Community
Community

Exciting Announcement! In celebration of launching our AI Certification, we’re thrilled to offer a 50% discount exclusively. Seize this unique chance—don’t let it slip by!

Learn more

Category: Aviz Service Nodes

Categories
Aviz Service Nodes Network Observability

The KPI Advantage: Unlocking Network Observability Through Data

Introduction

In today’s digital era, network efficiency plays a pivotal role in determining the quality of communication and data exchange. Whether for data centers, service providers, or end-users, understanding key network Key Performance Indicators(KPI) like latency and bandwidth is crucial. These KPIs directly influence application performance, video streaming quality, online gaming, and cloud-based services. The ability to measure and optimize these parameters ensures a seamless user experience and improved network reliability. Lets discuss in detail on how Aviz Service Node (ASN) efficiently computes the different KPIs of any Network (Telco, DC, Edge, FTTH, Campus) and helps in achieving the refined Network Observability in this blog.

Supported KPIs

  • Session based Packet Stats: ASN keeps track of the sessions and calculates the Total number of packets, Total Bytes for each session processed in the ASN. The stats are processed for each session direction - Uplink and Downlink.
  • Latency: Latency is the time it takes for a packet of data to travel from the User equipment(UE) to the Data Network(DN) and back. ASN measures the latency with the accuracy in nanoseconds (ns) and can be affected by factors such as network congestion, distance, processing, Queuing and Transmission delays. High latency results in lag, negatively impacting real-time applications like video conferencing, Gaming, VoIP etc.,
  • Bandwidth: Bandwidth is the maximum data transfer rate of a network, measured in Bytes per second (Bps). It determines how much data can be sent or received within a given timeframe. High bandwidth enables faster data transfer, reducing buffering and improving performance for high-demand applications. The major factors affecting Bandwidth are Network infrastructure, capacity, congestion, overheads.
  • TimeStamps: ASN can calculate bandwidth and latency based on Network timestamps if present in the packet. But ASN also can add the timestamp to the packet at nanosecond accuracy which will help in calculating the interval based KPIs.

KPI Calculation

ASN calculates average bandwidth and latency at 5-second intervals and exports the KPI data to a Kafka topic. Additionally, when a session is closed before the completion of the 5-second interval, the system triggers an export to a priority Kafka topic. This ensures real-time observability and accurate metric reporting.
  • Bandwidth is computed as the total bytes transmitted every second and average of the 5-second window as well.
  • If a session terminates early, the actual bandwidth data (for the shorter duration) is calculated and exported immediately to a priority Kafka topic.
  • The system ensures precise tracking by timestamping every exported KPI event.
This guarantees that critical network metrics are available in real time, allowing for improved monitoring, anomaly detection, and performance optimization.

KPIs Supported Matrix

KPIS Per Session Per Application Per Region
Throughput/Bandwidth
Uplink Latency
Downlink Latency
Retransmit count
Total Packets and Bytes

Key Benefits of Optimizing Latency and Bandwidth

  • Enhanced User Experience: Reduced latency ensures smoother online interactions, while higher bandwidth prevents buffering and slowdowns.
  • Improved Real-Time Communication: Low-latency networks are crucial for VoIP, gaming, and financial transactions.
  • