According to Gartner’s 2018 Marketing Guide for AIOps, “ AIOps platforms combine big data and machine learning functionality to support all primary IT operations functions through the scalable ingestion and analysis of the ever-increasing volume, variety and velocity of data generated by IT”. AIOps will also play a crucial role in helping enterprises manage all of the new software driven services that are coming from their Digitalization and Digital Transformation initiatives. This leads to AIOps playing a role in the following areas:
- Application Performance Management (APM) – APM tools have streams of metrics about the performance of the microservices, transactions, and applications that they monitor that measure the performance (response time), throughput (amount of work done per unit of time), and error rate of these microservices, transactions and applications. APM vendors are incorporating AIOps into their products in order for the AI to learn what is the normal state of each metric for each monitoring object, and then to automate the process of detecting anomalies in these metrics. Their job is to then automate to the greatest extent possible the process of determining where in the monitored code the cause of the problem lies.
- Infrastructure Monitoring or IT Operations Management – With the death of the ITOM suites from IBM, BMC, HP and CA, the emergence of open source tools for infrastructure monitoring, the breakup of infrastructure monitoring into many point tools, and the emergence of virtualization (VMware) and cloud platforms (Amazon AWS, Microsoft Azure, and the Google Cloud Platform), managing the availability and performance of the software and hardware infrastructure has become significantly more difficult and complicated. AIOps is expected to help these tools cope with the deluge of metrics that come from the hardware and software infrastructure layer and help operators of the environment automatically find anomalies and prioritize them.
- Event Management – Event Management refers to software that consumes all of the events and alarms in the environment, deduplicates them, prioritizes them and then facilitates the resolution of the event by the appropriate teams. Legacy event management systems like IBM NetCool were rule based and fell into disfavor because in a rapidly changing environment, it was impossible to keep the rules up to date. Modern Event Management systems use AIOps to automate the process of sorting and prioritizing the events.
- Digitalization and Digital Transformation – Digitization and Digital Transformation mean that many new software based business services are being put in production, and that each of them are now being evolved (changed) more frequently than legacy online applications. These new applications tend to be built around microservice based architectures which means that there are many more things to monitor. The rate of change in these new microservices means that they must be monitored more frequently. The combination of the explosion in the number of things to be monitored with the increased frequency creates a real time big data problem that AIOps is uniquely positioned to handle.
AIOps Platforms – In addition to AIOps being infused into every existing category of monitoring and management solution, a new category of monitoring and management solution will emerge – the AIOps platform. The AIOps platform will consume log, metrics, events, alarms and relationships from all of the existing platforms and tools and then apply the benefits of AIOps across this consolidated and related set of data.