Artificial Intelligence: Digital transformation has increasingly required a change in positioning and strategy in all business areas. Solutions involving Artificial Intelligence gain special prominence as they bring innovation and optimization to the activities in which they are applied.
This represents a change in the IT field, which is already breaking away from the traditional practices of management tools to implement AIOps (Artificial Intelligence for IT Operations).
These solutions combine automation and machine learning techniques in a Big Data environment to assertively react to IT problems, handle problem detection, error prevention and repair, event evaluation, risk reduction and more.
Therefore, it is possible to have more speed and performance to deal with Big Data since manual monitoring is losing the ability to meet these demands.
For companies that want to be part of this digital transformation and invest in improvements in IT infrastructure management, this is the best alternative. Understand what it is, how AIOps technologies work and why it is essential to invest in them.
What Is AIOps Technology, And How Does It Work?
AIOps is the use of Artificial Intelligence in IT operations. These solutions aim to automate and improve IT operations through Machine Learning (ML) technologies, automation and Data Analytics applied to Big Data.
AIOps platforms receive a large number of data from different sources and act on three main layers: systems, data and tools. Within these layers are performed service management (engagement), performance management (observe) and automation (action) actions.
All this is done through algorithmic analysis of IT data, which checks performance histories and events within the system, log data, network, performance and metrics, as well as incident and ticketing monitoring and support. . This algorithmic analysis process follows the analysis, algorithm and visualization steps.
The analysis involves:
- Interpreting basic information.
- Transforming data into metadata.
- Reducing noise.
- Identifying and predicting problems.
From the pre-existing data, the algorithms present the expected results and the most decisive actions, which optimizes operations management.
In other words, the machine learns how to behave in the face of system performance decisions and behaviors. Visualization tools generate graphs, reports and dashboards that help teams visualize and monitor events, facilitating decision-making and event prevention.
In addition, automation and Machine Learning mechanisms bring more satisfactory results in decision making, work with intelligent data analysis and personalized metrics, act better in risk prevention and are constantly improved as they learn from data behavior.
Why Invest In AIOps?
AIOps emerges with the Digital Transformation to meet the needs of this new context. This is because the number of data companies currently deal with requires an IT environment beyond human capacity, so traditional approaches are not functional in such a dynamic and volatile environment as Big Data.
As this volume of data only tends to increase over time, infrastructure management must keep pace, requiring ever faster tools that keep pace with the modern business, where problems need to be corrected immediately so that the flow of operations and the user experience is not affected.
AIOps technologies, which work as one more facility of cloud computing, are aligned with the demands of the new digital world. Thus, investing in AIOps solutions brings the following benefits to IT infrastructure management.
- Automated routine practices.
- Faster and more accurate problem identification.
- Simplified interactions between teams.
- Faster correction applications.
Therefore, investing in AIOps solutions implies the inclusion of Artificial Intelligence in all IT processes, adding more digital value beyond the technical scope, as it strongly influences customer interaction and fulfillment.
A company that can count on solutions of this level guarantees more prepared and robust IT operations and an organization with the technical and strategic capacity to deal with the complexity of Digital Transformation.