Generative AI (GenAI) is rapidly reshaping industries, and network management is no exception. While traditional AI focuses on identifying relationships within data, GenAI goes a step further – creating entirely new datasets synthetically. This capability enables powerful new use cases but also comes with an insatiable demand for high-quality data. For network vendors and operators, the question is clear: how do you provide GenAI with the right data, in the right context, at the right time? The answer lies in deep packet inspection (DPI) analytics.
Why Generative AI matters for network management
Network functions executing critical tasks such as routing, load balancing and filtering can leverage GenAI to enhance effectiveness and efficiency. By mimicking human thinking, advanced GenAI models deliver accurate and context-aware responses to network events. These responses can be in any form or format, for example:
- Automatically generated SD-WAN access policies
- Technical diagrams showing alternative routing paths for latency-sensitive AR/VR traffic.
With retrieval-augmented generation (RAG), real traffic data can be combined with GenAI outputs – enabling precise and actionable recommendations for network engineers.
Deep packet inspection (DPI): the foundation of GenAI-driven visibility
At the heart of GenAI lies data. For network management, that means network traffic data – precisely where DPI analytics comes in. Advanced DPI engines, such as R&S®PACE2 and R&S®vPACE by ipoque, offer real-time traffic analytics that can be built into GenAI information pipelines as well as monitoring dashboards that oversee GenAI processes and outputs.
Training and fine-tuning GenAI models with DPI data
When it comes to model training, next-gen DPI software by ipoque classifies traffic in real time – across applications, services and protocols.
It also extracts metadata such as:
- Source and destination IP addresses
- Port numbers
- Packet sizes
- Jitter and round-trip-time
This fine-grained labeling expands the data points available during GenAI training, enabling a model to build a deep understanding of complex network behaviors.
Next-gen DPI engines by ipoque also feature encrypted traffic intelligence. That means even encrypted, obfuscated and anonymized traffic can be classified — ensuring GenAI models are trained on data that truly represents the state of the network. This improves the accuracy of GenAI model outputs significantly. The engines also cater for custom signatures, which facilitates traffic analysis in niche environments.
Prior to deployment, a GenAI model is fine-tuned to the customer’s environment. This requires sufficient data to be harvested from the local network in a short time. R&S®PACE2 and R&S®vPACE enhance fine-tuning by offering:
- Lightweight traffic filtering
- Small memory footprint
- Customizable minimum build configuration
This facilitates traffic capture across virtually any network environment.
From prompts to querying: Enhancing real-time inferencing with network visibility
DPI data also strengthens the prompting and querying stage of GenAI workflows. To contextualize a prompt, users need access to real traffic data. For example, a prompt that seeks “compression ratios for YouTube content” must include current data on YouTube traffic volumes, bandwidth availability, device types and overall throughput. This becomes even more pertinent in the case of RAG models, where DPI-driven historical and real-time traffic insights ensure timely, context-rich responses to network events.
Testing and validating GenAI recommendations through DPI analytics
Beyond training and inferencing, DPI helps network administrators test and validate their GenAI models.
Examples include:
- Comparing traffic flows simulated by a GenAI-based load balancer with real flows captured by DPI,
- Validating GenAI-recommended routing pathways for video traffic during large-scale events (e.g. sports streaming) with DPI insights on video quality metrics such as latency and jitter.
These insights also help administrators distinguish between policy/configuration issues and gaps in GenAI model logic.
Monitoring and securing GenAI workloads in modern networks
GenAI workloads are resource-intensive, requiring continuous monitoring to detect performance bottlenecks and disruptions. By harvesting DPI-driven insights into monitoring systems, vendors can identify:
- Performance issues such as congestion, memory overflows, or misconfigured routers
- Resource contention between GenAI processing and other network functions
- Security threats, including adversarial attacks, model poisoning, or data corruption.
By feeding DPI-driven analytics into monitoring dashboards, vendors can proactively secure and optimize their GenAI deployments.
Business value: how DPI-driven network analytics reduces costs and unlocks monetization
Comprehensive and configurable traffic analytics from DPI can be used as a shared source of intelligence across many network functions, driving network-wide consistency in terms of policies and actions, and reduced overheads. The breadth of traffic data rendered by DPI fulfils the intelligence needs of virtually any function, which makes it highly practical and efficient. Additionally, DPI-driven high-quality traffic analytics can be packaged into premium features that allow deeper investigation, rigorous experimentation and unlimited querying. This can drive new monetization streams for vendors.
In short, DPI transforms GenAI from an experimental technology into a scalable, revenue-generating tool for network management.
Conclusion: winning the GenAI race with DPI-powered network management
The GenAI race in network management has just begun, but the winners will be those who combine advanced AI models with the right data foundation. DPI analytics provides this foundation – delivering accuracy, visibility, and security at every stage of the GenAI lifecycle.
Vendors equipped with advanced DPI analytics gain:
- A first-mover advantage
- The ability to deliver high-quality generative outputs
- The trust of customers who demand secure, high-performance GenAI solutions
Learn more: Download our latest report Generative AI in Network Management featuring insights from over 75 network vendors and discover how DPI analytics is powering the next wave of intelligent network management.
