Total 55,943 skills, DevOps & Cloud Services has 3440 skills
Showing 12 of 3440 skills
Manage vCluster (virtual Kubernetes clusters) instances using vind. Use when creating, managing, or operating lightweight virtual clusters for development, testing, or multi-tenancy.
Manage multiple Kubernetes clusters, switch contexts, and perform cross-cluster operations. Use when working with multiple clusters, comparing environments, or managing cluster lifecycle.
Mesh VPN.
Debug and troubleshoot Helm deployment failures, template errors, and configuration issues. Covers helm template, helm lint, dry-run, debugging YAML parse errors, value type errors, and resource conflicts. Use when user mentions Helm errors, debugging Helm, template rendering issues, or troubleshooting Helm deployments.
Netlify development best practices for serverless functions, edge functions, Blobs storage, build configuration, and deployment workflows.
Expert AWS Cloud Advisor for architecture design, security review, and implementation guidance. Leverages AWS MCP tools for accurate, documentation-backed answers. Use when user asks about AWS architecture, security, service selection, migrations, troubleshooting, or learning AWS. Triggers on AWS, Lambda, S3, EC2, ECS, EKS, DynamoDB, RDS, CloudFormation, CDK, Terraform, Serverless, SAM, IAM, VPC, API Gateway, or any AWS service.
This skill should be used when users need to manage progressive delivery via Kargo CLI. It covers freight management, stage promotion, warehouse status, and deployment pipeline operations. Integrates with ArgoCD for GitOps sync. Triggers on requests mentioning Kargo, freight, stage promotion, progressive delivery, or deployment pipelines.
Builds and deploys Firebase SQL Connect (aka Firebase Data Connect) backends with PostgreSQL securely. Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational database with Firebase, or when the user mentions SQL Connect or Data Connect.
Bump the NVIDIA PyTorch base image (`nvcr.io/nvidia/pytorch:<YY.MM>-py3`) used by Megatron-LM CI. Covers the two pin sites (GitHub CI in `docker/.ngc_version.dev` and GitLab CI in `.gitlab/stages/01.build.yml`), the post-bump CI loop (re-run functional tests, refresh golden values, mark broken tests), and the gotchas that bit PRs
Evidence-driven investigation for network, streaming, and protocol-layer bugs. Use when debugging connection resets (ECONNRESET, HTTP/2 RST_STREAM, INTERNAL_ERROR), SSE or long-polling stalls, fixed-time connection drops, CDN/proxy/CGNAT idle timeouts, or any incident where symptoms do not match the obvious cause. Applies falsification-first methodology — layered isolation experiments to pin down the responsible network layer, env-gated runtime instrumentation for non-invasive observation, and counter-review agent teams to challenge single-cause assumptions. Strongly trigger on "socket closed unexpectedly", "stream interrupted", "ECONNRESET", "HTTP/2 INTERNAL_ERROR", "fails after N seconds", "works sometimes but not always", "upstream silent for X seconds", or any scenario where the investigator might jump to conclusions before evidence. Generalizes to any multi-layer system investigation where assumption-first thinking is the failure mode.
Publishing, upgrading, and deploying Sui Move packages. Use this skill when the user needs to publish a package, upgrade a published package, deploy to multiple networks, serialize transactions for multisig signing, run a local Sui network (localnet), prepare for Mainnet launch, monitor production deployments, or debug dry run failures. Also use when the user asks about sui client publish, sui client upgrade, UpgradeCap, upgrade policies, Published.toml, --serialize-output, localnet, mainnet launch checklist, gas estimation, multisig publishing, production monitoring, rollback, incident response, devInspectTransactionBlock, or --dry-run.
Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.