As CSPs chart their course towards an increasingly automated and autonomous target state, a first foundational step may well be the adoption of AIOps. To that end, it is becoming clear that if data is the foundation, then actionable insight is the enabler for AIOps.
network's reliability and resilience. By addressing these diverse yet interconnected factors, organizations can design a network that not only meets current operational needs but is also prepared
for future scalability, performance, and security challenges. In the whole process, data plays a key role—quality of data, data aggregation, filtration, and correlation are absolutely
essential.
At the core is a Cloud Native framework—such an approach is crucial for maintaining data quality because it enables CSPs to build and deploy scalable, reliable, and efficient data management
systems. By leveraging cloud computing, microservices, and containers, cloud native architectures offer flexibility, agility, and the ability to handle large volumes of data while maintaining
data integrity and accuracy.
Embedding AI in the network components enables contextual awareness, which is essential to have direct access to real-time data and operational context. External tools, by contrast, often lack
this depth of insight, which can lead to less accurate or suboptimal decision making. Context awareness, analytics, and automation are essential for autonomous system decision-making.
What’s next?
CSP will need to select the right technology partner having expertise in cloud, cloud native environment, and data management—one who can support them in their journey towards this autonomous
network see Figure 2, below:
Follow a full-scale approach
As CSPs chart their course towards an increasingly automated and autonomous target state, a first foundational step may well be the adoption of AIOps. To that end, it is becoming clear that if
data is the foundation, then actionable insight is the enabler for AIOps. However, achieving full visibility across all components by aggregating data from various sources is challenging due to
the complexity and diversity of the network environment. Without clean, comprehensive data and real-time system visibility, AI-driven operations cannot deliver actionable insights or automation
at scale. AIOps demands seamless integration of telemetry, logs, metrics, and events from heterogeneous systems. In the journey towards an autonomous, zero-touch network, CSPs need to lay the
foundation of a cloud native network with in-built AIOps, powered by analytics and automation to realize the effective monetization of all network investments.
