Argo Workflows vs ONAP

Argo Workflows is a free, open-source engine for orchestrating container-based jobs on Kubernetes. Workflows can be arranged as sequential steps or as tasks linked in a directed acyclic graph, with each step running in a container. The project lists machine learning pipelines, data and batch processing, infrastructure automation, and CI/CD as use cases. Controls include loops, conditionals, retries, timeouts, suspension and resumption, cancellation, and limits on parallel work. Cron scheduling, workflow archiving, a UI for viewing and managing runs, and Prometheus metrics are included. Artifact support covers S3, Artifactory, Alibaba Cloud OSS, Azure Blob Storage, HTTP, Git, GCS, raw artifacts, and plugins. The server provides REST API support over HTTP and gRPC, with client libraries for Java, Go, Python, and TypeScript. Argo Workflows is self-hosted and can run on any Kubernetes cluster. Its listed plan costs nothing, and the official pages list no paid plans or usage limits. Administrators should configure transport security, authentication, roles, and permissions; workflow pods run as root by default unless their security context is set.

ONAP is a free, open-source platform for designing, orchestrating, observing, and automating network and edge services. It supports lifecycle management for physical, virtual, and cloud-native network functions, with real-time, policy-driven orchestration. Design and runtime capabilities include implementation, analytics, monitoring, alarm and event correlation, and closed-loop automation for service optimization. Role-based access through the Portal Framework serves service designers and operations personnel. ONAP is modular, so users can select orchestration functions; its Operations Manager uses Kubernetes to deploy, monitor, and manage component lifecycles. Published blueprints cover 5G, virtual CPE, broadband, VoLTE, and cross-domain VPN services. A full deployment guide lists 224 GB RAM, 160 GB disk, and 112 vCores, while selected components can substantially reduce those requirements. ONAP supports deployment on Kubernetes on bare metal or environments such as OpenStack, Azure, and AWS. It runs across API, Linux, self-hosted, and web contexts. Free introductory training and a paid ONAP Fundamentals course are available.