Deploy Applications to Kubernetes with Helm and Service Mesh

This workflow orchestrates a full Kubernetes deployment across seven phases: container preparation, K8s manifest creation, Helm chart scaffolding, service mesh configuration, security hardening, observability setup, and final deployment. Each phase names specific sub-skills to invoke and gives a copy-paste prompt for invoking that skill, and the workflow closes with a six-item quality-gate checklist before the deployment is considered complete.

Use this workflow when deploying to Kubernetes, creating Helm charts, configuring a service mesh, setting up K8s networking, or implementing K8s security. It is not a substitute for environment-specific validation, testing, or expert review, and work should pause for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Phase 1 (Container Preparation) creates a Dockerfile, builds and optimizes the container image, pushes it to a registry, and tests it, invoking docker-expert and k8s-manifest-generator. Phase 2 (K8s Manifests) creates a Deployment, configures a Service, sets up a ConfigMap, creates Secrets, and adds Ingress, invoking k8s-manifest-generator and kubernetes-architect. Phase 3 (Helm Chart) creates the chart structure, defines values.yaml, adds templates, configures dependencies, and tests the chart via helm-chart-scaffolding. Phase 4 (Service Mesh) chooses and installs a mesh, configures traffic management, sets up mTLS, and adds observability, invoking istio-traffic-management, linkerd-patterns, and service-mesh-expert. Phase 5 (Security) configures RBAC, sets up NetworkPolicy, enables PodSecurity, configures secrets, and implements mTLS via k8s-security-policies and mtls-configuration. Phase 6 (Observability) installs the monitoring stack, configures Prometheus, creates Grafana dashboards, sets up alerts, and adds distributed tracing via prometheus-configuration and grafana-dashboards. Phase 7 (Deployment) configures CI/CD, sets up GitOps, deploys to the cluster, verifies the deployment, and monitors the rollout via deployment-engineer and gitops-workflow.

Before the workflow is considered done, a six-item quality-gate checklist must pass: containers working, manifests valid, Helm chart installs, security configured, monitoring active, and deployment successful.

Each phase's skill is invoked with its own copy-paste prompt, for example:

Use @docker-expert to containerize application for K8s

and, for the manifest phase:

Use @k8s-manifest-generator to create K8s manifests

The workflow is also related to three neighboring workflow bundles: cloud-devops, terraform-infrastructure, and docker-containerization - useful when the deployment work extends beyond Kubernetes itself into broader cloud infrastructure or containerization concerns.

Platform and DevOps engineers running a complete Kubernetes rollout - from containerizing an application through Helm packaging, service mesh and security configuration, observability, and final GitOps-driven deployment - rather than handling each phase as a disconnected task. It suits teams who want a consistent, repeatable phase-by-phase structure with named sub-skills and ready-to-use prompts at each step, rather than improvising the deployment sequence each time.