Rivery, providers of a DataOps platform, is introducing Rivery CLI (command-line-interface), enabling customers to take the power, speed, and scalability of DataOps to a new level.
The Rivery CLI enables data engineers and other data developers to remotely execute, edit, deploy, and manage data pipelines via CLI and convert data pipelines into infrastructure as code (IaC).
The Rivery CLI modifies and stores data pipeline configurations as YAML configuration files. Developers can push these YAML files into the Rivery platform to update the corresponding data pipelines
The Rivery CLI empowers developers to create, edit, and save Logic Rivers configurations in a simple text editor.
This allows teams to sync pipeline logics – such as SQL-based transformations – within version control systems (VCS) such as GitHub.
With this Git compatibility, teams can potentially implement DevOps practices, including track changes, continuous integration and continuous deployment (CI/CD), and code reversion.
Rivery CLI streamlines the DataOps process in several ways:
- Launch data pipelines and data infrastructure via code – Remotely launch pre-built data pipelines for 150+ data sources, add custom data sources with Rivery’s Custom API, schedule data ingestion, build Logic Rivers, and more, all from a command-line interface.
- Enhance data transformations – Access Rivery’s transformation capabilities via code. Maintain SQL transformations in Git, unlock track changes, bulk updates, and script-based modification.
- Implement version control – Manage all logics and transformations in version control systems to maintain total command over and visibility into the data product delivered to stakeholders.
- Incorporate development best-practices – With Git integration, optimize production cycles with agile development, and apply DevOps functions to pipeline code, such as CI/CD, debugging, and staging environments.
- Revise and reinstate code – Store all versions of transformations and Rivery Kits for revision and reversion.
Rivery CLI enables data developers and data engineers to access and implement the Rivery platform in the format they feel most comfortable with: code.
At the same time, data analysts or even non-technical personnel can still build data infrastructure using Rivery’s point-and-click UI in parallel to data engineering efforts.
Developers can then edit the infrastructure created in the UI with Rivery CLI, allowing total synergy between the data initiatives of technical and non-technical teams.
For more information about this release, visit https://rivery.io/.