Defining the reference architecture for AIOps
In the previous sections, we studied the logical architecture of systems, the components of AIOps, and the technical service architecture. All these building blocks are used to define the architecture for AIOps. In this section, we will look at the reference architecture for AIOps.
First, let's recap the goal of AIOps. In Chapter 7, Understanding the Impact of AI to DevOps, we discussed the Key Performance Indicators (KPIs) for AIOps:
- Mean Time to Detect (MTTD)
- Mean Time to Acknowledge (MTTA)
- Mean Time to Resolve (MTTR)
AIOps adds artificial intelligence to IT operations, using big data analytics and machine learning (ML). The AIOps system collects and aggregates data from various systems and tools, in order to detect issues and anomalies fast, comparing real-time data with historical data that reflect the original desired state of systems. Through ML it learns how to mitigate issues by automated actions...
