「distributed」の検索結果

Unified expert guide for async job queues & durable workflows: BullMQ v5 (Redis queues), Trigger.dev v3 (serverless tasks), Inngest, and Temporal.io (distributed sagas) / Panduan ahli terpadu untuk antrean job asinkron & workflow tahan-gagal: BullMQ v5, Trigger.dev v3, Inngest, dan Temporal.io.

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Expert guide for scheduled tasks, cron jobs, recurring background work (Vercel Cron, Cloudflare Workers Cron, Inngest, node-cron), and distributed scheduling / Panduan ahli untuk tugas terjadwal, cron job, pekerjaan latar belakang berulang, dan penjadwalan terdistribusi.

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Software design principles, patterns, and architecture from SOLID through distributed systems. Covers the five SOLID principles with violations and fixes, DRY/KISS/YAGNI heuristics, separation of concerns, 12 GoF design patterns organized by intent (creational, structural, behavioral), architectural patterns (MVC, MVP, MVVM, layered, hexagonal, microservices, event-driven), coupling and cohesion metrics, dependency injection, and the design decision framework for choosing between competing approaches. Use when making design decisions, reviewing architecture, refactoring code, or teaching software engineering principles.

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OpenStack Swift object storage service. Provides S3-compatible distributed object storage with containers, ACLs, ring architecture, eventual consistency, large object support (SLO/DLO), tempURL for unauthenticated access, object versioning, and object expiry. Use for deploying, configuring, operating, and troubleshooting OpenStack object storage.

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Botnet architecture taxonomy, detection techniques, and defensive analysis. Covers C2 topologies, DGA analysis, fast-flux detection, P2P overlay mapping, blockchain C2, and ML-based traffic fingerprinting. Defensive research for understanding and countering distributed malicious infrastructure.

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Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.

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Attiya-Bar-Noy-Dolev atomic register emulation over message-passing. Load when designing quorum-based distributed storage, proving linearizability, or reasoning about fault-tolerant shared memory.

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ABD quorum-based linearizable registers for distributed storage — the canonical crash-tolerant read/write protocol with precise RTT and message complexity.

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Design stable, compatible public APIs using extend-only design principles. Manage API compatibility, wire compatibility, and versioning for NuGet packages and distributed systems.

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Write integration tests using .NET Aspire's testing facilities with xUnit. Covers test fixtures, distributed application setup, endpoint discovery, and patterns for testing ASP.NET Core apps with real dependencies.

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Critical Akka.NET best practices including EventStream vs DistributedPubSub, supervision strategies, error handling, Props vs DependencyResolver, work distribution patterns, and cluster/local mode abstractions for testability.

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Expert error coordinator specializing in distributed error handling, failure recovery, and system resilience. Masters error correlation, cascade prevention, and automated recovery strategies across multi-agent systems with focus on minimizing impact and learning from failures.

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Deploys custom Apify Actors via the Apify API v2 for large-scale web crawling using CrawleeJS. Leverages Apify dataset storage, RequestQueue, and proxy configuration for distributed scraping at scale.

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CTO-level architectural advisor for AI-native development. Use this skill whenever you encounter code design decisions, architecture discussions, system resilience questions, or any work touching: "architecture", "design", "scale", "dependencies", "state", "failure", "blast radius", "refactor", "migrate", "optimize", "resilience", "consistency", "observability", "bottleneck", "coupling", "monolith", "microservices", "distributed", "concurrency", "data flow", "system design", or any prompt suggesting code-first thinking when design-first thinking is needed. This skill integrates with Claude Code to review generated code for architectural soundness, define design systems via design.md, and guide teams toward CTO-level thinking. Trigger aggressively on architectural questions—this is where AI adds the most leverage.

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Applies general coding standards and best practices for Kafka development with Scala.

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Orchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.

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Apply ant colony optimization and foraging theory to resource search, exploration-exploitation tradeoffs, and distributed discovery. Covers scout deployment, trail reinforcement, diminishing returns detection, and adaptive foraging strategy selection. Use when searching a large solution space where brute-force enumeration is impractical, balancing investment between exploring new approaches and deepening known good ones, optimizing resource allocation across uncertain opportunities, or diagnosing premature convergence on local optima.

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Implement layered collective defense using alarm signaling, role mobilization, and proportional response. Covers threat detection, alert propagation, immune response patterns, escalation tiers, and post-incident recovery for distributed systems and organizations. Use when designing defense-in-depth where no single guardian covers all threats, building incident response that scales with severity, or when current defense is over-reactive to every alert or under-reactive to genuine threats.

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Unify metrics, logs, and traces for cohesive debugging. Implement exemplars for log-to-trace linking, build unified dashboards using RED/USE methods, and enable rapid root cause analysis across observability signals. Use when investigating complex incidents spanning multiple systems, reducing mean time to resolution, implementing distributed tracing, or moving from siloed tools to a unified observability platform.

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Use when the user asks about NixOS, Nix language, flakes, nixpkgs, configuration.nix, nixos-rebuild, modules, options, overlays, derivations, mkDerivation, callPackage, home-manager, nix-darwin, devenv, packaging, cross-compilation, binary caches, garbage collection, NixOS containers, networking, firewall, systemd services, filesystems, LUKS, Wayland, X11, kernel, profiles, NixOS testing or VM tests, ISO images, Docker images, Raspberry Pi, Terraform, distributed builds, remote machines, pinning nixpkgs, rollback, generations, Nix Pills, or any topic related to configuring, packaging, deploying, or troubleshooting NixOS and the Nix ecosystem.

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Use ManagedCode.Orleans.SignalR when a distributed .NET application needs Orleans-based coordination of SignalR real-time messaging, hub delivery, and grain-driven push flows.

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Integrate ManagedCode.Orleans.Graph into an Orleans-based .NET application for graph-oriented relationships, edge management, and traversal logic on top of Orleans grains. Use when the application models graph structures in a distributed Orleans system.

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Build or review distributed .NET applications with Orleans grains, silos, persistence, streaming, reminders, placement, transactions, serialization, event sourcing, testing, and cloud-native hosting.

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VictoriaTraces provider for obz. Covers trace search, trace retrieval by ID, and extension commands for service and operation discovery via the Jaeger-compatible HTTP API. This skill should be used when the user mentions "VictoriaTraces", "obz trace -p vt", or needs to search distributed traces from a VT backend.

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。