Why IT Operations Teams Must Embrace AIOps

The complexity of hybrid IT environments (on-premises/cloud) is continuously and rapidly increasing, placing ever greater demands on performance, stability, availability, and security. The associated tasks and challenges are becoming almost unmanageable for IT (especially IT operations teams) given the limited human resources available, particularly amid ongoing skills shortages. This is exactly where AIOps comes into play.

What is AIOps?

AIOps stands for AI-driven automation of IT operations. Its main goal is to improve the performance and availability of IT services and applications. Additionally, it aims to automate at least certain areas of IT operations and related processes. Artificial intelligence technologies play a key role, enabling the detection of issues and impending outages before they happen (predictive analysis).

Predictive AI is a form of machine learning that uses advanced algorithms to analyze large datasets in order to uncover hidden patterns and relationships between variables. In data analysis, predictive AI trains ML models to learn from historical data and make forecasts about future events, scenarios, or outcomes based on those patterns.

By analyzing these patterns and trends, predictive analytics helps detect potential problems early and take action to proactively avoid them.

When predictive AI technologies are combined with a data lakehouse, they can deliver even greater value; namely, prescriptive insights based on contextual data, from the IT infrastructure level to the level of digital user experience.

Generative AI refers to a form of artificial intelligence capable of generating new content based on existing information and user input.

AIOps in Practice

More and more companies are using AIOps. For example, the BT Group (British Telecom) leverages AIOps technologies to optimize the customer experience of its 30 million residential customers and over one million business clients, while also staying competitive.

BT Group’s application monitoring now covers several hundred applications, representing 80% of all incident-generating applications. To address these, the IT operations team has developed 64 scenarios that enable the automatic resolution of incidents. Additionally, monitoring and service management platforms are directly integrated with the continuous integration/continuous development (CI/CD) platform. This ensures that the development team is immediately informed when operational issues arise.

Result: Thanks to AIOps, BT Group was able to reduce Mean Time to Remediation (MTTR) from nearly two hours to just 85 seconds.

Dynatrace Davis AI and Davis CoPilot: Hypermodal AI for Higher Productivity and Faster Troubleshooting

With Davis AI, Dynatrace offers a combination of predictive, causal, and generative AI.

Causal AI analyzes observability and security data in the context of topology information. It groups anomalies, identifies their root causes, and automatically assigns priorities – either ad hoc or based on business impact. Dynatrace has been using causal AI in its monitoring solutions for over a decade.

Predictive AI delivers continuous forecasts and anomaly predictions based on multidimensional baseline data, application traffic, and service utilization.

Based on these results, Davis CoPilot generates the corresponding generative AI-powered queries, notebooks, and dashboards to simplify analysis. It also provides recommendations for improving or automating workflows.

For example, Davis AI automatically detects issues that may affect the customer experience and uses topology, transaction, and code-level data to conduct root cause analysis. Based on this analysis, Davis CoPilot independently suggests corrective actions.

Building on these suggestions, Davis AI and the AutomationEngine allow IT operations teams to use a no-code/low-code editor to create workflows that can be triggered on a schedule or by specific events.

This means the entire process, from issue detection to root cause analysis to resolution, can be fully automated.

If you’re interested in learning more about AIOps in general or Dynatrace Davis AI in particular, please contact your amasol representative.