Why Convergence Over Pipelines

The decision to adopt a convergence-based model instead of a traditional pipeline approach in Prodvana stems from various factors that make convergence more robust, efficient, and flexible for the management of cloud-native SaaS deployments.

Key Reasons

  1. Independent Updates: In a pipeline-based system, deployments proceed in a specific sequence, creating dependencies that slow development and deployment. Convergence allows each component to be updated independently, speeding up deployments and allowing for more parallel development.

  2. Desired State Management: Convergence models focus on achieving and maintaining a desired state across your system. This approach contrasts with pipelines, where the focus is often on the process of change. The desired state approach reduces the chances of configuration drift and inconsistencies that can lead to errors and system instability.

  3. Idempotence: In convergence models, operations can be repeated without leading to different outcomes. This is not the case in pipeline models. Idempotence in convergence models contributes to consistency and reliability, especially in environments where repeated operations are common.

  4. Adaptability: Convergence-based systems are flexible and adaptable, catering to various computing platforms. This differs from many pipeline systems, which may require significant changes or specific configurations to support different platforms.

  5. Extensibility: Convergence-based systems are designed to be easily extended. Prodvana supports both runtime extensions and delivery extensions. In contrast, extending traditional pipeline systems can often be more challenging and less seamless.