- Top 6 Things AIOps can Do for your IT Performance
- What are AIOps?
- Top 6 Things AIOps can do for your IT Performance
- 1. Resource Allocation and Utilization
- 2. Real-time Notification and Quick Remediation
- 3. Automated Event and Incident Management
- 4. Dependency Mapping
- 5. Root-cause Analysis
- Manage IoT
With technological advancement and reliance on IT-centric infrastructure, it is essential to analyze lots of data daily. This process becomes challenging and often overwhelming for an enterprise. To ensure the IT performance of your business is on par with the industry, Artificial Intelligence for IT operations (AIOps) can help structure and monitor large scores of data at a faster pace.
What are AIOps?
It is the application of artificial intelligence, machine learning, and data science to monitor, automate and analyze data generated by IT in an organization. It replaces the traditional IT service management functions and improves the efficiency and performance of IT in your business.
AIOps eliminates the necessity of hiring more IT experts to monitor, manage and analyze the ever-evolving complexities in IT operations. AIOps are faster, efficient, error-free, and reliable in providing solutions to issues and challenges involved in IT.
Top 6 Things AIOps can do for your IT Performance
By moving to AIOps you save a lot of time and money involved in monitoring and analyzing using the traditional methods. You can also eliminate the risk of faulty data or outdated reports by opting for AIOps. Here are six reasons to choose AIOps and how they can enhance your IT performance.
1. Resource Allocation and Utilization
AIOps make it easy for an enterprise to plan its resources. Real-time analytics provides data on the infrastructure necessary for a seamless experience be it the bandwidth, servers, memory, and more details.
AI-based analytics also helps an enterprise plan out the capacity required for their IT teams and reduce operational costs. With AI-driven analytics, the enterprise knows the number of people required to address and resolve events and incidents. It can also plan the work shifts and allocate resources based on the number of incidents during any given time.
2. Real-time Notification and Quick Remediation
Real-time analytics has made it easy to make quick business decisions. With AIOps, businesses can create triggers for incidents and can also narrow down business-critical notifications.
According to a study, about 40% of businesses deal with over a million events daily. Assessing priority events becomes an issue in such cases. AIOps help businesses prioritize and effect quick remedies for anomalies. The priority incidents can then be assigned to the IT team to resolve on priority.
3. Automated Event and Incident Management
Using data collected by AIOps, both historical and real-time, businesses can plan for different events and incidents. Thus, offer automated remedies for such incidences.
Traditionally, detection and resolution of such events took a long time and required larger incident management teams. It also meant that the data collected would not be real-time.
Using AI-based automation reduces the workload and ensures that an enterprise is equipped to handle current incidents and planned events. It also requires less manpower to deal with such incidents saving a business from hiring costs.
4. Dependency Mapping
AIOps help understand the dependencies across various domains like systems, services, and applications. Operators can monitor and collect data to mark the dependencies which are even hidden due to the complexities involved.
AIOps even analyze interdependencies that might be missed unless there is thorough monitoring of data. It helps enterprises in the process of configuration management, cross-domain management, and change management.
Businesses can collect real-time data to map the dependencies and create a database to use in change management decisions like when, how, and where to affect system changes.
5. Root-cause Analysis
For improved IT efficiency and performance, understanding the root cause of anomalies and correlating them with incidents is important. Early detection will help affect quicker remedies.
AIOps let IT teams in a business have visibility on anomalies and their relation to abnormal incidents. Thus, they can respond quickly with efficient resolutions for a smooth experience.
The root-cause analysis also helps in improving the domain and ensuring that the business runs efficiently with less exposure to unknown anomalies. Businesses are equipped to investigate and remedy the issue with better diagnoses.
With many Internet of Things devices used widely, the necessity to manage data and the device complexity is of utmost importance. AIOps sees a wide application in this field and help manage several devices at the same time. The sheer volume of devices can make it overwhelming to manage IT operations.
IoT devices have several variables in play and operators require AIOps to manage them with ease. Machine learning helps leverage IoT and monitor, manage and run this complex system.
AIOps ensure that the IT performance thrives with consistent efficiency. It not just helps monitor large data in real-time but also detects issues, analyzes correlation, and ensures quick resolutions. Automated resolutions and management can eliminate downtime and save time and money for any business.
In a nutshell, AIOps aid in the consolidation of data from various IT streams and ensures you receive the highest benefit out of it. Whether it results in automation, resolving incidents at a quick pace, or finding anomalies and making data-driven decisions, AIOps help an organization while ensuring the IT performance is efficient.