3 years ago

Category: Deployment, Business, Data, Architecture, automation, machine-learning, artificial-intelligence

Most notably, it is delivering a new form of DevOps that recognizes the need to have systems that are intelligent by design and underpinned by comprehensive security (DevSecOps). For many, this will be the crucial next step if DevOps is to shorten the software development lifecycle for all connected intelligent systems, ensuring the continuous delivery of secure high-quality software.By now, most organizations understand DevOps is a substantial discipline that they must adopt – according to Deloitte, organizations adopting DevOps see an 18%-21% reduction in time to market.

Incorporating AI and ML into that DevOps strategy will take things to the next level.Today’s companies are data-driven and being built as digital platforms.

Security is of ever growing importance to each and every organization and, through empowering it with AI and ML processes, it can be enhanced too, simplifying the processing of data to easily identify threats or potential vulnerabilities in the security makeup.

Data is powerful if used correctly, but with so much of it to process and analyze, that can be a challenge.A move toward secure automated processes is the progressive step that many organizations need to consider if they are to realize their digital transformation ambitions.