2022 saw a return to normalcy on the Covid front as offices re-opened, people gathered in large groups indoors again and mask mandates waned, even as Covid never really went away. Meanwhile, inflation raged through the summer months before subsiding somewhat later in the year and the Great Resignation gave way to mass layoffs, especially in the tech industry.
OpsRamp has enhanced its hybrid observability capabilities by adding an integrated log management solution to unify log, event and alert data within customers’ monitoring and event management command center. Presenting this log data as part of a unified view of IT performance data and integrating it with remediation capabilities will allow enterprises and service providers to expedite the process of identifying and resolving potential issues before they impact their business operations.
In the last two decades, the software industry has shifted away from on-premises applications to software-as-a-service (SaaS). SaaS now accounts for 70% of the business software market according to BetterCloud, and is worth more than $170bn annually, according to Gartner.
OpsRamp’s Operating System Patch Management module is a flexible, yet powerful capability provided to all OpsRamp platform customers or licensed separately. With our SaaS-based OS Patching solution for Windows and Linux endpoints, you can automate the entire patch management process from identification of missing OS patches to the process of patch installation.
As another autumn fast approaches, any look back at the summer would be incomplete without a review of the latest round of Gartner Hype Cycle reports. The Gartner Hype Cycles are an annual summer ritual, a series of reports published every July (and sometimes August) that track the maturity, adoption and business impact of technology innovations.
In the last half-decade, AIOps and observability have arguably been the hottest two topics in IT operations management. Gartner first mentioned AIOps—Artificial Intelligence for IT Operations—in 2016, defining it as using big data and machine learning to automate IT operations processes, such as event correlation, anomaly detection and causality determination.
As more workloads move to the cloud, more employees work remotely and SaaS application adoption increases, enterprises have had to rethink the way they secure access to the IT services their employees need. The reality for most enterprises today is a multi-vendor, siloed approach that has only compounded their security and IT operations management headaches as they end up using multiple management tools to secure and govern their access to cloud services.
