Node.js – Run Node.js builds & tests with dependency caching.

Python – Run tests with pytest/tox, cache pip dependencies.

Java (Maven) – Compile & test Java projects using Maven.

.NET – Build and test .NET Core projects.

Go – Build, lint, and test Go projects.

Rust – Build & test Rust projects with Cargo.

PHP – Run Composer install & PHPUnit tests.

Ruby – Run Bundler setup & RSpec/Rake tests.

Docker Build & Push – Build Docker images and push to GHCR or DockerHub.

Docker Compose Test – Run integration tests using docker-compose.

Kaniko Build – Build Docker images without Docker using Kaniko.

AWS Deploy – Deploy artifacts to AWS (S3, ECS, Lambda).

GCP Deploy – Deploy to Google Cloud (Cloud Run, GKE).

Azure Deploy – Deploy to Azure WebApps or AKS.

Azure AKS – Deploy Kubernetes manifests to Azure Kubernetes Service.

Azure Functions – Deploy serverless applications to Azure Functions.

Azure Container Apps – Deploy containerized workloads to Azure Container Apps.

Azure Static Web Apps – Deploy JAMstack or SPA apps to Azure’s static hosting service.

Azure Bicep/ARM – Provision Azure infrastructure using Bicep or ARM templates.

Terraform Plan & Apply – Validate, plan, and apply Terraform configurations.

Ansible Lint – Lint Ansible playbooks for best practices.

Kubernetes Deploy – Deploy Kubernetes manifests via kubectl.

Helm Deploy – Deploy applications using Helm charts.

Helm Lint – Validate Helm charts with linting and template rendering.

Kustomize Deploy – Deploy manifests with Kustomize overlays.

Kubernetes Validate – Dry-run manifest validation.

Kubernetes Policy Check – Enforce best practices with kube-score.

ArgoCD Sync – Trigger ArgoCD application sync.

Kubernetes Image Update – Patch deployments with new image tags.

Lint & Format – Run code style checks and format validation.

Security Scans – Run Trivy or similar scanners on codebase & dependencies.

Release – Auto-generate GitHub Releases from tags with changelog notes.

Train ML Model – Runs a training pipeline for ML/DL projects (PyTorch, TensorFlow, Hugging Face).

Test ML Model – Executes unit tests and model evaluation metrics.

Deploy to Hugging Face Hub – Publishes models to Hugging Face’s Model Hub.

Deploy Model with Docker – Builds and pushes ML model APIs as Docker containers.

MLflow Experiment Tracking – Logs and tracks experiments in MLflow.

AWS SageMaker – Train and deploy ML models on AWS SageMaker.

GCP Vertex AI – Train and deploy ML models on Google Cloud Vertex AI.

Azure ML – Train and deploy ML models using Azure Machine Learning.

Build & Test MCP Server – CI workflow for validating MCP servers (Node.js or Python).

Publish MCP Server – Publishes MCP servers to npm or PyPI.

MCP Integration Test – Runs integration tests between MCP client(s) and server(s).

Deploy MCP Server (Docker) – Builds and pushes MCP servers as containerized services.