Proactive, predictive operations management: Enhancing IT operations with AI, GenAI

AIOps provides a unified, intelligent approach to IT operations management.

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I always remember and was fascinated as a kid by the Chappies brand of bubble gum introduced in South Africa in the late 1940s. It is known for its iconic "did you know?" facts printed inside every wrapper. So today’s fact…

We are now 24 years into the 2000s and already past the halfway mark of this year, so time to embrace AI is ticking along. Now, with the option to make use of composite (multiple) AI technologies to improve operations and the option to partner with businesses like Blue Turtle, which have built a strong understanding of AI, businesses can deploy and become effective in their use of AI.

Modern IT departments in any industry are grappling with the challenges of managing complex hybrid environments and multiple sources of data. Adding to this burden are rising user expectations driven by the rapid adoption of AI technologies and the use of multiple solutions within your environment. This makes the implementation of AIOps solutions essential for enhancing agility, preventing issues and meeting evolving demands. AIOps leverages artificial intelligence, machine learning and advanced data analytics to automate and enhance IT operations, providing a proactive, predictive and reliable approach to managing IT infrastructure.

Three key capabilities in today’s operations are to gain observability using composite AI with the inclusion of GenAI and causal AI into the AIOps process. What this delivers is a proactive and predictive approach to processes of a business, regardless of the industry.

Observability, in our terms, refers to the ability to gain proactive and predictive insights into the internal state of a system by examining its outputs while running in real-time. These systems can span from hybrid cloud IT infrastructures used by any IT organisation to edge infrastructure used in mining and manufacturing. It's a key concept in modern business, helping organisations ensure that their systems are functioning as intended and can proactively identify and address any issues that occur. Observability is achieved through the collection, analysis and interpretation of data from various sources within a system.

According to Gartner, composite AI refers to the combined application (or fusion) of different AI techniques to improve the efficiency of learning to broaden the level of knowledge representations. Composite AI broadens AI abstraction mechanisms and, ultimately, provides a platform to solve a wider range of business problems in a more effective manner.

AIOps refers to the use of AI technologies to automate and improve IT operations. It encompasses the use of data, analytics and machine learning to analyse large volumes of IT data in real-time, enabling IT teams to detect anomalies, predict issues and resolve problems faster. Working with customers, specifically around the deployment of BMC’s comprehensive AIOps solutions, we have evidenced that by automating routine tasks and providing deep insights into IT operations, AIOps allows organisations to shift their focus from firefighting to innovation.

Again, if we look at what Gartner says about AIOps, it combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination.

Modern IT environments are complex, often comprising hybrid and multicloud infrastructures, containerised applications, sensor data and microservices. These environments generate vast amounts of data, making it difficult for traditional operations tools to keep up. The main challenges include:

• Data overload – IT teams are inundated with data from various sources, making it difficult to identify meaningful patterns and insights.
• Event noise – High volumes of alerts and notifications can obscure critical issues that need immediate attention.
• Manual processes – Traditional IT operations rely heavily on manual processes for root cause analysis and incident resolution, which are time-consuming and prone to errors.
• Siloed systems – Disparate monitoring tools and systems lead to fragmented data and hinder comprehensive visibility into IT operations.
• Sensor data – No way of correlating sensor data to predict and proactively alert future failures.

AIOps addresses these challenges faced by IT environments by providing a unified, intelligent approach to IT operations management. One of the primary benefits of AIOps is enhanced efficiency and productivity. By automating routine tasks such as anomaly detection, event correlation and root cause analysis, AIOps frees up IT teams to focus on more strategic initiatives. This reduction in manual workload leads to improved productivity and enables faster decision-making.

Another significant advantage is proactive problem resolution. AIOps leverage real-time insights and predictive analytics to help IT teams identify and address potential issues before they can impact business operations. This proactive approach minimises downtime and ensures higher service availability, keeping the business running smoothly.

