Digital operational maturity is defined as an organization’s effectiveness at real-time work and ability to focus on performance metrics that improve as the organization becomes more adept at responding to incidents. Based on extensive research and nine years of industry data, in conjunction with a survey of 600+ respondents from across industries, PagerDuty developed a model that identified the four following levels of operational maturity.
A little more than four years ago, Anodot started applying advanced AI/ML and unsupervised learning technologies to simplify monitoring challenges for DevOps teams. Today our company has customers from a variety of verticals and departments harnessing our unique platform to monitor business health, user behavior, product usage, IT ops, machine learning processes and even IoT.
2019 could be the year of artificial intelligence (AI) in IT service management (ITSM). To better understand why this may be the case, let’s take a closer look at AI, how it works and the benefits associated with it.
It’s no secret that we, at OnPage, are passionate about healthcare and the clinical professionals that make the industry go ‘round. It’s through our appetite for this industry, which lead us to publish several, interesting blogs about healthcare and its related topics in 2018. It’s been a successful year and we look forward to 2019, filled with a fresh batch of healthcare posts.
In a world where everything comes down to moments of truth, teams must respond to issues and opportunities in seconds. Rising customer expectations demand real-time response, and effective DevOps and ITOps shouldn’t just be tied to laptops and desks.
When we introduced ‘remote actions’ in 2012, i.e. the execution of IT automation tasks from your smartphone, we aimed at empowering the mobile (IT) workforce of the future. We aimed at relieving IT people from being bound to their desks, notebooks and PCs.
