What:

  • DevOps-style continuous delivery is based on multi-disciplinary teams that seamlessly work together; it also builds on highly automated “tool trains” often based on open source technology that cover the entire applications lifecycle in the blink of an eye
  • Systems that are purposely architected on the principles of speed, safety, and scalability are stable and yet can accommodate rapid, iterative change
  • Automation can be extended to monitoring the actual business performance of the application, applying Artificial Intelligence to detect and correct inefficiency and anomalies without human intervention

Use:

  • An industrial manufacturer increased its IT process efficiency by over 30% by implementing end-to-end process automation, also covering data integration and the verification process
  • A European bank drastically moved to DevOps-style, highly automated software delivery, changing its image of error-plagued laggard to innovation leader
  • A large stock exchange replaced its incoherent set of application management tools with an end-to-end, automated suite; it enabled them to fluently migrate their application landscape to the public cloud without the danger of failing performance and poor quality results

Impact:

  • Rapid delivery of potentially disruptive solutions to the market, starting from Minimum Viable Products that can quickly and iteratively be extended and improved
  • Lower cost of software development and maintenance, combined with higher software quality
  • Optimization of application performance and opportunities to proactively monitor and improve the business impact of software

Tech: