IT operations deal with a huge volume of data every day which puts tremendous pressure on the IT workforce. In addition, this also results in loss of optimization and real-time monitoring and resolution of issues. Artificial Intelligence in IT Operations or AIOps, efficiently handles these basic tasks to reduce the burden on IT operations and automates basic functions like monitoring, service desk, technical support amongst other solutions.
What is AIOps and how it can help your company?
AIOps works on three aspects: monitoring, engaging, and acting on big data. AIOps basically includes the application of machine learning and big data in IT operations. AIOps not just benefits IT and cloud-based companies but also see implementation in healthcare, finance, insurance, and other sectors.
Some use cases of AIOps include:
- Automation tools for service desk
- Realtime user monitoring tools
- Application performance monitoring
- Ingestion of data to recognize events and remediation
AIOps monitors data across IT systems, devices, and processes and helps companies control the ace at the following:
- Anomaly Detection
- Realtime Notification
- Automated Event Management
- Dependency Mapping
This results in reduced costs for companies and less reliance on the human workforce. It also helps in scaling down errors and increasing the productivity of the workforce by organizing shifts for a smooth experience. It offers service reliability as the tool can be operated 24/7.
For example, AIOps in healthcare can easily replace the helpdesk and takeover booking appointments, generating triggers for issues, flagging important and emergency requests along with assigning them to the relevant teams. The prediction and remediation of issues can be a game-changer in the healthcare industry.
How to choose the right AIOps tool for your business
While the application of AIOps is very beneficial for a company, the implementation of the right tool is critical. So how do you identify the best AIOps solution for your business? All AIOps tools do not fit every business. Choosing the right tool depends on a match between your company’s IT goals and the features offered by the AIOps tool. The suitability of the two will determine whether an AIOps product works for your company.
Here are some factors to consider while picking an AIOps tool
- Complexity – The first factor is the level of complexity involved in your business. Higher complex environments require expensive AIOps to be deployed with better features. Understand what kind of features and functions are helpful for your business before implementing an AIOPs tool for your business. AIOps do not reduce complexity but give the company a tool to deal with large sets of data and process it in real-time for better decision making.
- Monitoring – The monitoring features of an AIOps tool are critical while selecting the right tool. However, it is not limited to only monitoring. A tool cannot entirely be considered AIOps if it offers only storage and retrieval of data.
- Connectivity – Connectivity to systems varies for every company and finding an AIOPs tool that offers connectivity to systems like Kubernetes, SAP and others is important. It isn’t easy to deploy such connectivity on your own. It is easy to determine what kind of connectivity your business needs. The factors involved include connectivity to a system and the ability to gather data while controlling that system.
- Return on investment – To measure returns on AIOps, you need historical data and monitor the progress. Typically, the ROI can be measured within 6 months of deployment. The result may not yield 100% results, but it definitely offers increased efficiency. One must also take into consideration the time taken to resolve issues using the human workforce to measure the value of your investment.
- Observability – Through observability, companies can monitor internal systems and use predictive analytics models to find anomalies and detect issues. After detection, the companies can then administer resolution and remediation of such issues. It also helps companies in being proactive in finding solutions for issues and predicting and detecting abnormal behaviors.
- Root-cause analysis – To know the origin of a failure or issue is one of the main features that help businesses trace and remedy an incident or event. Root-cause analysis helps businesses understand the primary cause even in complex and interdependent systems. AIOps tools that provide this feature, help companies that have multi-dependent and interwoven systems.
- Automation features – It is not enough for many businesses to ingest, correlate and understand data, events, and anomalies. The deployment of automated remedies not just saves time and effort but also reduces the costs involved. Automation features replace manual labor and save on human resource costs. It also helps in 24/7 monitoring and resolution which is beneficial to both the company and customers.
Choosing the right AIOps tools varies from company to company as their IT operating systems and requirements are different. However, understanding what your IT infrastructure needs, charting your AIOps transformation journey, and aligning it with your business goals can help you pick the right tool for your business.