AI (Artificial Intelligence) and ML (Machine Learning) are the number one strategic enterprise IT investment priority in 2018 (named by 33% of enterprises), taking the top spot from container management (28%), and clearly leaving behind DevOps pipeline automation (13%), according to new Enterprise Management Associates (EMA) research.
At the same time, most enterprises are still struggling to understand the basics of how to successfully evaluate AI and ML solutions, how to put project performance metrics in place, and how to handle the eight key limitations of AI and ML technologies today, says EMA.
Some of the key benefits of artificial intelligence and machine learning identified in the research are:
■ Free up 30% of developer time and up to 50% of IT operator time used to support infrastructure
■ Eliminate operational silos as the root cause of cost, quality, and speed bottlenecks in DevOps
■ Proactively address operational issues and minimize mean time to repair (MTTR)
■ Curb alert flood and receive earlier alerts aligned with business priorities
■ Help the 72% of enterprises with ungoverned Kubernetes clusters to bring these back under corporate control
■ Operate a mostly self-driving hybrid cloud to unlock the 50% of data that cannot go into the public cloud today
■ Improve collaboration between developers, IT, and business
The Latest
APMdigest and leading IT research firm Enterprise Management Associates (EMA) are partnering to bring you the EMA-APMdigest Podcast, a new podcast focused on the latest technologies impacting IT Operations. In Episode 2 - Part 1 Pete Goldin, Editor and Publisher of APMdigest, discusses Network Observability with Shamus McGillicuddy, Vice President of Research, Network Infrastructure and Operations, at EMA ...
CIOs have stepped into the role of digital leader and strategic advisor, according to the 2023 Global CIO Survey from Logicalis ...
Synthetic monitoring is crucial to deploy code with confidence as catching bugs with E2E tests on staging is becoming increasingly difficult. It isn't trivial to provide realistic staging systems, especially because today's apps are intertwined with many third-party APIs ...
Recent EMA field research found that ServiceOps is either an active effort or a formal initiative in 78% of the organizations represented by a global panel of 400+ IT leaders. It is relatively early but gaining momentum across industries and organizations of all sizes globally ...
Managing availability and performance within SAP environments has long been a challenge for IT teams. But as IT environments grow more complex and dynamic, and the speed of innovation in almost every industry continues to accelerate, this situation is becoming a whole lot worse ...
Harnessing the power of network-derived intelligence and insights is critical in detecting today's increasingly sophisticated security threats across hybrid and multi-cloud infrastructure, according to a new research study from IDC ...
Recent research suggests that many organizations are paying for more software than they need. If organizations are looking to reduce IT spend, leaders should take a closer look at the tools being offered to employees, as not all software is essential ...
Organizations are challenged by tool sprawl and data source overload, according to the Grafana Labs Observability Survey 2023, with 52% of respondents reporting that their companies use 6 or more observability tools, including 11% that use 16 or more.
An array of tools purport to maintain availability — the trick is sorting through the noise to find the right one. Let us discuss why availability is so important and then unpack the ROI of deploying Artificial Intelligence for IT Operations (AIOps) during an economic downturn ...
Development teams so often find themselves rushing to get a release out on time. When it comes time for testing, the software works fine in the lab. But, when it's released, customers report a bunch of bugs. How does this happen? Why weren't the flaws found in QA? ...
