Aviz Service Node (ASN)

AI-Ready Packet Intelligence for Modern Network Observability

April 9, 2026

Overview

Modern networks are highly distributed-spanning data centers, public cloud, edge, and telecom infrastructures making traditional visibility approaches fragmented and inefficient.

Aviz Service Node (ASN) provides a unified packet intelligence layer that transforms raw network traffic into optimized, enriched, and actionable telemetry for security and observability platforms.

Deployed as a software-defined platform on commodity x86 or as a virtual instance (vASN), ASN enables organizations to scale visibility while reducing infrastructure complexity and cost.

The Challenge

Organizations face increasing challenges in network visibility:

01

Exploding Traffic Volumes Across hybrid and multi-cloud environments.

02

Tool Inefficiency Due to duplicate, noisy, or irrelevant traffic.

03

Lack of Application and Subscriber-Level Visibility

04

Limited Visibility into East-West and Intra-Workload Traffic

05

High Cost and Rigidity of Proprietary Appliances

The Aviz ASN Approach

ASN introduces a packet intelligence pipeline that processes traffic before it reaches tools

Figure 1: Aviz Service Node (ASN) – Software-Defined Packet Intelligence Stack

Aggregate

• Collects traffic from TAP/SPAN, cloud mirroring, and virtual agents across distributed environments

Optimize

• Removes duplicates, filters noise, and prepares traffic for efficient downstream processing

Enrich

• Converts packets into structured, high-fidelity metadata with application and session context

Accelerate (Optional)

• Leverages DPU-based acceleration (e.g., BlueField-3) for high-performance, low-latency processing

Distribute

• Intelligently forwards relevant traffic and metadata to security and observability tools

Key Capabilities

01

Deep Packet Inspection (DPI)

Identifies and classifies 2000+ applications.

Enables granular application-level visibility.

02

Intelligent Traffic Optimization

L2–L4 deduplication reduces tool load by 30–50%.

Advanced filtering ensures only relevant traffic is delivered.

03

Rich Metadata Generation

Extracts application, protocol, and session-level metadata.

Enables analytics without full packet storage.

04

Subscriber-Aware Analytics (Telco)

GTP correlation across control and user planes.

Enables per-subscriber visibility in 4G and 5G networks.

05

Metadata Streaming & Ecosystem Integration

Kafka-based export (JSON format).

Integrates with SIEM, NDR, and observability tools (Splunk, Datadog, Elastic, etc.).

06

Real-Time Packet Capture

Generates PCAP for forensic analysis and troubleshooting.

Cloud & Virtual Deployment (vASN)

ASN extends into cloud environments through Virtual ASN (vASN), enabling:

• Integration with cloud-native traffic mirroring (AWS)
• Agent-based (vTAP) traffic acquisition for workload-level visibility
• Visibility into east-west and intra-host traffic

vASN ensures consistent packet intelligence across:

• Public cloud
• Hybrid architectures

Hardware Acceleration with DPU

ASN supports DPU-based acceleration (e.g., NVIDIA BlueField-3) to:

• Achieve line-rate packet processing
• Reduce CPU overhead
• Deliver low-latency, high-throughput performance

This is particularly valuable for:

• Telco-scale deployments
• High-density data centers
• Performance-sensitive environments

Deployment Flexibility

ASN can be deployed as:

Physical ASN (Bare Metal)

• High-throughput environments
• Data centers and telecom networks

Virtual ASN (vASN)

• Public Cloud environments
• Edge and distributed deployments

This unified architecture enables consistent visibility across all environments.

Use Cases

01

Enterprise & Data Center

• Application-aware traffic monitoring
• Tool optimization and cost reduction
• East-west visibility

02

Telecom (4G/5G)

• Subscriber-aware analytics
• GTP correlation
• Network performance monitoring

03

Cloud & Hybrid Environments

• Workload-level visibility
• Cloud traffic optimization

04

Security & NDR Enablement

• Improved threat detection with enriched metadata
• Efficient traffic delivery to NDR/SIEM tools
• Reduced noise and false positives

Key Benefits

01

End-to-End Visibility

From core network to cloud and edge

02

Improved Tool Efficiency

Deliver only relevant, optimized traffic

03

Reduced Infrastructure Costs

Eliminate proprietary hardware dependencies

04

Scalable Architecture

Linear scaling with compute resources

05

Future-Ready Platform

Designed for AI-driven observability and analytics