AIOps: Impact of artificial intelligence on IT operations and batch chain optimization
One of the main concerns in sectors that manage large volumes of data and interactions focuses on reduce process times.
This objective arises from the need for organizations to maximize the availability of services, react quickly to eventualities or unforeseen events, and solve problems in a timely manner.
In this effort, the practice AIOps: Artificial Intelligence for IT Operations (or in English, Artificial Intelligence for IT Operations), allows Automate and improve IT operations management.
The process begins with the historical collection of information, under certain configuration and logic patterns. From there, it performs analysis and obtains results.
In this article we explain What does AIOps implementation entail? in organizations that must manage large data and transaction infrastructures.
We also address the current impact that AI and machine learning have on these processes, and what are the most recommended AIOps implementation strategies. In particular, we will analyze How to optimize the bach window with this emerging technology.
What is AIOps?
AIOps combines analytics with artificial intelligence - specifically Machine Learning - to Improve efficiency across all domains of IT operations: performance analysis, automation and service management (ITSM).
Other AIOps applications lie in analyzing all the data generated by today's complex IT landscape, to:
- discover patterns,
- correlate events,
- predict behaviors or
- facilitate root cause analysis.
For its part, IBM, in its report Grid® Report for AIOps Platforms – Spring 2023, describes AIOps as the use of AI or machine learning to analyze large volumes of data across a variety of systems.
They claim that AIPos platforms speed up problem identification and resolution. This enables increased accuracy of root cause analysis and proactive identification, reduced resolution time, and improved service level agreement (SLA) compliance.
To provide more efficient and proactive IT management, AIOps is crucial, especially for data-intensive and interactive businesses.
Retailers, telcos and financial institutions, where system availability and security are vital, are some of the examples of industries that benefit from the application of artificial intelligence to process improvement.
Furthermore, considering that it allows problems to be detected and resolved before they affect users, Downtime is reduced and business continuity is improved.
In this sense, predictive analysis allows:
- Optimize the use of resources.
- Ensure compliance with regulations.
- Increase operational efficiency.
- Reduce costs.
- Increase customer satisfaction.
- Strengthening confidence in the financial services offered.
How do AIOps platforms work?
To qualify as an AIOps platform, IBM maintains that a product must:
- Leverage AI and/or machine learning to analyze large volumes of data.
- Monitor and analyze data from various types of systems.
- Identify problems proactively and reactively.
- Assist or guide the problem-solving process.
- Integrate with a variety of IT systems.
Current impact of artificial intelligence for IT operations
The Market Guide for AIOps Platforms prepared by Gartner in 2019, anticipated that by 2023 the 40 % of DevOps teams would augment application and infrastructure monitoring tools with AIOps platform capabilities.
He exponential growth that artificial intelligence has had in recent years, confirmed that prediction in fact.
In fact, IT infrastructure complexity will only increase, reaching a point in the next 5 years where The human professional in charge of IT operations will rely on artificial intelligence algorithms integrated into all of its ITOps tools, to maintain SLAs that are in line with your business objectives.
In his report Report on Industry Size & Market Share Analysis – Growth Trends & Forecasts (2024 – 2029)Mordor Intelligence notes that AIOps market size to exceed $27 billion by 2024.
The forecast is to reach $79 billion in 2029, tripling current values, with a compound annual growth rate of 24,01%.
The report highlights that the integration of artificial intelligence into the operational services of all financial institutions improved the capabilities built into service desk systems.
As for the countries that stand out in the AIOps market in each region of the world, the study on AIOps Market of 360 Research Reports, reports that In South America, Brazil, Argentina and Colombia lead the way..
One of the sectors that most uses AIOps solutions today is banking and finance, and it does so with the aim of Optimize batch and online processes.
What are the most recommended AIOps strategies?
A successful AIOps implementation project involves developing strategies that combine Advanced technology, well-defined processes and an organizational culture that values innovation and continuous improvement.
Based on this framework for action, we share some strategies to consider:
1. Use machine learning algorithms to Identify patterns and predict potential failures before they happen.
2. Implement systems that not only detect problems, but can also solve them automatically without human intervention.
3. Process and analyze data in real time to Provide instant insights and enable rapid responses.
4. Implement AI to correlate events from multiple data sources, reducing noise and highlighting critical issues that need attention.
5. Integrate AIOps with automated CI/CD pipelines, to Identify and correct problems in the development and deployment stages.
