IT operations analytics scan all the data that has been gathered using different tools and provides resolutions to problems and does root-cause analysis.

But modern machine learning & Deep Learning methods can learn the IT landscape’s behavior and raise proactive alarms when anomalies are deducted. It allows the system to follow, learn and unlearn patterns and can further use resources to avoid application downtime, performance degradations, and capacity bottlenecks.

Artificial Intelligence with IT operations Management

The modern digital systems are largely dependent on multiple sources of technology services. They use a combination of on premise, private, public data centers and cloud resources. IT operations management leverages artificial intelligence to:

  • Provide proactive performance anomalies to stabilize availability of digital services
  • Optimize cost by aligning risk decisions with business needs
  • Provide timely inputs to efficiently manage technologies that drives business
  • Reduce MTTR problems reported by recommending resolutions for the problem

Enrich Enterprise Performance

  • Reactive to Proactive
    Proactively detects different patterns from the environment that helps in improving system efficiency and avoids outages.
  • Dynamic IT infrastructure planning
    In the age of digitalization, the capacity to have flexible and dynamic IT infrastructure is mandatory. Power to foresee & dynamically provision futuristic infrastructure requirement is the biggest boon from artificial intelligence in IT operations.
  • Transform service delivery
    It is critical for Enterprises to maintain reliability and performance of their customer systems as they grow and expand their business. Machine learning capability helps in learning the needs and recommends technology upgrades required in the landscape.
  • Enable BYOD integration
    With BYOD concept being used extensively, the challenge to manage data security is intense. With the help of artificial intelligence, log data from multiple applications, machines, sensors, web sites and mobile devices are processed in real time and breaches are notified to stakeholders.
  • Systematic transaction management
    IT operations follow an application centric infrastructure monitoring model, displaying all applications in a single view. Artificial intelligence helps in recording end-user patterns in real-time, to provide clear visibility into end users behavioral patterns.
  • Resolve problems automatically
    Machine learning techniques are used to understand the root cause for an event and expedites resolution time by using log analytics based on the context of the event. Automated workflows help in automatically resolving high-impact issues.

There is a constant need for enterprises to revive their business models which allows them to adjust their processes to handle multiple situations. Artificial intelligence in IT operations management should play a role to enrich enterprises to make their IT infrastructure highly available, scalable and be prepared for the future demands.