Oracle is Using AI for DevOps in Platform Push
Nearly a decade on from coining the term that describes the union of software development and enterprise operations, DevOps has increased the speed with which companies roll out software applications.
The quickened pace has in turn, pushed the teams of programmers distributed throughout the enterprise – as well as the prime target for vendors seeking to capitalize on the shift – to develop more agile ways of working.
To help programmers become more productive, and in a bid to lure the companies that employ them to its palette of cloud services, Oracle is building artificial intelligence into its core database software, and into the applications development and management platforms that companies use to access it.
The enhancements help teams by automating processes across the DevOps cycle, from the collection and collation of increasingly dense and diverse datasets to the testing and monitoring that are the hallmarks of continuous application development.
Autonomous Cloud Eases Integration
Last month, the ERP giant augmented its portfolio with AI to automate the tuning, backing up, patching and upgrading of applications that are built on those platforms.
Offered as a subscription service, Oracle platforms for mobile, data integration and API design and management feature AI-enabled machine learning capabilities to continually monitor and refine tasks based on the information these applications process.
Customers also can onboard the Oracle-managed platforms behind their systems’ firewalls under the California-based company’s Cloud at Customer services model. They permit voice interaction with self-learning chatbots and oversee the provisioning of computer processing resources based on utilization histories.
The enhancements build on the Autonomous Database 18c introduced in 2017 as part of the ongoing, year-long roll-out of enhancements to the platforms that overlay it.
AI Cost Reduction
Launched in October 2017 at the Oracle OpenWorld convention in San Francisco, the 18c can operate, scale and repair itself based on user parameters, driving down the costs that arise from human moderation.
Human intervention includes both errors made and the resources used to track them down and rectify the results. In the 18c, machine-learning algorithms mine data for errors and match them with known causes and solutions, automatically updating those libraries as they go.
Taken together, the offerings facilitate what Oracle envisions as an ‘autonomous enterprise’ – one in which AI and the machine learning it enables initiate automation, rather than simply executing processes automatically in response to commands or sensory data.
At February’s Oracle CloudWorld expo in New York City, the company said it would extend these capabilities across its range of platforms. In addition to allowing DevOps teams to move their attention away from repetitive tasks, the enhancements reduce risk by closing the enterprise loop and improve availability, thanks to continuous monitoring and regular upgrades.
Chatbots at Play
A proving of sorts took place in May, when Oracle technologies provided fans at the Madrid Open tennis tournament with a chatbot-enhanced experience they could access using their smartphones.
The June release included a dedicated platform for developers replete with testing and continuous integration of programs built by agile methodologies like DevOps. It also enables teams to create automated interfaces for virtual machines housed in container environments.
The platform works with a range of development frameworks that will grow in number with the arrival later this year of enhanced security features and a blockchain interface.
As the rolling release schedule indicates, these are heady times for the vendors that target DevOps, not just as a means for deeper penetration into enterprise IT. Amid the Oracle rush, vendors large and small have made enhancements to their respective lines that employ AI to assist distributed teams of developers.
The enhancements are no doubt for the best: the arrival of 5G communications technology in 2020 will increase data flows, presenting a significant challenge for DevOps. Thanks to the wider frequency spectrum the standard embraces, the number of connected devices is expected to mushroom.
However, only Oracle has taken automation with AI, including of DevOps processes, to this level of corporate warfare.
