Total 55,877 skills, DevOps & Cloud Services has 3436 skills
Showing 12 of 3436 skills
Use when performing a release, cutting a new version, or running the full release process for the jackin project
Cloudflare Workers, Deno Deploy, Vercel Edge Functions, edge patterns (geo-routing, caching). Use when implementing edge compute, CDN logic, or global low-latency APIs.
Manage Tencent Cloud CLS alarm policies, notice groups, shields and alarm execution logs. Use when the user asks to: list / create / modify / delete CLS alarms, enable or disable alarms, manage notice recipients (SMS / email / webhook), mute alarms during deploys, or view which alarms fired and when. For searching the underlying log content, use the companion `tencentcloud-cls` skill.
Manage Tencent Cloud TKE (Tencent Kubernetes Engine) clusters and workloads. Use when the user asks to: list clusters, check cluster / node health, list pods or services, scale a Deployment, do a rolling restart, fetch kubeconfig, view recent K8s events, manage node pools. Combines the official tencentcloud-sdk-python TKE client (cluster metadata) with kubectl for in-cluster operations.
Discover the user's local AWS context (active profile, region, account ID, caller identity) at the start of any AWS task. Use this skill before any other AWS work — deploying to SageMaker, creating resources, calling AWS APIs, or anything that touches an AWS account. Use it especially when the user has not specified a region or profile explicitly, when they say things like "use my AWS account", "deploy to AWS", "use my profile", or when about to make any AWS CLI or SDK call. Never guess the region or account ID — always use this skill to read it from the local configuration first.
Optimizes GKE costs, rightsizes workloads, and configures Spot VMs, CUDs, cost allocation, and resource quotas. Use when optimizing GKE cluster or workload costs, configuring GKE cost allocation or quotas, rightsizing CPU/memory requests, or selecting Spot VMs and machine types. Don't use for general compute class provisioning or GPU Selection (use gke-compute-classes instead).
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.
Pi-hole installation, blocklist management, DNS-over-HTTPS setup, DHCP integration, local DNS records, and troubleshooting broken DNS resolution on a home network.
Mackerel integration. Manage data, records, and automate workflows. Use when the user wants to interact with Mackerel data.
Guides FinOps analysis on AWS, GCP, and Azure—cost visibility and allocation, tagging and showback/chargeback models, rightsizing and waste removal, RI/Savings Plan/CUD recommendations, budgets and forecasts, anomaly detection, unit economics (cost per service/customer), and FinOps cadence with engineering accountability. Use when optimizing cloud spend, analyzing CUR/billing exports, building cost dashboards, explaining bill spikes, or improving allocation—not for GL mapping, capex, depreciation, or month-end ledger close (compute-accounting-manager), enterprise EA negotiation (enterprise-cloud-architect), hands-on resource provisioning (cloud-engineer), or hardware supply efficiency (data-center-compute-supply-efficiency).
Implement database backup strategies. Configure automated backups, retention, and recovery testing. Use when designing backup and recovery procedures.
Execute and monitor Harness pipeline runs via MCP tools. Find pipelines, provide runtime inputs, trigger executions, monitor progress, handle approvals, retry failures, and abort running or stuck executions. Use when asked to run a pipeline, execute a deployment, trigger a build, start a pipeline, deploy a service, check execution status, approve a pipeline, or abort/stop/interrupt executions. Trigger phrases: run pipeline, execute pipeline, deploy, start build, trigger pipeline, check execution, approve deployment, retry failed pipeline, abort execution, stop pipeline, interrupt execution, kill stuck pipeline.