Learn ARGO-WORKFLOWS with Real Code Examples

Highly scalable using Kubernetes scheduler

Supports parallel execution for faster completion

Resource allocation depends on Kubernetes cluster size

Efficient artifact management using object storage

Large workflows may require careful DAG structuring

Use Kubernetes RBAC to restrict workflow access

Manage secrets with Kubernetes Secrets

Run containers with minimal privileges

Limit resource requests and enforce quotas

Audit workflow execution and artifact storage

Argo UI dashboards for workflows and steps

CLI commands for real-time inspection

Workflow events tracked via Kubernetes API

Integrate with Prometheus/Grafana

Audit logs and artifact tracking

Modular YAML templates per workflow

Version-controlled manifests

Validate workflows with `argo lint`

Use artifacts for reproducibility

Monitor logs for debugging and improvement