Implementation of automation and artificial intelligence
Posted: Wed Feb 05, 2025 10:59 am
Watt adds that there is no magic number, so the size should be determined with an eye to creating a team that can work as independently and quickly as possible. “The key is that the team needs to be able to work autonomously,” he explains. “If they have to coordinate with different stakeholders to get information, you’ve already lost the battle.”
Watt says it’s important for response teams to have a clear understanding of business priorities and what should guide decision-making. For example, if there’s a major outage, it’s more important that accounting systems or customer support systems are up and running first. “Understanding those priorities and your business flows is really important in a large-scale response,” he says.
For Gordon, problem prevention is an ongoing effort that requires investment. “We’re constantly improving in terms of what we can see, what issues we can detect, and how we can automate problem resolution for all of our customers,” he says.
Watt explains that automation used to belgium mobile database more of an “if this then that” (IFTTT) model, where a company would have hard-coded criteria for an error condition that would trigger an automated action—low disk space, low memory, or a service that had stopped responding, for example. “In the future, autonomous tools will be able to abstract information from systems and help diagnose and troubleshoot much more complex system interactions that might otherwise require an engineer,” he says.
In addition to automation, Ashmore predicts that the use of AI to predict failures will expand and become ubiquitous in IT. “AI will move beyond simple machine learning-based prediction algorithms and become self-learning, allowing us to predict failures in situations that have yet to be seen,” he says.
Ashmore explains that systems will also use AI to provide self-healing capabilities through automated recovery, troubleshooting, scaling, and intelligent workload distribution. “AI will be used for decision support, automated incident summary generation, incident response, and root cause analysis,” he explains.
Watt says it’s important for response teams to have a clear understanding of business priorities and what should guide decision-making. For example, if there’s a major outage, it’s more important that accounting systems or customer support systems are up and running first. “Understanding those priorities and your business flows is really important in a large-scale response,” he says.
For Gordon, problem prevention is an ongoing effort that requires investment. “We’re constantly improving in terms of what we can see, what issues we can detect, and how we can automate problem resolution for all of our customers,” he says.
Watt explains that automation used to belgium mobile database more of an “if this then that” (IFTTT) model, where a company would have hard-coded criteria for an error condition that would trigger an automated action—low disk space, low memory, or a service that had stopped responding, for example. “In the future, autonomous tools will be able to abstract information from systems and help diagnose and troubleshoot much more complex system interactions that might otherwise require an engineer,” he says.
In addition to automation, Ashmore predicts that the use of AI to predict failures will expand and become ubiquitous in IT. “AI will move beyond simple machine learning-based prediction algorithms and become self-learning, allowing us to predict failures in situations that have yet to be seen,” he says.
Ashmore explains that systems will also use AI to provide self-healing capabilities through automated recovery, troubleshooting, scaling, and intelligent workload distribution. “AI will be used for decision support, automated incident summary generation, incident response, and root cause analysis,” he explains.