Digital.ai Unveils the Latest Version of AI-Enhanced DevOps Product
Digital.ai recently launched the latest version of an AI-enhanced DevOps product
The latest version of Digital.ai’s AI-powered DevOps product platform, Corbett, was introduced to help companies build applications with improved user experiences while increasing the efficiency of software development teams.
According to the company, Corbett has enhanced intelligence capabilities that allow teams and organizations, not just individuals, to better harness the power of AI to produce better software. Read more about how Digital.ai introduces the latest version of the AI-enhanced DevOps product.
From development to production, Digital.ai now centralizes and integrates data from more sources, including AI-enhanced DevOps products and third-party software tools, so teams can avoid siled reporting and analysis and harness the power of AI to make predictions about potential to meet results based on past performance.
New people-based dashboards can be deployed to assess historical data for each step of application development and deployment while displaying key performance indicators aimed at team and process efficiency and risk mitigation. The new enhancements build on existing predictive intelligence capabilities that use machine learning to help organizations evaluate options, manage tradeoffs, and make more predictable decisions.
Corbett’s release, said Derek Holt, CEO of Digital.ai, “underscores our commitment to delivering an open DevOps platform built for the enterprise and building custom solutions that support the complexity and scale of the world’s largest companies .
“With the Corbett release, we are making another significant advance as we bring fully updated versions of our industry-leading products to market, and significantly expand the use of data, machine learning and artificial intelligence in software development and delivery. We strive to use artificial intelligence to create value for teams, organizations and individuals as the pace of AI-powered innovation accelerates.
Key improvements include the following:
More trusted and quality applications should be delivered.
Better Identification of Jailbreak Workarounds: Teams can now instantly identify the latest workarounds, allowing organizations to frustrate more attackers by preventing more jailbreaks.
Test manager: Organizations can save time by avoiding the need to recreate tests by using a new central database of tests shared by all project stakeholders, which also improves test management and communication.
Advanced protection methods: Organizations can increase the speed of client protection by 20x. While this acceleration still delivers a secure application, it allows for more iterations to optimize performance.
Increase intelligence by leveraging people- and team-based insights.
Dashboards for Scrum Masters and DevOps Managers: Teams can access development progress across releases and analyze it using persona-based analytics based on previous comparisons, which also allows companies to prioritize features, reduce development times, and streamline deliveries.
Intelligence from Platform Engineers and Release Managers Now organizations can reduce risk by better understanding the root causes of release failures by examining release dependencies and success trends.
Forecast by portfolio teams: A new interactive feature helps organizations better plan their work by calculating team capacity over time using available capacity and what-if scenarios.
Integrate security from the beginning of the development process.
Integrate security checks into release pipelines for better governance. Leveraging an up-to-date connection with OPA, organizations can automatically verify that a tiered list of protections has been successfully applied to a mobile application.
With self-service cloud-native app onboarding, teams can now register and deploy cloud-native apps faster while complying with governance rules in multi-cloud environments.
With the help of a new open SDK, organizations can now harness the power of Kubernetes to easily build integrations with their preferred language, such as Python or Go. This increases productivity and scale.