.
원문 언어: 영어
Monitor ML models in production for drift, performance degradation, and data quality. Outputs metrics, alerts, and retraining triggers.
원문 언어: 영어
Design Retrieval-Augmented Generation systems with vector databases, chunking strategies, and hybrid search. Outputs architecture, embedding pipelines, and retrieval optimizations.
원문 언어: 영어
Design penetration testing plans with OWASP methodology, attack vectors, and remediation tracking. Outputs test scope, findings, and security improvements.
원문 언어: 영어
Design threat models using STRIDE, attack trees, and data flow diagrams. Outputs threat analysis, risk ratings, and mitigation strategies.
원문 언어: 영어
Document architecture decisions with ADRs (Architecture Decision Records). Outputs decision context, options, trade-offs, and rationale.
원문 언어: 영어
Design contract tests for APIs and microservices with Pact. Outputs consumer-driven contracts, provider verification, and CI integration.
원문 언어: 영어
Design performance and load tests with JMeter, k6, Locust. Outputs test scenarios, metrics, bottleneck analysis, and capacity planning.
원문 언어: 영어
Design a complete REST or GraphQL API from requirements. Outputs endpoints, request/response schemas, error handling, authentication, and versioning strategy.
원문 언어: 영어
Design asynchronous processing patterns for background jobs, event-driven systems, and non-blocking I/O. Outputs queues, workers, retry logic, and monitoring.
원문 언어: 영어
Design a multi-layer caching strategy for performance optimization. Outputs cache types, TTLs, invalidation, and cache-aside patterns.
원문 언어: 영어
Circuit breaker pattern for handling service failures gracefully. Outputs states (closed/open/half-open), thresholds, fallback strategies, and monitoring.
원문 언어: 영어
Generate a focused code review checklist based on language, framework, and change type. Outputs specific items to check, not generic advice.
원문 언어: 영어
Design a normalized database schema with tables, relationships, indexes, and constraints. Outputs SQL DDL and ER diagram description.
원문 언어: 영어
Design a comprehensive error handling strategy for an application. Outputs error types, response formats, logging patterns, and user-facing messages.
원문 언어: 영어
Feature flag system for gradual rollouts, A/B testing, and kill switches. Outputs flag types, targeting, evaluation, and lifecycle management.
원문 언어: 영어
Design a Git branching strategy and workflow for a team. Outputs branch naming, merge strategy, CI/CD integration, and release process.
원문 언어: 영어
Design a comprehensive logging strategy for production systems. Outputs log structure, levels, retention, aggregation, and query patterns.
원문 언어: 영어
Design a microservices architecture from a monolith or new requirements. Outputs service boundaries, communication patterns, data ownership, and deployment strategy.
원문 언어: 영어
Design pagination for large datasets with cursor-based, offset-based, and keyset strategies. Outputs performance trade-offs and implementation patterns.
원문 언어: 영어
Design rate limiting to prevent abuse and ensure fair usage. Outputs algorithms (token bucket, sliding window), storage strategies, and bypass rules.
원문 언어: 영어
Analyze a codebase or component to identify technical debt, assess impact, and prioritize remediation. Outputs categorized debt items with ROI estimates.
원문 언어: 영어
Design continuous integration and deployment pipelines. Outputs stages, testing, artifact management, deployment strategies, and rollback procedures.
원문 언어: 영어
Create production-ready Docker Compose configurations for multi-container applications. Outputs service definitions, networking, volumes, and environment management.
원문 언어: 영어
Create production Kubernetes manifests with deployments, services, ingress, configs, and autoscaling. Outputs complete YAML with best practices.
원문 언어: 영어
Production Terraform modules for infrastructure as code. Outputs reusable modules with variables, state management, and CI/CD integration.
원문 언어: 영어
Design data warehouse schemas with star/snowflake patterns, dimensions, facts, and slowly changing dimensions. Outputs DDL and ETL integration.
원문 언어: 영어
Design extract-transform-load pipelines for data warehousing. Outputs data sources, transformations, quality checks, scheduling, and monitoring.
원문 언어: 영어
Optimize slow SQL queries with indexing, query rewriting, and execution plan analysis. Outputs before/after metrics and index strategies.
원문 언어: 영어
Design ML features with encoding, scaling, selection, and extraction. Outputs feature pipelines, importance analysis, and validation strategies.
원문 언어: 영어
Design an end-to-end machine learning pipeline from data to deployment. Outputs data preparation, training, evaluation, deployment, and monitoring steps.
원문 언어: 영어