Results for “service-mesh”

Expert backend architect specializing in scalable API design, microservices architecture, and distributed systems. Masters REST/GraphQL/gRPC APIs, event-driven architectures, service mesh patterns, and modern backend frameworks. Handles service boundary definition, inter-service communication, resilience patterns, and observability. Use PROACTIVELY when creating new backend services or APIs.

Create and manage Kubernetes workloads with declarative YAML manifests, covering deployments, networking, security, storage, Helm charts, and troubleshooting.

Expert en data mesh (domain ownership, data products, self-serve, gouvernance fédérée)

Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.

Provides persistent, self-hosted semantic memory for AI agents via MCP, storing worklogs, decisions, and notes in PostgreSQL with pgvector for meaning-based retrieval across sessions.

service-development

Inter-agent message bus with channels, queues, routing, reliability, and multiple communication patterns

Provides cross-harness memory for agents by maintaining a local memex and offering commands to query, record, and check status across sessions.

Inspect, generate, transform, and visualize UV channels on StaticMesh assets (UVMappingService). Use when the user asks to check/add/remove UV channels, auto-unwrap UVs, transform (tile/offset/rotate) UVs, check UV health/islands, or export a UV layout image.

Query resource usage metrics for Railway services. Use when user asks about resource usage, CPU, memory, network, disk, or service performance like "how much memory is my service using" or "is my service slow".

Expert en serverless (AWS Lambda, Cloudflare Workers, Vercel Edge, cold starts, contexte DZ)

Assists with intercepting network requests for API mocking using Mock Service Worker (MSW). Use when mocking REST or GraphQL APIs for unit tests, integration tests, or local development without modifying application code or running mock servers. Trigger words: msw, mock service worker, api mocking, test mocking, request handlers, setupServer.

Query resource usage metrics for Railway services. Use when user asks about resource usage, CPU, memory, network, disk, or service performance like "how much memory is my service using" or "is my service slow".

Enumerate SMB, WinRM, LDAP, and MSSQL services, validate credentials, spray passwords, and execute commands on remote hosts using NetExec during authorized penetration tests.

Create foliage types and place/scatter foliage instances on landscapes and meshes (FoliageService). Use when the user asks to add trees/grass/bushes/rocks as foliage, create a foliage type from a mesh, scatter or paint foliage instances, or query/remove foliage on a surface.

App Shell architecture — the cached HTML/CSS/JS skeleton (header, nav, footer) served instantly via Service Worker while dynamic content streams in. Use when building PWAs, wiring service-worker caches, inlining critical CSS, or adding offline fallbacks and skeleton loading states.

Mock Service Worker API mocking, request handlers, and integration testing.

Use to design VIP or tiered support programmes and to test whether higher tiers actually deliver better outcomes. Trigger for "VIP support programme", "service tiering", queue priority for premium customers, entitlement vs priority, tier inflation, or "does our enterprise tier get faster support".

Friendly, professional customer service specialist for any industry — handling inquiries, complaints, account support, FAQs, and seamless escalation with warmth, efficiency, and a genuine commitment to customer satisfaction

Map the end-to-end service delivery system including frontstage actions, backstage processes, and supporting infrastructure.

sse-streaming

Create and manipulate Animation Montages — sections, slots, segments, branching points, notifies, and blend settings (AnimMontageService). Use when the user asks to create a montage (from an animation or empty), add or link montage sections, set up slots/segments, add branching points, or adjust montage blend timing.

Consulte métricas de uso de recursos para serviços Railway. Use quando o usuário perguntar sobre uso de recursos, CPU, memória, rede, disco ou desempenho do serviço, como "quanto de memória meu serviço está usando" ou "meu serviço está lento".

Drive mex (`mex-agent`), persistent project memory and code graphs for AI coding agents. One command scaffolds a living wiki, builds a deterministic code graph, and installs a project anchor file (CLAUDE.md, root AGENTS.md, .cursorrules, .windsurfrules, copilot-instructions.md, or .opencode/opencode.json) that your agent auto-loads as a standing rule document. Use when the user wants to `mex setup` a new project, build a symbol-grounded wiki, keep knowledge connected to implementation, route relevant context to agents, or run drift detection (`mex check`, `mex sync`). Triggers on: "mex setup", "project memory", "code graphs", "codebase documentation", "drift detection", "agent memory", "structured scaffolds", "architectural context", "living wiki", "project anchor file".

Provides a pre-built Salesforce Service Cloud data model template with Mermaid diagrams, ASCII fallback, and relationship summaries for documentation and analysis.

Advanced Zephyr RTOS kernel services. Covers inter-thread communication using Zbus (pub/sub), behavioral management with the State Machine Framework (SMF), background processing via work queues, and persistent configuration with the Settings subsystem. Trigger when building modular application architectures, complex state-driven logic, or requiring persistent data storage.

Jest configuration, mocking strategies, snapshot testing, and coverage.

Provides a pre-built Salesforce Party Model data model template with Mermaid diagrams, object tables, and relationship summaries for Industry Clouds.

Install and route through OpenSpace, the skill management layer for AI agents, so a host agent can retrieve/rank/load the right SKILL.md out of this jeo-skills catalog (~150 installed skills), then evaluate skill quality from real execution evidence and evolve skills via FIX/DERIVED/CAPTURED updates. Covers install-as-skill-finder, retrieve-a-skill, evaluate-quality, evolve-skills, and local-first hub share/import. Triggers on: openspace, skill finder, skill retrieval, find the right skill, rank skills, skill discovery, skill quality, evolve skill, FIX DERIVED CAPTURED, skill hub, openspace-mcp, DiscoverSkills, skill-discovery, delegate-task.

Generate production-grade Kubernetes manifests — Deployments with probes and security contexts, Services, Ingress with TLS, HPA, PDB, NetworkPolicy, ConfigMaps, Secrets — with optional Helm charts, Kustomize overlays, Istio mesh, and ArgoCD GitOps