Manage clusters and applications at scale with Argo CD Agent on Red Hat OpenShift GitOps

Manage clusters and applications at scale with Argo CD Agent on Red Hat OpenShift GitOps What is a centralized deployment model? What is a distributed deployment model? Why Argo CD Agent? Managed and autonomous modes Event-driven architecture Encryption Get started today Try this interactive demonstration Red Hat OpenShift Container Platform | Product Trial About the author Gerald Nunn More like this How Banco do Brasil uses hyperautomation and platform engineering to drive efficiency 2025 Red Hat Ansible Automation Platform: A year in review Technically Speaking | Taming AI agents with observability Ready To Launch | Compiler Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share The Argo CD Agent is now Generally Available with the release of Red Hat OpenShift GitOps 1.19. Organizations using Kubernetes and OpenShift have widely adopted the GitOps methodology to manage clusters and applications, with Argo CD being the leading open source GitOps solution on Kubernetes. However, organizations adopting Argo CD have faced challenges selecting an appropriate Argo CD deployment model. There's often a choice between prioritizing scalability across multiple clusters or to implement centralized GitOps management. The Argo CD Agent for OpenShift GitOps solves this challenge by combining the best of both traditional Argo CD deployment models: Centralized and distributed. Prior to the Argo CD Agent, organizations adopting Argo CD would have to choose between two deployment models, each with its own strengths and weaknesses. This could also mean adopting different deployment models for different use cases. In the centralized model, an organization deploys a single Argo CD that centrally manages a fleet of clusters. This had the advantage of providing a "single pane of glass" for management, making it convenient for teams to manage a variety of infrastructure and applications. The disadvantage of this approach was that it could only scale so far. An organization with large fleets of clusters or application inventory would inevitably hit a point where Argo CD performance became problematic. Additionally, this model is a single point of failure (SPOF).