Artificial Intelligence for IT Operations (AIOps)

Artificial Intelligence for IT Operations, commonly called AIOps is the IT operations analytics, for the next generation. AIOps helps organisations meet their IT related challenges. Some such issues are:

  • Dynamics of the IT Architecture and its complexities


  • Transformation of the businesses in the digital age


  • Siloed IT operations


  • Huge availability of data that are mostly uncorrelated in nature.


  • There is an increasing need for IT organizations to imbibe new technology so as to update their operations processes. The said technology, should be proficient in correlating enormous amounts of data spread across the organisations entire IT domains. A new breed of technology that can detect patterns through machine learning algorithms and present insights in an easy to understand way.

    AIOps, does exactly that!



    AIOps Platforms

    Artificial intelligence for IT operations platforms, simply put as AIOps Platforms are software tools that can replace a lot of IT operations tasks like monitoring and tracking performances, managing automation processes and IT products. It can also upgrade or enhance certain existing IT operations functions.

    AIOps Platforms takes charge of the following IT operations processes:


    Open Data Ingestion

    An AIOps platform collects data of all types from various sources. That may include data on faults, logs, performance alerts, and tickets. The ability to ingest data from the most diverse data sources is critical. It allows for an accurate, real-time view of all the moving parts across hybrid IT environments.Read Blog


    Auto-Discovery

    Given the very dynamic nature of modern IT environments, businesses need an auto-discovery process. That automatically collects data across all infrastructure and application domains – including on-premises, virtualized, and cloud deployments. And it identifies all infrastructure devices, the running applications, and the resulting business transactions. Read Blog


    Correlation

    Then it’s time for the AIOps platform to correlate this data in a contextual form. So it needs to determine the relationships between infrastructure elements (such as the physical and virtual connections at the networking layer), between an application and its infrastructure (for instance, by mapping application flows to the supporting infrastructure), and between the business transactions and the applications. Read Blog


    Visualization

    Once the end-to-end correlation process is completed, they need to be presented in an easy-to-use format. And that’s what visualization is all about. Data is typically visualized in topology maps, application maps, business and operations dashboards, and other formats. Visualization is important because allows IT operations to quickly pinpoint issues and take corrective actions. Read Blog


    Visualization

    Finding the root cause of a problem is key. But it’s even more critical to determine recurring patterns and predict likely future events. AIOps solutions use supervised and unsupervised machine learning to determine patterns of events in a time-series. They also detect anomalies from expected behaviors and thresholds and predict outages and performance issues. Read Blog


    Automation

    Then it’s time for the AIOps platform to correlate this data in a contextual form. So it needs to determine the relationships between infrastructure elements (such as the physical and virtual connections at the networking layer), between an application and its infrastructure (for instance, by mapping application flows to the supporting infrastructure), and between the business transactions and the applications. Read Blog