argo-expert_skill

This skill helps DevOps teams master Argo CD, Workflows, and Rollouts for scalable, secure GitOps deployments across multi-cluster environments.

Shell

25

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill martinholovsky/claude-skills-generator --skill argo-expert

SKILL.md42.7 KB

Overview

This skill is an Argo ecosystem expert for Argo CD, Workflows, Rollouts, and Events, focused on production-grade GitOps, progressive delivery, and workflow orchestration. It helps DevOps, SRE, and platform teams design secure, scalable multi-cluster delivery pipelines and advanced deployment strategies. The skill emphasizes test-driven configuration, observability, and operational resilience for production environments.

How this skill works

I inspect and validate Argo manifests, recommend architecture patterns (App-of-Apps, ApplicationSet, sync waves), and design workflows, rollouts, and analysis templates for automated verification. I produce TDD-oriented test workflows, dry-run and schema checks, rollout analysis jobs, and progressive delivery configurations with traffic shaping and automated rollbacks. I also advise on RBAC, secrets handling, multi-cluster targets, monitoring integration, and disaster recovery.

When to use it

Implementing GitOps pipelines or migrating to Argo CD for declarative delivery
Designing CI/CD or data pipelines with Argo Workflows and artifact caching
Running progressive delivery (canary, blue-green) with Argo Rollouts and metric-based analysis
Operating applications across multiple Kubernetes clusters or regions
Hardening Argo stack for production: RBAC, secrets encryption, supply chain controls

Best practices

Adopt TDD: create failing validation/workflow tests, then implement minimal configs to pass
Keep Git as single source of truth and separate app definitions from manifests
Use ApplicationSet and matrix generators for DRY multi-cluster deployments
Add AnalysisTemplates for automated runtime verification and safe promote/rollback
Limit blast radius with progressive delivery and automated metric gates
Enforce least-privilege RBAC, encrypted secrets, and image provenance checks

Example use cases

Create an App-of-Apps root application to manage dozens of teams’ apps with consistent sync policies
Build a workflow test suite that runs kubeval, kubeconform, and kubectl dry-run before merges
Configure an ApplicationSet to deploy a service to dev/staging/prod clusters using matrix generators
Implement a canary rollout with traffic shifting (Istio/NGINX) and analysis jobs that run E2E tests and check error rates
Design a disaster recovery plan using multi-cluster failover and Git-backed restore procedures

FAQ

Run schema and strict validation (kubeval, kubeconform), perform server-side dry-run applies, and execute test Workflows that mimic real syncs in a staging cluster.

When should I use ApplicationSet vs App-of-Apps?

Use ApplicationSet for templated, multi-cluster or matrix-driven deployments; use App-of-Apps when you need to manage a curated collection of independent Application resources as a single unit.