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Aviz Service Node enhances IP traffic analysis for better observability

Source Decision Insights Coverage Published November 7, 2025 Companies 2
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2 companies named across 16 categories, one of 28 articles referencing DEEP. Previous coverage: ASN R2.0 Introduces Enhanced Network Observability (Nov 2025).

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Aviz Service Node (ASN) offers an OP designed for Internet Protocol (IP) networks, enhancing performance through detailed data analysis. IT leaders may find Autonomous System Number (ASN) valuable for optimizing application performance and improving overall operational efficiency.

Challenges in Network Infrastructure

Network infrastructures face various challenges, including congestion and scaling issues that impede user experience. Teams also contend with performance threats such as latency and packet loss, which jeopardize Service Level Agreements (SLAs). Additionally, a lack of real-time telemetry can obscure the identification of performance bottlenecks.

ASN for IP Traffic Analysis

IP Session Management

ASN processes high-volume packet streams while managing millions of IP sessions concurrently, allowing for detailed session metadata aggregation. This session management is vital for high-throughput network environments.

Key metrics collected include duration, traffic direction, and packet counts, which facilitate performance monitoring and security assessments.

Protocol Decapsulation and Header Stripping

ASN utilizes protocol decapsulation techniques to inspect payloads, thus enabling Deep Packet Inspection (DPI) and aiding in troubleshooting efforts. This approach allows for improved visibility into network operations.

Supported Tunnels/Encapsulations

Supported tunnel types include Generic Routing Encapsulation (GRE), ERSPAN, Virtual Extensible LAN (VXLAN), PPPoE, L2TP, and IP over Ethernet, which contribute to the system's efficiency in managing data flow.

Application Identification (DPI)

ASN's Deep Packet Inspection (DPI) technology currently identifies over 500 applications, expanding to more than 1000 in the future. This identification employs techniques such as pattern matching and SNI (Server Name Indication) for enhanced application visibility.

KPI Calculation and Streaming

Exporting Session Metadata

ASN facilitates the exporting of session records and key performance indicators (KPIs) to external systems using Kafka, which aids in advanced analytics and monitoring.

High-Frequency KPI Export

Real-time Key Performance indicator (KPI) data is streamed every five seconds, ensuring that performance metrics are readily available for operational assessments.

Real-Time Alerts

Critical events such as session changes trigger notifications to aid quick response and issue resolution.

Packet Deduplication

The system provides configurable deduplication capabilities that help eliminate duplicate packets, which can distort analytics and inflate bandwidth usage. This process leads to more accurate network performance metrics.

Packet Capture (Live)

ASN supports live packet capturing, enabling effective troubleshooting without disrupting network operations, particularly in busy environments.

Benefits of ASN for IP Traffic Analysis

ASN enhances operational transparency, delivers detailed application insights, and allows for ongoing network optimization, tailored for large scale operations.

FAQs

1) What is ASN?

ASN is designed for observability across various network infrastructures, providing valuable insights into performance metrics.

2) How does ASN identify applications?

Through a sophisticated DPI engine, ASN accurately categorizes network applications using diverse identification techniques.

3) Can ASN handle advanced packet analysis?

Yes, ASN is equipped for advanced techniques like decapsulation to analyze inner payload data.

4) How does ASN manage metadata exports?

It exports critical session data to analytics platforms, ensuring real-time monitoring capabilities.

5) Why is deduplication significant?

Reducing duplicates optimizes bandwidth efficiency and enhances the accuracy of performance metrics.

Blog post, originally published by Subhiksha Devarajan at Aviz Networks.

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