510건 · 관련도순
Diagnose software failures using observability data, ranked hypotheses, and targeted instrumentation. Use when the cause is unclear or an issue requires systematic investigation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert SRE incident responder specializing in rapid problem resolution, modern observability, and comprehensive incident management. Masters incident command, blameless post-mortems, error budget management, and system reliability patterns. Handles critical outages, communication strategies, and continuous improvement. Use IMMEDIATELY for production incidents or SRE practices.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Masters log analysis, distributed tracing, Kubernetes debugging, performance optimization, and root cause analysis. Handles production outages, system reliability, and preventive monitoring. Use PROACTIVELY for debugging, incident response, or system troubleshooting.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Diagnose software failures using observability data, ranked hypotheses, and targeted instrumentation. Use when the cause is unclear or an issue requires systematic investigation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Plan, create, and configure production-ready Azure Kubernetes Service (AKS) clusters. Covers Day-0 checklist, SKU selection (Automatic vs Standard), networking options (private API server, Azure CNI Overlay, egress configuration), security, and operations (autoscaling, upgrade strategy, cost analysis). WHEN: create AKS environment, provision AKS, enable AKS observability, design AKS networking, choose AKS SKU, secure AKS, optimize AKS, AKS spot nodes, AKS cluster-autoscaler, rightsize AKS pod, pod rightsizing, over-provisioned AKS pod, pod resource requests and limits, Vertical Pod Autoscaler, VPA recommendations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infrastructure.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Read and write Langfuse: browse traces and observations, list prompts and datasets, score traces, add dataset items. Trigger phrases: langfuse, llm observability.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design or troubleshoot telemetry, SLOs, and incident diagnostics. Route to the relevant signal, system boundary, or vendor guide.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Brings Azure Monitor, Application Insights, and Log Analytics telemetry into Fabric as Eventhouse external delta tables and correlates it with business data. Use to onboard observability data, judge whether latency or availability affected revenue, or build a Real-Time dashboard and Operations Agent over it.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Provides guidance for implementing OpenTelemetry instrumentation in .NET codebases, covering tracing (Activities/Spans), metrics, logs, naming conventions, error handling, performance, SDK setup, resources, context propagation, and API design best practices.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Add OpenTelemetry tracing to MATLAB code. Use when the user asks to "add tracing", "instrument with spans", "add OpenTelemetry", "trace my code", "add observability" (when about tracing), or mentions "spans", "distributed tracing", or "OTel tracing" in the context of MATLAB functions. Covers span creation, parent-child context propagation, error handling, attributes, events, and semantic conventions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Deploys and operates a LiveKit agent in production: shipping a version to LiveKit Cloud and rolling it back, secrets and configuration, the worker process model and prewarming, safe async inside worker processes, provider timeouts and degradation, graceful shutdown, SDK upgrades, and observability. Use when the user says "deploy my agent", "roll back the deployment", "tail the agent logs", "the first call after a restart is slow", "attached to a different loop / event loop is closed", "prewarm the VAD", "shut down without dropping calls", "upgrade livekit-agents safely", "correlate logs by session", or is changing an agent codebase that is already live. Not for designing the agent (building-livekit-agents) or reproducing one bad conversation locally (debugging-livekit-agents).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Configure a Mac mini as a reliable local LLM server with remote access, observability, and power-safe operation. Use when building an always-on private AI inference server on Apple Silicon.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement Istio and Linkerd service meshes. Configure mTLS, traffic management, and observability. Use when managing microservices communication.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement Datadog monitoring and APM for infrastructure and applications. Configure agents, create dashboards, set up alerts, and implement distributed tracing. Use when implementing enterprise monitoring, APM, or unified observability platforms.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and operationalize SRE dashboards that surface reliability, latency, error, saturation, and capacity signals across services. Use when building observability views for SLOs, incident response, and executive reliability reporting.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Instrument applications and infrastructure with OpenTelemetry for unified traces, metrics, and logs. Use when implementing distributed tracing, service-level troubleshooting, or vendor-neutral observability.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.