DevOps 与云

alloy

205devops-cloud

Build a unified telemetry pipeline with Grafana Alloy — one OpenTelemetry-compatible binary that collects metrics, logs, traces, and profiles and ships to Grafana Cloud / Prometheus / Loki / Tempo / Pyroscope. Covers the Alloy config language (blocks, `sys.env`, component refs), `prometheus.scrape` → `remote_write`, `loki.source.file` + `loki.process` → `loki.write`, `otelcol.receiver.otlp` → `otelcol.exporter.otlp`, `pyroscope.scrape`, K8s / Docker / EC2 discovery, relabeling, modules (`import.file/git/http`), clustering, Fleet Management `remotecfg`, the Alloy UI at `:12345`, and `alloy fmt` / `alloy validate`. Use when writing a `config.alloy`, replacing Grafana Agent / OTel Collector, scraping K8s pods, parsing logs, ingesting OTLP, or debugging "Alloy isn't sending anything" — even when the user says "set up the agent", "write me a scrape config", "drop these logs before sending", or "OTel collector config" without naming Alloy.

grafana

tempo

205devops-cloud

Stand up Grafana Tempo as a cost-efficient distributed-tracing backend that only needs object storage, and write TraceQL queries against it. Covers OTLP + Jaeger + Zipkin ingestion, the distributor → live-store → block-builder → object-storage write path, metrics-generator for RED spanmetrics + service graphs, Helm `tempo-distributed` deployment, multi-tenant `X-Scope-OrgID`, TraceQL span / resource / event scopes, structural operators (`>>`, `<<`), `rate()` + `quantile_over_time` metrics, and the traces-to-logs / metrics / profiles datasource links. Use when deploying Tempo, writing a TraceQL query for slow / errored requests, debugging "no traces showing in Explore", sizing queriers / compactors, configuring S3 / GCS / Azure block storage, or wiring trace ↔ log ↔ profile correlation — even when the user says "tracing backend", "find slow requests", "show me the service graph", "store traces in S3", "Jaeger compatible store", or "what called this span" without naming Tempo.

grafana

temporal-developer

198devops-cloud

Develop, debug, and manage Temporal applications across Python, TypeScript, Go, Java, .NET, Ruby, and Rust. Use when the user is building workflows, activities, or workers with a Temporal SDK, debugging issues like non-determinism errors, stuck workflows, or activity retries, using Temporal CLI, Temporal Server, or Temporal Cloud, or working with durable execution concepts like signals, queries, heartbeats, versioning, continue-as-new, child workflows, or saga patterns. Also use when the user mentions "run a Temporal workflow from the CLI", "start a dev server", "run temporal server start-dev", "temporal workflow start", "temporal workflow execute", "temporal workflow signal", "temporal workflow query", "temporal workflow update".

temporalio

byted-mediakit-audio

面向音频文件或视频中的音轨，处理语音边界定位、音频媒资信息探测、音频转码与码流封装适配、人声与背景声分离等目标。若对象和目标族已明确属于音频内容理解、音频转码、音频格式治理或音轨分离，但具体做法不确定，可先加载本 Skill 探索。

byted-mediakit-video

面向视频文件的智能处理、媒资理解、画质治理与画质检测、抽帧、隐私保护、语音转字幕、字幕提取、字幕擦除、水印处理、精彩片段与高光拆条分析生成、剧情结构化与剧本整理、场景与语义分段、画面文字识别、视频转码转封装及抠像换脸等目标。若对象和目标族已明确属于视频增强、视频分析理解、视频内容结构化、从视频提取字幕、语音转字幕、视频字幕识别或擦除、视频隐私脱敏、视频媒资探测或分发适配，但具体能力不确定，可先加载本 Skill 探索。

