Operations | Monitoring | ITSM | DevOps | Cloud

As soon as the ITOps technician is ready to grab a cup of coffee, a zing comes along as an alert. Cling after zing, the technician has to respond to so many alerts leading to fatigue. The question is why can’t systems be smart enough to predict bugs and fix them before sending an alert to them. And, imagine what happens when these ITOps personnel have to work with a complex and hybrid cloud of IT systems and applications. They will dive into alert fatigue.

Incident management is the process of identifying and resolving problems that occur in IT services. Incident Management is also used as a metric to measure the health of the IT Service Desk. Let’s discuss what incident management is, why it matters to your business, and how you can apply it to your organization.

The onset of ServiceNow has relieved the IT Services workforce. With CloudFabrix RDA added to it, we made it even better. Let’s face it that many IT Service transformation implementations take longer because of a lack of automation around migration and production. The efficiency of ITSM is further compromised due to the absence of data automation and enrichment. ServiceNow with Robotic Data Automation stirs a positive impact on three critical areas of data operations ITSM teams.

Automating incident recovery has inculcated rhythm to systems. But ITOps need more than automation. And, that is the acceleration of automated incident recovery. 79% reported in a survey that adding more IT staff to address IT incident management is not an effective strategy. Incident recovery needs accelerated intelligent automation. The two core outputs when accelerated are better and faster Incident Diagnosis and Resolution.

Modern complex systems are easy to develop and deploy but extremely difficult to observe. Their IT Ops data gets very messy. If you have ever worked with modern Ops teams, you will know this. There are multiple issues with data, from collection to processing to storage to getting proper insights at the right time. I will try to group and simplify them as much as possible and suggest possible solutions to do it right.

For a long time, IT Ops teams have been trying to keep up with the advancements in data analytics and management. In certain organizations, this problem is charged to DataOps teams. .These teams are tasked with managing data growth and complexity as well as keeping pace with new technologies like Artificial Intelligence driven Ops (AIOps).