Steps to Transition and Transform to Autonomous Network Infrastructure

Transforming to an autonomous network infrastructure (and operation model) is a strategic move that can significantly enhance your business operations. As your business grows, an autonomous network infrastructure can adapt to increased demands without requiring extensive manual intervention.

Enterprises finalising their application and cloud roadmaps expect that their network infrastructure layer is sufficiently modern to automatically detect and resolve issues, minimise downtime and ensure continuous operations, while rapidly reducing cost in maintenance and support. Autonomous network infrastructures can provide enhanced performance, security, and efficiency, making them a crucial part of modern digital infrastructure.

An autonomous network infrastructure is designed to operate with minimal human intervention, leveraging advanced technologies to manage and optimise itself. Components of autonomous network infrastructure include platform technologies such as Artificial Intelligence (AI) and Machine Learning (ML) at the core, combined with network technologies such as Software Defined Networks, Network Function Virtualisation, Intent-Based Networking and Self-Healing Capabilities.

Transitioning existing environments to AI and ML platforms?

AI and ML-based platforms implemented by enterprises enable the network to learn from data, predict potential issues, and make real-time decisions to optimise performance and security. AI-driven security measures can quickly identify and respond to threats, enhancing the overall security posture of the network. This includes automated threat detection, response, and mitigation.

Tying to this are real-time telemetry and data analytics provide continuous monitoring of network performance. This data is crucial for AI and ML algorithms to make informed decisions and ensure the network operates efficiently. These technologies can analyse vast amounts of data to identify patterns and anomalies that may indicate a security breach. Regularly auditing your network and conducting penetration tests can help identify and address potential vulnerabilities before they are exploited by malicious actors or cause network failures.

Fully transforming to autonomous network technologies with platforms

Enterprises rely on their network to connect branches, distribution centres, employees, and more recently, devices and applications as dynamically as possible. This spans multiple technology towers including wide-area networking, carrier management, local area and edge networks, data centre networks and cloud-onramps into public environments such as the untrusted internet and cloud service platforms.

Software-defined networks that decouple the control plane from the data plane, centralising network intelligence. This allows for more flexible and efficient network management, enabling dynamic adjustments to network configurations based on real-time needs. NFV allows network services to be virtualised and deployed dynamically. This increases the agility of the network, enabling it to scale resources up or down based on demand.

Intent-Based Networking (IBN) allows network administrators to define desired outcomes, and the network automatically configures itself to achieve those outcomes. This reduces the complexity of network management and ensures that the network aligns with business objectives. Lastly, Self-Healing Capabilities can detect and resolve issues without human intervention. Self-healing capability minimises downtime and ensures continuous network availability.

The challenges in implementing autonomous networks and platforms?

Implementing autonomous networks comes with several challenges that must be addressed to ensure successful deployment and operation. Here are some of the key challenges.

The initial investment required for transforming to autonomous networks can be substantial. Businesses need to weigh the long-term benefits against the upfront costs and ensure they have the financial resources to support the transition. Especially in developing markets, enterprises face technical debt such as residual costs from previous investments. Exchange rate fluctuation and funding reprioritisation also places pressure. The lack of homogeneity of network environments, whether you have a single or multi- vendor strategy, or across the network towers exaggerates the cost of transformation.

The cost is not just tangible asset transformation. Integrating autonomous network technologies with existing legacy systems can be complex. Ensuring compatibility and seamless operation between old and new systems requires careful planning and execution. Disparate tooling and network management systems including observability tools that are not integrated make it difficult to evolve quickly to autonomous platforms.

Most enterprises face a shortage of skilled personnel proficient in AI, and machine learning proficient in network automation. Training existing staff or hiring new talent with the necessary skills is essential but can be challenging. Finding a partner that designs, supports operations and integrates to enterprise governance policies and structures offsets reprioritising skills in the business from supporting business-facing applications.

While autonomous networks can enhance security, they also introduce new vulnerabilities. Ensuring robust security measures to protect against cyber threats is crucial. This includes safeguarding AI algorithms from being manipulated. Autonomous networks rely heavily on data to function effectively. Managing this data, ensuring its accuracy, and protecting it from breaches are significant challenges. Compliance with data privacy regulations adds another layer of complexity.

Plotting your transition and transformation roadmap to autonomous networking infrastructure

Modernising your network infrastructure infrastructure allows for seamless scalability. This flexibility is crucial for staying competitive in a rapidly changing market. As laid out in this article, if you require quick results without heavy initial capital outlay usually until your strategy matures, we suggest two steps to reaching full autonomous networking infrastructure: platform adoption and then transforming networking technologies.

By automating routine tasks and optimising resource allocation, autonomous networks can significantly reduce operational costs. For example, they can dynamically adjust bandwidth and compute resources based on real-time needs, ensuring you only pay for what you use. Additionally, modern cloud solutions can offer improved performance at lower costs compared to traditional on-premises systems. This is a useful business case drive to move network deployment and support to operational expenditure.

Identifying a partner that is certified across technology vendors, including design, day 1 and 2 operations and is conversant with your enterprise architecture, is critical to offset skills and cost challenges, as this contributes to reduced capital outflow or fixed costs for tooling and engineering. Having technologies such as AI and ML, event-level reporting and pre-integration with telemetry and observability tools will be an advantage to you.

Concerns about security governance and flexibility in data collection protocols is also key in selecting a platform-based network operations partner. Just as important is that your partner can help you before transformation in optimising your network environment, reducing noisy events, identifying vulnerabilities and providing you insight on areas of focus to be modernised. This pre-empts a transformation strategy that is advantaged with partners that can help you transform through global negotiating power and funding models that reduce your cash outflow over your entire investment case.

Conclusion

Modernising your network and cloud environment prepares your business for future technological advancements. With the rise of digital operational technologies and applications, having a robust, flexible, and scalable network infrastructure is essential. This readiness can help you quickly adopt new technologies that drive innovation and efficiency across the rest of your enterprise.