byted-mediakit-image

面向单张或批量图片的视觉处理、质量优化、内容理解与基础编辑目标，适用于图片尺寸缩放与体积治理、元信息探测、裁剪旋转翻转与圆角、颜色与锐化清晰度调整、负片、模糊与打码、水印、背景移除、文字识别、画质评估与智能裁剪等。若对象和目标族已明确属于图片优化、图片理解或图片隐私保护，但具体做法不确定，可先加载本 Skill 探索。

byted-mediakit-editing

面向音频、视频或图片素材组成成片的编辑制作目标，适用于时间线裁剪与拼接、速度和音量调整、视频滤镜、运镜特效、转场、画面裁切旋转翻转、画面叠加、字幕压制、动图截取、淡入淡出、音视频提取与合流、音频混合、文字滚屏成片、图转视频以及多画面空间组合等操作。若用户要给视频添加滤镜效果，或对象和目标族已明确是对现有素材做剪辑、合成、叠加、混合或成片编排，但具体做法不确定，可先加载本 Skill 探索。

mongodb-atlas-stream-processing

165devops-cloud

Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnostics, and tier sizing. Supports Kafka, Atlas clusters, S3, HTTPS, and Lambda integrations for streaming data workloads and event processing. NOT for general MongoDB queries or Atlas cluster management. Requires MongoDB MCP Server with Atlas API credentials.

mongodb

dt-platform-costs

157devops-cloud

Query and analyze a Dynatrace tenant's ACTUAL billing and usage data with DQL against dt.system.events — DPS consumption breakdown, cost-normalized spend ranking, included volume deduction, chargeback/showback, cost drivers, spending trends, cost investigation, metrics ingest optimization, query cost attribution, workflow total cost, entity-level cost drill-down (RUM, hosts, synthetic, K8s), and AI/LLM cost (AI Units, AI Function Standard Calls, AI-generated query consumption). Directs licensing/entitlement questions to documentation (not via DQL). USE ONLY to query/analyze the tenant's actual consumption. Do NOT use for conceptual 'explain' questions about how DPS billing/pricing works or what units/weights/the rate card mean — see Dynatrace documentation. Do NOT use for making DQL queries faster or cheaper to run (query optimization, reducing scanned data/consumption per run, filter-early best practices) — that belongs to dt-dql-essentials. This skill MEASURES consumption; it does not tune queries.

dd-apm

156devops-cloud

APM - install, onboard, instrument, enable, set up, configure, traces, services, dependencies, performance analysis. Use for any request involving Datadog APM setup, instrumentation (SSI, ddtrace, agent install), or analysis.

datadog-labs

dd-pup

147devops-cloud

Datadog CLI (Rust). OAuth2 auth with token refresh.

datadog-labs

dt-obs-gcp

135devops-cloud

GCP cloud resources including Compute Engine, GKE, Cloud Run, Pub/Sub, VPC networking, DNS, IAM, Secret Manager, and monitoring. Monitor GCP infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across projects and folders.

dt-obs-azure

132devops-cloud

Azure cloud resources including VMs, VMSS, SQL Database, Storage, AKS, App Service, Functions, VNet networking, load balancers, Event Hubs, Container Apps, and Key Vault. Monitor Azure infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across subscriptions and resource groups.

dt-obs-predictive-analytics

131devops-cloud

Predictive analytics for Dynatrace — time series forecasting with the timeseries-forecast tool, capacity saturation planning, trend and anomaly detection across hosts, services, and infrastructure.

planetscale-readonly-inventory

128devops-cloud

Collect read-only evidence about PlanetScale org, database, branches, webhooks, backups, roles, Insights, recommendations, and traffic configuration.

planetscale

dt-migration

126devops-cloud

Migrate Dynatrace classic and Gen2 entity-based DQL to Smartscape equivalents. Covers three scenarios. (1) mass data queries filtered by classic entity conditions — migrate to direct dimension filters first, Smartscape only as fallback; (2) mass data queries using entity subqueries for filtering — same dimension-first strategy; (3) pure entity list queries — migrate fetch dt.entity.* to smartscapeNodes. Also handles entityName, entityAttr, classicEntitySelector, and classic relationship patterns.

