The latest News and Information on AIOps, alerting in complex systems and related technologies.
Artificial Intelligence (AI) is all the rage these days. Everywhere you look, companies are promising to solve your ills by applying AI to whatever problem you’re trying to solve. It doesn’t seem to matter what area you are in; medical, research, education, technology, software or anything else. Someone, somewhere is offering an AI-based tool that will solve all your problems.
In today's business and IT environment, marked by constant change and transformation, if you’re a managed service provider (MSP), you are probably struggling to keep up. You’re faced with the need to modernize your operations, but the speed at which you can do so is constrained by years of accumulated complexity and chaos.
“Make life easier” isn’t a mantra for the lazy—it’s a way to drill down on important automation in the IT Ops room. When Ryan Taylor, VP of solutions engineering at Transposit, talks about his experience and outlook in the IT Ops chair, people tend to listen.
Every product or application needs a release strategy. It’s how you can double check that everything in your deployment is appropriately tested, validated and verified. Having a standardized release strategy in place allows your team to follow a protocol and reduce the number of unknowns they must face in the product life cycle. However, there are a few considerations to make this critical process run smoothly.
Improvements in the performance and accessibility of technology have changed our expectations for how applications should work and, by extension, the way we work. For example, three years ago only 6% of workers were remote. According to the 2021 Upwork "Future Workforce Report," that number is now 22%, and remote workers are expected to reach 28% of the workforce by 2025. As more and more people are let loose from their office tethers, they bring with them a belief that their organization's services and applications should work as they did before. What's more, expectations extend from the workplace to the marketplace.
The amount of data volume and complexity within tech stacks is continuing to increase with no sign of slowing down. As a result, many organizations are facing significant challenges related to tool sprawl and the overwhelming amount of data that needs to be exchanged between all the different systems. The result is this new rapid pace of data which brings a need for faster flow and exchange of information.
