Seven Key Capabilities of AIOps
First, data collection
Look for systems that work perfectly with other solutions. In essence, an enterprise's AIOps solution must be able to collect information from multiple sources, including physical infrastructure components such as services and applications and virtual entities. During deployment, an enterprise's AIOps solution must also be able to interface with existing monitoring tools as well as emerging technologies.
Second, data aggregation
Focus on features that help facilitate cross-domain collaboration. First, an enterprise's AIOps solution needs to be able to aggregate data from IT Infrastructure Monitoring (ITIM), Network Performance Monitoring and Diagnostics (NPMD), Digital Experience Monitoring (DEM), and Application Performance Monitoring (APM).
Third, data enrichment
Aggregation is the first step in enabling data usage, but to gain real value, our AIOps also need to have the ability to enrich the data collected. AIOps needs to provide a retrospective view through historical data, such as logs and events, and use metadata and tags to enrich the search content in the index.
By overlaying data points with timestamps, we can enrich real-time data such as performance and telemetry information to generate time-series information that is meaningful. In subsequent use of this information, companies can also add appropriate tags to create key-value pairs to unlock the full potential of the data.
Fourth, Analytical Insights
Insights are the core value of AIOps tools. Clearly, the most basic correlation and statistical analysis capabilities alone are not sufficient to allow us to identify complex root causes. Pattern discovery and anomaly detection are key components in a good AIOps system, and can also provide an important enabling basis for driving specification based on insights. In addition to infrastructure operational insights, our AIOps system should analyze the specific impact of infrastructure issues on the business. The resulting Service Level Agreement (SLA) management will help businesses gain tremendous convenience and value when interacting with non-technical stakeholders.
Automation can bring extremely high efficiency and effectiveness to the IT operation management system. Therefore, it is best for enterprise AIOps tools to quickly generate and deploy workflows that automate functions. Specifically, the AIOps system should provide options such as automated library maintenance functions and rapid workflow sharing across operational flows. Excellent automation capabilities can not only improve operational agility, but also significantly reduce unexpected errors and greatly enhance service availability.
Sixth, ease of use
Some AIOps platforms provide a cloud-based management layer, which can help IT teams solve the problems of multiple customers at multiple sites simultaneously in a secure, distributed manner, thereby improving management efficiency. By monitoring data pipelines, AIOps platforms can help other tools easily access the collected information, greatly facilitating collaboration across teams.
Seventh, flexible deployment
In terms of service assurance, different enterprises always have different actual situations and specific needs. Therefore, when choosing an AIOps platform, whether self-hosting, remote management, or platform-as-a-service, the AIOps deployment model must be able to meet the unique business and operational needs of the enterprise.
According to Gartner, by February 2023, 30% of large enterprises will use AIOps platforms. AIOps use cases have proven that existing technologies are fully capable of enabling truly proactive IT operations management functions. The excellent approach it provides will help us maintain a good and proven approach to managing complexity in the face of an evolving infrastructure.
Businesses need to be careful when choosing an AIOps tool. Only excellent AIOps tools that meet the above seven basic requirements can consolidate business strategy results and bring solid and reliable IT operations capabilities.