Autonomous network infrastructure: how to make your network smarter

Can your network run itself? Not entirely … yet. But rapid advances in AI, machine learning and automation are bringing us closer to a fully autonomous network infrastructure – a network and integrated day-two platform ecosystem that can manage, configure and improve itself with minimal human intervention.

At the architecture level, a high degree of autonomy means the network will automatically detect and resolve issues – also called self-healing. For example, if a network component fails, the system will reroute traffic to avoid downtime. And, by analyzing historical and current data and trends, it will predict potential failures and take proactive measures to prevent them.

The system will also monitor performance and adjust network configurations to improve reliability. This includes allocating resources dynamically, scaling up and down based on demand, and integrating new devices and services without manual setup. 

Importantly, security also gets a boost as the network will automatically detect and respond to a range of threats in real time.

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These capabilities make moving to an autonomous network infrastructure a strategic move: as your business grows, the infrastructure can keep adapting fast and securely at the same time without extensive manual intervention.

The technology and protocols behind the scenes

Even before AI and machine learning, this level of autonomy has relied on technologies such as software-defined networking, network function virtualization and intent-based networking:

• Software-defined networks decouple the control plane from the data plane and centralize network intelligence. This allows for more flexible and efficient network management, with dynamic adjustments to network configurations based on real-time needs.
• Network function virtualization allows network services – for example, firewalls, network address translation, virtual private networks, and intrusion detection and prevention – to be virtualized and deployed dynamically. This makes it easier to scale network resources up or down based on demand.
• Intent-based networking allows network administrators to define a desired outcome, and the network automatically configures itself to achieve that outcome. This makes network management simpler and helps to align it with your business goals.

Underpinning these technologies are real-time network performance telemetry and analytics. This data powers the platforms that use AI and machine-learning algorithms to improve resolution time, resolve common network incidents that can affect your organization, and identify vulnerabilities in network capacity and security.

These algorithms need vast amounts of high-quality, current and well-structured data to make informed decisions on network operations and identify patterns and anomalies that may, for example, indicate a security breach.

Where you really need warm-body support – especially in a pre-transformation network environment – your engineers can use these algorithms to resolve and report on network incidents. In turn, this will help you to define the business case for full network transformation based on actual data collected from your connected sites.

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4 steps to network autonomy

If you want to introduce autonomy into your organization’s network but are unsure if you can afford it or what it would take to complete the transition, take these steps to compile a network roadmap:

1. Budget intelligently: The initial investment required for this transformation can be substantial. Weigh the long-term benefits against the upfront costs, and ensure you have the financial resources to support the project. Keep in mind that multivendor network environments can push up costs, with residual costs from previous investments. And, in many regions, exchange-rate fluctuations are an important factor.
   
   On the upside, once they’re up and running, autonomous networks reduce operational costs by automating routine tasks and resource allocation. For example, they can adjust bandwidth and computing resources based on real-time needs, so you pay only for what you use. And cloud solutions offer improved performance at lower costs – as operational expenditure – compared with traditional on-premises systems.
2. Prepare for complexity: Integrating autonomous network technologies with existing systems can be complex. Ensuring compatibility between old and new technologies requires careful planning and execution, while disparate network management systems – including observability tools – can hold back progress during the transition.
3. Decide who will do the work: To transform your network, you will have to choose between using in-house skills and working with a trusted partner. Most organizations face a shortage of skilled personnel proficient in AI, machine learning and network automation, and training existing staff or hiring new talent can be challenging. Working with a partner is an efficient way of gaining ongoing access to these valuable skills.
4. Ramp up security measures: Autonomous networks can improve your security posture but also introduce new vulnerabilities. AI algorithms must be kept safe from manipulation, and the underlying network data feeding into the autonomous network has to be kept secure, accurate and up to date. Compliance with data-privacy regulations adds even more complexity.

Consider a partnership for swift success

There is clearly much to consider in a move to an autonomous network infrastructure, and you may lack the in-house skills to give the project the expert attention it needs. Therefore, working with an experienced partner is the easiest way of making the transition as painless as possible.

The ideal partner will be certified across technology vendors and familiar with your enterprise architecture, and will have platform-based network tools and services in place. Also look for experience in technologies such as AI and machine-learning, event-level reporting and telemetry and observability tools.

Beyond the technology, it’s just as important that your partner can first assess your current network environment and identify vulnerabilities and areas to modernize – in alignment with your business goals. Combined with security, governance and data management skills, this lays the foundation for an efficient network transformation strategy.

As a trusted local provider of global skills ranging from networks and cloud to data centers, GenAI and edge computing, NTT DATA has the experience, expertise and reach to transform your network in stages that match your budgets and business plans.

Let us use our tools and managed services to modernize your network and cloud environment to prepare your organization for the future.