Software development has transformed dramatically in the last decade. The aspirational goal of this transformation is a state of continuous integration and continuous delivery (CI/CD) with short, rapid build/test cycles to quickly deliver quality software to the production environment. As a result, developers are releasing software more often and in smaller batches.
Fast, automated software testing is a key CI/CD tactic. The sooner problems are detected and corrected, the faster they can be fixed and the build promoted to the next stage of the pipeline.
This means that software must be tested at each stage of the development process. And software must be tested in environments that are as close as possible to the production environment.
To enable this transformation developers have created software pipelines automating the provisioning and configuration of infrastructure and deployment of code. Automated software environments can now be built and deployed in minutes. New technologies have made it possible to provision computing, storage, and networking infrastructure in hours or even minutes. But an important element is often missing — quality data.
Percent of Enterprises Adopting Modern Software Methodologies
The provisioning of production data to development teams is slowed by organizational and technical challenges. It can take days or even weeks to request, approve, extract, transform and deliver production data for developers and testers because of the unique data requirements of software development.
Data delivery must keep pace with faster production cycles. Data environments for development and testing must be as close as possible to the production environments in which the code will run. Data is needed in its original form, not extracted or transformed — except as required for risk management. At the same time, data must be masked to protect security and privacy, while retaining realism and referential integrity.
Developers and operations teams must collaborate on workflows and data delivery. Developers need to work with data in all the contexts and platforms of the modern software development life cycle — multiple clouds, data sources, regulations, and more. Developers need to manage data like code, through familiar semantics and workflows.
As a result, data is both a bottleneck in the software development life cycle and an impediment to software quality.
DataOps is the answer to the rising complexity of data management for software development.
DataOps is a set of practices and technologies designed to break down barriers between data owners and data users. DataOps supports data users through the continuous delivery of data and through self-service data management — while maintaining control, security, and privacy.
Integrating flexibly with a variety of platforms, cloud services, and databases and delivering production-quality data to developers, a DataOps platform can simplify and accelerate the delivery of data to the users. It can provision data to development environments quickly — a task that normally can take days or weeks to fulfill through IT ticketing mechanisms.
By integrating masking, a DataOps platform can ensure that data users receive only the data they need to do their jobs — while protecting the security and privacy of suppliers and customers.
A modern DataOps platform can keep developers’ data environments in sync with production data sources. At the same time, individual developers retain control of their copies of production-quality data, which they can modify or restore as needed.
DataOps for App Dev makes data management an agile part of the development process for the first time.
Effective DevOps teams need self-service access to data that can be driven by APIs and supports diverse data sources that may be located on-premises or in the cloud.
How Can DataOps for App Dev improve your Development Speed and Quality?
To find out more about how DataOps for App Dev can solve the data problems in the current application development toolchain, download our white paper, Are You DevOps Complete?