# 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