Ellie Horvath
DataOps.live, the software company dedicated to helping organizations build and manage their essential Data Applications and Data Products more effectively, has released the latest version of its revolutionary DataOps platform, combining a unified developer experience with the ability to perform DataOps at scale.
“No-Fear Enterprise Data Engineering at Scale means enabling Data Product developers to build faster, handling more data domains at the same time, building larger and more sophisticated Data Products at the same time, while data engineers remain 100% in control,” says Thomas Steinborn, VP of Products. “We are delivering enhancements across five functional areas to deliver on this premise.”
DataOps on Kubernetes
We’re excited to announce support for Kubernetes (our most requested feature) which enables customers to dynamically scale their enterprise DataOps infrastructure within their highly managed, highly available cloud architecture while using compute resources mor efficiently and reducing cost. Load balance all your workloads across nodes, and let Kubernetes ensure high availability for all your data pipelines.
DataOps Unified Developer Experience
DataOps.live is launching its new unified developer experience, a fully hosted IDE with all the pre-packaged components and plugins needed for a highly efficient Snowflake development experience. Just click one button and you have all the power, control and usability features of a locally installed IDE like Visual Studio, without ever installing anything. It’s available wherever and whenever you need it. This is the final step in enabling Data Product developers to be as efficient and productive as software developers. Day-to-day developer productivity can increase by up to 50% depending on the amount of development time they are spending every day.
DataOps.live introduces full “Data Product” objects
Dataops.live now supports Data Product objects as code, bringing a more natural, streamlined experience to Data Product creation and management. Data Product owners can organize projects by Data Product and dataset; data engineers can find the one table they need among thousands and have fewer merge conflicts; new developers have a faster learning curve; and Data Product stakeholders can have their Data Product refreshed in their data catalogs in seconds.
DataOps Safety Net for Snowflake
Deleting objects in any data platform can be catastrophic for a business and take hours or days to recover. Our Snowflake Object Deletion Prevention makes each deletion an explicit user-defined action, which enhances productivity while reducing the risk of catastrophic failure.
DataOps Continuous Execution
In another step towards zero downtime, the release ensures your data pipelines do not fail during maintenance.
“We’re very excited about the DataOps.live Fall Release – as a dynamic data driven organization processing literally trillions of data points, these new capabilities around scalability will allow us to continue to accelerate our initiatives to grow OneWeb to the forefront of our industry,” says Miguel Morgado, Product Owner, Service and Platforms at OneWeb.
These powerful new capabilities enable clients to dramatically decrease the time to value and accelerate release productivity for Data Products and Data Applications. To find out how DataOps.live can help drive success from modern data architectures at your organization and deliver data engineering at scale, read our Product Release Blog, and join us at our upcoming Product Release Webinar on November 9th at 11am EST/4pm GMT and visit https://www.DataOps.live.
About DataOps.live
DataOps.live was built to meet the real-life needs of modern, data-driven companies using Snowflake’s cloud data platform. It removes the need for enterprises to choose between governance and agility, delivering fundamental improvements in both. The platform brings agile DevOps automation (#TrueDataOps) to the Snowflake cloud data platform. DataOps.live is a single platform for 100% of an organization’s DataOps lifecycle needs around Snowflake.