planetscale-best-practices-matrix

126devops-cloud

A concise feature matrix for deciding which PlanetScale safety, observability, and automation recommendations apply by engine.

planetscale

planetscale-postgres-safety-review

126devops-cloud

Review PlanetScale Postgres for Traffic Control, query tags, roles, pg_strict, backups/PITR, private connectivity, webhooks, branches, and safe agent operation.

planetscale

dt-obs-hosts

125devops-cloud

Host and process metrics including CPU, memory, disk, network, containers, and process-level telemetry. Use when analyzing infrastructure health, resource utilization, process consumption, or host discovery. Also use when building timeseries queries for host metrics that feed into analytical workflows like anomaly detection, forecasting, or seasonality analysis. Trigger: "show hosts", "CPU usage", "memory utilization", "disk space", "high CPU", "host with most free disk", "top hosts by CPU", "top processes by memory", "Linux hosts in AWS", "what databases are running", "infrastructure costs by cost center", "hosts running EOL Java", "container monitoring", "listening ports", "process resource consumption", "CPU forecast", "memory anomaly", "host seasonality". Do NOT use for explaining existing queries, product documentation questions, Kubernetes pod/workload queries (use dt-obs-kubernetes), AWS cloud resource inventory (use dt-obs-aws), or service-level metrics (use dt-obs-services).

dt-obs-kubernetes

125devops-cloud

Kubernetes cluster, pod, node, and workload monitoring. Use when analyzing K8s health, resource optimization, pod failures, OOMKills, scheduling, or security posture. Also use for Kubernetes operational events like pod restarts, OOM events, evictions, and cluster event history. Trigger: "Kubernetes pods", "K8s cluster health", "OOMKill", "pod restarts", "container CPU", "namespace resource usage", "over-provisioned pods", "privileged containers", "pod placement", "K8s node capacity", "running containers by cluster", "workload scheduling", "pod evictions", "K8s labels and annotations", "kubernetes events", "pod restart events", "OOM events", "K8s event history". Do NOT use for explaining existing queries, product documentation questions, AWS-specific resource queries, service-level RED metrics, distributed tracing, or log analysis — use the relevant skill instead.

dt-obs-aws

125devops-cloud

AWS cloud resource monitoring including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, S3, DynamoDB, SQS/SNS, and cost optimization. Use when analyzing AWS infrastructure, resource inventory, security compliance, capacity planning, or cost savings. Trigger: "show EC2 instances", "find RDS databases", "VPC resources", "AWS cost optimization", "Lambda functions", "ECS services", "security groups", "unattached EBS volumes", "AWS load balancer topology", "publicly accessible databases", "AWS dashboards". Do NOT use for explaining existing queries, product documentation questions, generic host CPU/memory metrics (use dt-obs-hosts), application-level tracing (use dt-obs-tracing), or log analysis (use dt-obs-logs).

dt-obs-problems

124devops-cloud

DAVIS problem analysis including root cause identification, impact assessment, and correlation with other telemetry. Use when querying or investigating detected problems. Trigger: "active problems", "root cause analysis", "problem impact", "affected users", "list problems", "P-12345 details", "recurring problems", "problem history", "problem trending", "blast radius", "which entity caused the problem", "problems affecting Kubernetes", "problems by service". Do NOT use for explaining existing queries, product documentation questions, generic log searching, distributed tracing, or host-level resource monitoring.

dt-obs-logs

124devops-cloud

Log querying, filtering, pattern analysis, and error rate calculation. Use when searching application or infrastructure logs, analyzing error patterns, or correlating log data. Trigger: "show error logs", "search logs for keyword", "log error rate", "recent errors", "logs from last hour", "find log entries", "top error messages", "log patterns", "parse JSON logs", "logs by process group", "log trends over time", "log entry counts per minute". Do NOT use for explaining existing queries, product documentation questions, distributed tracing or span analysis (use dt-obs-tracing).