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2 posts about Argo CD. Every summary links to the original.
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Argo CD is a GitOps controller that treats Git as the desired state and continuously reconciles it against what actually runs in each cluster. It maps the parts of that loop and why pull-based agents change its scale.
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This article continues a series on Red Hat Developer Hub, describing how platform engineers create golden path templates to standardize developer workflows. The sample template scaffolds a Go project with a Tekton pipeline, Argo CD manifests, a devfile, and catalog-info.yaml containing annotations that map to enabled plug-ins. Developers use the template from the self-service screen, completing a form to specify application metadata, image registry, OpenShift details, and Git repository. After scaffolding, automated CI/CD is triggered by a Git commit, and developers monitor Tekton PipelineRuns, Argo CD sync status, container images from Quay, and Kubernetes resources from tabs within Developer Hub. The article provides step-by-step instructions for both platform engineers and developers, including template authoring, registration, scaffolding, and subsequent observability.
Red Hat conducted a performance and scale test of the argocd-agent pull architecture for GitOps, using 42 physical machines, 500 spoke clusters, and software including OpenShift 4.21 and OpenShift GitOps 1.20. The pull model decentralizes reconciliation to lightweight agents on each managed cluster, which pull configurations from a central hub, improving security by eliminating inbound administrative ports and reducing cross-cluster network traffic by up to 80%. In the bootstrap scenario, generating and syncing 31,200 applications across 480 clusters completed in 13 minutes 3 seconds, while the sync-to-commit scenario, which includes a polling delay, took 13 minutes. The test revealed bottlenecks including Kubernetes API limits on the hub, informer processing slowdowns causing watch restarts, event writer retry issues under load, and ApplicationSet controller RAM consumption. The team also deleted all 31,200 applications in 4 minutes 53 seconds using cascading deletion, and the insights are informing future OpenShift GitOps releases.
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