479건 · 관련도순
Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident management.
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Select and implement the right Azure compute platform for a workload. Decision tree guides choice based on workload characteristics, scaling needs, and operational maturity. Covers serverless, PaaS, containers, Kubernetes, and IaaS patterns.
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Configure microsegmentation policies to enforce least-privilege workload-to-workload access using tools like VMware NSX, Illumio, and Calico, preventing lateral movement in zero trust architectures.
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Marketing project management and execution excellence for B2B SaaS campaigns. Use this skill when coordinating multi-channel campaigns, allocating team resources, planning agile marketing sprints, running QBRs with clients, managing project timelines, balancing marketing workload, or implementing marketing operations scrum. Also triggers on: campaign coordination, resource allocation, agile marketing, sprint planning, client success, QBR, project timeline, marketing ops scrum, workload balancing.
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Use when working with Coreweave — coreWeave GPU cloud management covering Kubernetes namespace inventory, GPU workload status, virtual server instances, persistent volume claims, node allocation, billing analysis, and network configuration. Use for comprehensive CoreWeave infrastructure assessment and GPU workload optimization.
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Use when working with Kubescape — kubescape Kubernetes security posture analysis. Covers NSA/CISA framework assessment, MITRE ATT&CK mapping, CIS Kubernetes benchmarks, workload scanning, RBAC analysis, and network policy evaluation. Use when assessing Kubernetes cluster security, evaluating compliance frameworks, or analyzing workload configurations.
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bu skill covers hardening managed Kubernetes clusters on EKS, AKS, and GKE by implementing Pod Security Standards, network policies, workload identity, RBAC scoping, image admission controls, and runtime security monitoring. It addresses cloud-specific security features including IRSA for EKS, Workload Identity for GKE, and Managed Identities for AKS.
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Configure microsegmentation policies to enforce least-privilege workload-to-workload access using tools like VMware NSX, Illumio, and Calico, preventing lateral movement in zero trust architectures.
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Plan, evaluate, and adopt agent infrastructure for a named workload. Use for agent runtime/framework selection, agent evaluation or observability plans, memory and tool boundaries, infrastructure cost controls, and organizational adoption. Covers workload-first comparison, risk and recovery planning, held-out evaluation, cost accounting, and staged rollout. Not a vendor ranking or a production certification. NOT for implementing a specific agent behavior (agentic-patterns), building a specific agent (ai-engineer), prompt optimization (prompt-engineer), or conventional ETL workflow design (jury_rig-architect).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Configure microsegmentation policies to enforce least-privilege workload-to-workload access using tools like VMware NSX, Illumio, and Calico, preventing lateral movement in zero trust architectures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
공장의 설비, 인력, 자재, 납기를 고려해 생산 순서를 검토합니다. 작업 전환과 공정별 부하를 조정하고 설비 고장이나 자재 부족 시 계획 수정을 돕습니다.
Kubernetes 설정 파일 작성과 검토, 장애 원인 조사를 돕습니다. 상태 확인, 권한, 리소스 제한, 자동 확장 설정 예시와 조사 명령을 참고할 수 있습니다.
Helps design ClickHouse tables, write analytical queries, and improve slow queries. Covers loading data in batches, preparing reusable summaries, and monitoring performance for large datasets, real-time dashboards, and time-series analysis.
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TorchTitan과 PyTorch로 대규모 언어 모델 사전 학습을 설정합니다. 여러 GPU에 작업을 나누고 단일·다중 노드 실행과 학습 저장·재개를 지원합니다.
Qdrant에 텍스트 등의 특징을 벡터로 저장해 유사 검색을 구현합니다. 속성 필터링, AI 답변용 자료 검색, 실시간 추천과 대규모 운영 설정을 지원합니다.
Analyze application and system performance to find bottlenecks, the points that slow processing. Use resource usage and performance data to plan improvements to resource allocation, load balancing, caching, and algorithms, then compare results after changes.
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Assembles teams of AI agents by analyzing task complexity, required skills, and resource needs. It covers selecting specialists, adjusting team size to workload, and refining coordination using patterns from past executions.
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Coordinate decisions across multiple AI agents by synchronizing shared memory, combining knowledge, and weighing input by expertise. The skill also guides workload distribution, conflict handling, and recording decisions with their rationale.
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Coordinate multiple AI agents in a mesh, a network where peers communicate directly. It guides shared decisions, task assignment based on skills and workload, network monitoring, and recovery when agents fail or connections break.
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Estimate future spending from recent usage costs, with projections for 7, 30, 90, and 365 days. When a budget is configured, see how many days remain before spending reaches key budget thresholds.
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Coordinates multiple AI agents with agentic-flow to run tasks in parallel or through dependent stages. It covers team communication structures, shared memory, workload balancing, failure recovery, and performance monitoring for complex workflows.
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Add glow, depth-based blur, color correction, and other finishing effects to Three.js scenes. Covers combining effects with EffectComposer, writing custom shaders for screen effects, handling window resizing, and adjusting rendering workload.
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Use SymPy to simplify expressions, solve equations, and calculate derivatives, integrals, and matrices with exact symbolic results. Specify assumptions, verify solutions, and turn mathematical expressions into numerical functions, source code, or LaTeX output.
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Follow guidance to create and operate Kubernetes clusters on Azure Kubernetes Service. Configure groups of worker machines, automatic scaling, networking, monitoring, identity integration, and upgrades, with command examples and Terraform configuration for repeatable setup.
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