Any interruption in the IT service is termed an IT incident. An IT incident not only jeopardizes the IT infrastructure but also affects the service availability. Data breaches, login issues, database corruption, and many other issues come under IT incidents. An organization should have a well-planned strategy for finding and eliminating IT incidents. If an organization fails to fix an IT incident on time, it may jeopardise its business continuity. Incident management is responding to IT issues and fixing them quickly. Read on to find out the different stages of effective IT incident management.
It is the first step of incident management for any organization. If an organization cannot detect IT issues, it cannot respond to them. The MTTD (Mean Time to Discover) for finding IT issues should be low for any organisation. MTTD is a metric that defines the time taken to detect IT issues within the organization. It can be reduced only if your IT infrastructure is equipped with robust monitoring systems. An outdated monitoring tool cannot find IT issues in real-time, thus, increasing MTTD.
Since legacy monitoring tools are ineffective in the current scenario, organizations use AI for application monitoring. AI-based monitoring tools can help organizations identify IT incidents in real-time. Once you have identified an IT incident in real-time, you have ample time to fix it before it impacts the service availability. Gone are the days when system administrators could identify IT risks easily as they few. In this complex technological era, the number of software systems used by organizations has increased. Numerous IT incidents can occur in a day and cannot be detected manually by system administrators.
Root Cause Detection
Knowing that an IT incident has occurred within the IT infrastructure is not enough. IT teams also need to know the actual cause of an IT incident. For example, if data silos have occurred in your IT infrastructure, you need to know which software system is not sharing data with others. Many organizations waste a lot of time in determining the cause of an IT incident. When they discover the root cause, much time has been wasted and, service availability is jeopardized. Root cause detection can be enhanced when you have high observability in the software systems.
Legacy monitoring tools do not tell you much about the internal states of software systems. It is why organizations need AI automated root cause analysis solutions to know more about the internal states of software systems. An AI-based monitoring tool offers high observability into software systems by studying their outputs. IT teams can quickly know which software system is causing all the hassles. Incident management becomes easier when IT teams know the exact point of an IT issue. Nowadays, IT teams are using AIOps based analytics platforms for effective root cause analysis. The best AIOps tools and products can study the relationships between data to find the reason for an IT incident.
What to do if multiple IT incidents occur at the same time? Well, you can start by fixing the ones that can seriously deteriorate the service availability. Since there are a greater number of software systems connected to the IT infrastructure, there is a possibility that numerous IT incidents can occur simultaneously. Again, AI data analytics monitoring tools can help organizations with impact analysis.
AI has the power to forecast the impact of an IT incident on the IT infrastructure and service availability. Based on the impact analysis results, you can fix incidents orderly. The software systems in an organization are interconnected to each other in some or another way. An IT incident that may seem small can jeopardize the complete IT infrastructure. It is why impact analysis is needed to find which IT incidents need urgent action and which can be done later.
During impact analysis, redundant IT incidents are also eliminated. Monitoring systems usually raise a ticket whenever an IT issue occurs. Many times, multiple tickets are raised for a similar IT incident. IT teams can get tangled among redundant tickets and jeopardize service availability. With impact analysis, IT teams can spend time on incidents that require urgent attention.
Escalate to the Right IT Team
How do you know which IT team is best suited for fixing an incident? Due to lack of communication, IT teams are not sure about which one of them will fix an IT incident. The Mean Time to Acknowledge (MTTA) increases as IT teams do not know which one of them will act. It is where AI for application monitoring comes into the limelight. An AIOps-based tool will not only find the root cause but also find the IT team responsible for fixing an IT incident. The communication standards among your incident management teams can be enhanced with the use of AIOps.
By using AI for application monitoring, you will know the root cause of an incident and its impact on service availability. You will know about the team responsible for fixing the IT incident. With all the information, fixing an incident become easier. MTTR (Mean Time to Resolve) is decreased drastically with the information provided by AIOps-based platforms. The best part about AI for application monitoring is that it offers actionable insights. Actionable insights can tell you simple ways to fix any IT incident. When you fix IT incidents quickly, the uptime of your software systems will increase. You can ensure high service availability when all your software systems have high uptime.
Incident Management Report
After solving an IT incident, a report is created by IT teams for documentation and backtracking. However, more IT incidents are occurring and, it gets hard to document them all. With AIOps, organizations do not have to worry about incident management reports as AI remembers it all.
In a Nutshell
More and more organizations are relying on AIOps based analytics platforms for effective incident management. The global AIOps industry is growing with an annual growth rate of around 30%. You can also facilitate your IT teams with AIOps for better results. Start using AIOps for effective incident management now!