「distribute」の検索結果

Spring Boot 4 observability with Actuator, Micrometer, and OpenTelemetry. Use when configuring health indicators, health checks, custom metrics, distributed tracing, production endpoint exposure, Kubernetes probes, Cloud Run probes, logging, or monitoring. Covers Actuator endpoint security, Micrometer Timer/Counter/Gauge patterns, OpenTelemetry span customization, liveness/readiness probe setup, and metric tag best practices.

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Analyze smart grid and power distribution optimization code for power flow solver correctness, fault detection and restoration automation, distributed energy resource management, voltage regulation, SCADA integration, and cybersecurity posture..

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Allocate testing effort based on risk and failure likelihood using Google's SET/SWE/TE model. Use when user says "risk-based testing", "where should I focus testing", "test coverage strategy", "prioritize what to test", "high risk areas", or needs to decide how to distribute QA effort across a codebase - even if they don't explicitly say "risk-based".

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Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).

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Use when planning, configuring, or maintaining a Salesforce Mobile Publisher branded app — a customer-facing or partner-facing mobile app distributed through Apple App Store or Google Play, built on either the Experience Cloud (LWR/Aura) Mobile Publisher template or the Field Service Mobile Publisher template. Triggers: 'salesforce mobile publisher branded app', 'experience cloud mobile app store distribution', 'mobile publisher push notifications certificate', 'app store review rejection salesforce', 'mobile publisher version policy update'. NOT for the standard mobile app — use admin/lightning-app-builder-advanced. NOT for Field Service mobile — use admin/fsl-mobile-app-setup.

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Use when an admin or partner needs to package an Experience Cloud (Community) site as a reusable Lightning Bolt Solution for distribution — covers the export workflow from Experience Builder, what gets bundled (ExperienceBundle, custom apps, flow categories, theme, layouts, navigation menus) versus what does NOT (data, CMS content, files), choosing Bolt vs managed package vs unlocked package vs cloning a site, sandbox-to-production promotion, multi-org distribution, AppExchange listing as a Bolt, and template versioning via the LightningBolt metadata `versionNumber`. Triggers: 'turn this community into a reusable template', 'package an Experience Cloud site to ship to multiple orgs', 'export Experience Builder template for AppExchange', 'should we use a Bolt or a managed package for this community', 'create an industry-specific community starter', 'how do we version our partner portal template', 'distribute branded Experience site across business units'. NOT for general Experience Cloud site build, content, or member setup (use admin/experience-cloud-site-setup, admin/experience-cloud-cms-content, admin/experience-cloud-member-management). NOT for shipping Apex / LWC / data-model functionality as a product (use devops/managed-package-development, devops/second-generation-managed-packages, devops/unlocked-package-development). NOT for moving a single Experience site between sandbox and prod as a one-off (use devops/experience-cloud-deployment-admin, devops/cicd-for-experience-cloud).

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Microservices design expert covering service decomposition, communication patterns, and distributed systems

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Handle MSAL distributed token cache collisions and stale entries in ASP.NET Core applications

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How to coordinate with squads on different machines using git as transport

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Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

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Apache Spark 4.0.2 best practices for PySpark and Scala distributed data processing

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Comprehensive guide to designing reliable, scalable data systems covering databases, streaming, and consistency

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Implementing the `Idempotency-Key` HTTP header pattern (Stripe-pioneered, IETF-standardizing) so retries don't double-charge or duplicate side effects — full Postgres schema with recovery-point state machine, fingerprint check, in-progress lock with 409 response, and 24h retention. Grounded in Stripe blog/docs, the IETF httpapi WG draft, and Brandur Leach's canonical implementation.

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Use when CPU usage is high, memory grows unboundedly, goroutines leak, mutex contention shows in traces, or escape analysis suggests excess heap allocation. Triggers: net/http/pprof endpoint exposure, go tool pprof analysis, flamegraph generation, allocs vs inuse_space heap profiles, runtime/trace event timeline, mutex profiling, block profiling, goroutine dumps, GC pressure measurement. NOT for non-Go languages, distributed tracing (use OpenTelemetry skill), or production telemetry pipelines.

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Foundational impossibility result proving consensus cannot be guaranteed in asynchronous systems with even one faulty process

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Use when running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).

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Building resilient distributed systems with circuit breakers, retries with full-jitter exponential backoff, retry budgets (per-request 3-attempt + per-client 10% ratio per Google SRE), deadline propagation, and the cascading-failure math (4 layers × 3 retries = 64x amplification). Grounded in Resilience4j, Microsoft Cloud Patterns, AWS Architecture Blog (Marc Brooker), and Google SRE Book.

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Foundational concurrent computation model where actors communicate exclusively through asynchronous message passing

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Choose multi-agent architectures using environment-first analysis, coordination pressure, commitment tuning, and knowledge levels. Use for autonomy design, protocol choice, and coordination failures. NOT for single-agent planning, centralized schedulers, or prompt-only swarms.

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Model gene-family birth-death dynamics across a species tree using CAFE5 (Mendes et al 2020 Bioinformatics 36:5516 gamma-distributed rate categories), CAFE5-error (annotation-error-aware), Count (Csurös 2010 ancestral state reconstruction), BadiRate (Librado 2012 likelihood + parsimony), DupliPHY-Family, and ALE/AleRax (for per-family DTL; see [[gene-tree-species-tree-reconciliation]]). Test lineage-specific gene-family expansions and contractions, distinguish biological dynamics from annotation artifacts, account for assembly fragmentation, identify functional enrichment in expanded / contracted families. Use when correlating gene-family changes with phenotype evolution, ranking lineages by adaptive gene-family-rate shifts, post-WGD dosage-balance analysis, or building Birth-death models from OrthoFinder presence/absence matrices.

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Expert guide for Backend.AI distributed computing platform. Automatically activates when users ask about: - Backend.AI architecture, components (Manager, Agent, Storage Proxy, Webserver, App Proxy) - Features (session scheduling, Sokovan orchestrator, multi-tenancy, resource allocation) - APIs (REST, GraphQL), authentication, RBAC authorization - Container runtime (kernels, jail sandbox, hook library, virtual folders) - Accelerator support (CUDA, ROCm, TPU, NPU, Graphcore IPU) - Client SDKs (Python, Java, JavaScript, PHP) - Setup, requirements (Python 3.13+, Docker, PostgreSQL, Redis, etcd) - How WebUI connects to/interacts with Backend.AI backend - Plugin interfaces, development setup, infrastructure Use when user mentions "Backend.AI", "backend.ai", "Sokovan", component names, or asks about the backend platform this WebUI connects to. allowed-tools: WebFetch, Read

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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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Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.

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Azure Cosmos DB SDK for Rust (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.

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