Skip to main content

AIOps takes closed-loop autonomous operations to the next level

AIOps takes closed-loop autonomous operations to the next level

What is needed to reach closed-loop autonomous operations?

The telecom industry has undergone an incredible transformation spurred by rapid advancements in IoT, 5G, autonomous vehicles, and other innovative services. Connected devices now outnumber the world's population and continue to grow, and the 5G era has drastically impacted how communication service providers (CSPs) operate. 5G technology and software have allowed CSPs to boost network efficiency, enhance customer satisfaction, and streamline operations.

Still, new challenges arise with the introduction of various layers, hybrid cloud solutions, network domain stitching, and the increased complexity of end-to-end service operations and assurance. We need technology and processes to guide us forward; the adoption of AI and automation will accelerate CSPs’ efforts to enhance their operations and improve the customer experience, which are crucial objectives in the expanding partner ecosystem. 

Modern service and network automation is a must for OSS/BSS evolution, starting from the business layer of order capturing, customer interactions, and proposal management, to the intelligent orchestration and assurance of the end-to-end service across multiple network domains.

However, achieving true autonomous behavior at every level requires more than basic automation. Current tools for network and service operations are slow, siloed, unresponsive, and unable to predict future outcomes. Attempts to control AI through external engines integrated with existing tools are counterproductive. In the future, AIOps will be an integral component of all tools, enhancing the closed-loop autonomous processes and taking them to the next level.

How Nokia can help

Nokia's Digital Operations software seamlessly integrates AIOps as a crucial component of the solution. Our inventory system utilizes a graph database to store a digital twin of the network, enabling advanced analysis and organization of complex cross-domain data. It empowers root cause and service impact analysis for automation and assurance. Our Assurance solution includes forecasting, anomaly detection, and pattern recognition capabilities. Additionally, our Orchestration solution automates service fulfillment and enables prompt reactions to events, closing the loop efficiently.

We’ve seen significant results from our customers and proven use cases. Some of the more impactful benefits are:

Dynamic Resource Management:

Autonomous operations enhance 5G slicing by dynamically managing network resources. Using advanced algorithms and machine learning, autonomous systems monitor performance, traffic, and application needs. Real-time analysis intelligently allocates resources to different slices based on their requirements, optimizing utilization. This ensures each slice receives the necessary bandwidth, computing power, and latency, improving service quality and network performance. Forecasting techniques have shown up to 3x more efficient network utilization, crucial for new use cases like UE Route Selection Policy (URSP).

Proactive Fault Detection and Remediation:

In 5G slicing, rapid issue detection and resolution are vital. AIOps-powered autonomous operations detect and fix faults proactively. By analyzing data and monitoring performance, autonomous systems identify anomalies, predict faults, and take automated actions, minimizing disruptions and improving reliability. They maintain performance levels for network slices, meeting industry requirements. Closed-loop systems currently resolve 40% of incidents automatically.

Intelligent Slice Operation:

Efficient slice management must consider multiple network slices and ensure smooth operations and resource allocation. Autonomous operations constantly adapt to changing conditions and traffic demands, making intelligent decisions on slice management. AI algorithms optimize network performance, minimize manual intervention, and enable rapid deployment of 5G slicing. This reduces service activation time from days to minutes, even for complex scenarios.

Predictive Analytics and Optimization:

Autonomous operations optimize 5G network slices using predictive analytics. AI algorithms analyze data, predict network behavior, and optimize slice configurations. These systems forecast peak usage and congestion, proactively optimizing resources. This approach ensures network slices handle demands, enhancing user experiences and meeting SLAs. It's crucial for enterprise slices like fixed wireless access and low latency services. Root cause analysis with forecasting models reduces investigation times from hours or days to minutes and seconds.

Final Thoughts

With Digital Operations software, Nokia enhances network efficiency through AIOps-capabilities, including:

  1. Network digital twin model with complex relations graph of all elements within the service across multiple domains and technology areas
  2. Fast root cause and service impact analysis for existing events and forecasting and anomaly detection for future possible outcomes
  3. Autonomous loop algorithm that automates network and service management and makes it self-sufficient.

AI and machine learning are not just buzzwords anymore. They are as essential as smartphones in our daily lives, backed by real-life examples. AIOps has paved the way for the next technological revolution in telecom digital operations and service assurance. 

Oleksandr Dmytriiev

About Oleksandr Dmytriiev

Oleksandr Dmytriiev is a product manager with more than 15 years of experience in the networks and telecom industry. He has excelled in defining the product vision, roadmap, and go-to-market strategy for complex product portfolios in OSS, BSS, Cloud and ML domains in his past roles, and is very passionate about cutting-edge technologies.

Article tags