6. Provide continuous feedback to the development team about system performance and issues in production.
7. Add advanced monitoring tools that provide a complete view of system status and performance.
8. Create Intuitive dashboards and graphics that allow IT teams to visualize the status of infrastructure and applications in a clear and concise manner.
9. Incorporate AI to manage and automate configuration changes, minimizing human errors and ensuring consistency.
10. Predicting the impact of changes in the infrastructure before its implementation.
11. Use predictive models to anticipate capacity needs and optimize resource use.
12. Identify opportunities to reduce operating costs by optimizing the use of cloud infrastructure and resources.
13. Use artificial intelligence to detect anomalies and potential security threats in real time.
14. Implement automated responses to security incidents to mitigate risks quickly.
15. Continually review and adjust AIOps strategies based on new data and learnings.
16. Keep AI models updated with the latest data to ensure accuracy and relevance.
17. Facilitate the Collaboration between development, operations and security teams through the use of common platforms and tools.
18. Promote a culture where Decisions are made based on data and analysis provided by AIOps tools.
Meanwhile, our partner Centreon, focuses on the combination of two main strategies:
The first one, Invest in AI-powered tools, such as those we provide from IT Patagonia, when obsolete platforms are replaced.
This stage includes the IT Infrastructure Monitoring (ITIM), Application Performance Monitoring (APM) and Digital Experience Monitoring (DEM). In addition to the Network Performance Monitoring and Diagnostics (NPMD).
The second strategy is to apply AI to ITIM, APM, NPMD and DEM, as well as IT automation and ITSM. The goal is a domain-agnostic platform that can collect data from all other platforms, correlating across domains.
This second, more ambitious approach complements the first without replacing it, attracting larger organizations that can afford to have a dedicated team, or outsource to a company like IT Patagonia, that provides this service, to create and maintain wide-reaching AIOps platforms.
In any case, the approach should be oriented towards have the best IT monitoring platform, which natively includes its own AIOps capabilities and the right connector to create a more ambitious multi-domain platform, when integrated into a broader IT operations framework, composed of multiple high-level platforms in specific domains.
How to optimize batch window with AIOps?
Maximiliano Casalaspro, Data Center Services Manager IT Patagonia, AIOps contributes to improving batch and online processes, providing the following main benefits:
- Early detection of deviations in the event of cancellations.
- Estimating schedules.
Precisely, the ability of these platforms to overcome several of the inconveniences that large banks and companies present today in their operations, makes AIOps are considered as the future of IT operations management.
In this regard, Maximiliano states that any company that has a scheduler in its corporation, due to the volume of processes in execution, should implement this solution. In this way, it will be able to provide greater visibility and optimization to its processes and chains.
AIOps: What is IT Patagonia’s proposal?
From IT Patagonia We propose a process optimization tool based on artificial intelligence, which allows the implementation of a preventive process for improving batch and online processes.
It provides organizations with predictability, security and control of their critical processes, and allows them to anticipate problems and make informed decisions.
OPTI, our AI optimization product provides:
- Prosecution: including the identification of critical paths, a catalog of processes by consumption, consolidation of errors and cancellations, and dependency analysis.
- Information: automated reports and reports, processing projections, automatic alarms and job monitoring.
- Medium: providing a knowledge base, centralized documentation, shift passing (operators), tape inventory, and recording and control of manual tasks.
Its benefits include:
- A rapid implementation of improvements, in less time, by allowing work on optimizations 48 hours after receiving the corresponding logs. In this way, the client receives the first improvements during the second week of the project.
- Automation: By drastically reducing manual work to identify improvements and changes, times are considerably optimized.
- Automatic alarms: Daily monitoring of processes allows for the rapid identification of variations, errors and cancellations. These alarms are triggered after the logs have been processed and indicate which processes require immediate attention, saving time.
In terms of return on investment, OPTI generates a reduction in times (with a view to a 7×24 scheme), savings in the cost of Scheduler licenses, and a reduction in the time to resolve cancellations.
Conclusion
Preventive detection of anomalies, achieved by using artificial intelligence to automatically incorporate patterns from monitored indicators, allows early warning when anomalous behavior is experienced, and optimizes and provides greater security to process management.
The incorporation of AIOps applies to the Optimization of batch and online processes, in Mainframe and distributed environments, and allows to reduce at least 30% of the critical window in 4 months.
AIOps empowers IT operations teams by providing advanced automation, analytics, and optimization capabilities, and improving efficiency, proactivity, and incident response capabilities.
We invite you to learn about our services and discover How we optimize the back-end chains of Argentina's major banks.