Improving the customer experience is another key benefit of AIOps. By streamlining IT operations and enhancing service reliability, AIOps ensure that automated incident management and faster resolution times lead to more stable and high-performing services. This results in a better overall experience for customers, who benefit from more reliable and efficient service delivery.

AIOps solutions also offer scalability and flexibility, essential for managing the growing complexity of IT environments. These solutions are designed to integrate seamlessly with existing tools and systems, providing a comprehensive view of the entire IT landscape. This flexibility ensures that organisations can scale their IT operations efficiently as their needs evolve.

But what makes a good AIOps solution? An effective AIOps solution should offer a range of features that support comprehensive IT operations management. One essential feature is intelligent monitoring and analytics. AIOps leverages advanced monitoring and analytics capabilities to provide real-time visibility into IT operations. This includes service-centric monitoring, which focuses on the performance and availability of business services rather than individual components.

Another critical feature is anomaly detection. Machine learning algorithms analyse historical and real-time data to identify anomalies and predict potential issues. This capability helps IT teams detect abnormal behaviour and take corrective action before problems escalate, ensuring smoother and more reliable operations.

Event correlation and noise reduction are also vital components of an AIOps solution. AIOps automatically correlates related events and reduces event noise, making it easier for IT teams to identify the root cause of issues. This significantly reduces the mean time to resolution (MTTR) and enhances overall operational efficiency.

Then there is automated incident management, an aspect of AIOps that streamlines the process of detecting, analysing and resolving incidents. Policy-based automation allows predefined rules to take corrective actions automatically, further enhancing the efficiency and responsiveness of IT operations.

Similarly, open integrations are crucial for a comprehensive AIOps solution. AIOps should support integrations with a wide range of third-party tools and systems to provide a unified view of the IT environment. This ensures comprehensive data collection and analysis across different platforms, allowing for a more holistic approach to IT operations management.

For example, our partner BMC’s comprehensive AIOps solutions apply the power of generative AI and observability to automate IT operations, so you can deliver faster and more reliable experiences for your customers.

Ultimately, if you are considering making use of AIOps, you need to adopt a strategic approach that aligns with the organisation’s overall IT strategy and business goals. The first step in this process is to assess current IT operations. Begin by evaluating your existing IT operations processes, tools and challenges. Identify areas where AIOps can provide the most value, such as improving incident response times or reducing manual workloads.

Once you have a clear understanding of your current operations, the next step is to define objectives and metrics. Set clear goals for your AIOps implementation, such as reducing mean time to resolution (MTTR), improving service availability or enhancing customer satisfaction. Establishing metrics to measure the success of your AIOps initiatives is crucial for tracking progress and demonstrating value.

Choosing the right AIOps solution is also essential. Select an AIOps solution that aligns with your organisation’s needs and integrates seamlessly with your existing IT environment. Look for features such as advanced analytics, anomaly detection and open integrations. BMC’s Helix Operations Management with AIOps is a comprehensive solution that provides these capabilities, offering predictive analytics and intelligent automation to enhance IT operations.

After selecting the appropriate solution, it is important to pilot and scale the implementation. Begin with a pilot project to test the effectiveness of the AIOps solution in a controlled environment. Use the insights gained from the pilot to refine your approach and gradually scale the implementation across the organisation.

But, most importantly, remember that AIOps is not a one-time implementation but an ongoing process of continuous improvement. Regularly review and update your AIOps strategies to adapt to changing IT environments and business needs. By continuously improving your AIOps implementation, you can ensure that your IT operations remain efficient, proactive and aligned with business goals.

What vendors like BMC have identified and are capitalising on is that AIOps empowers IT teams to focus on innovation and deliver superior business outcomes by automating routine tasks, providing real-time insights and proactively addressing issues. As businesses continue to evolve and embrace digital transformation, AIOps will play a critical role in ensuring the agility, resilience and scalability needed to succeed in today’s competitive landscape.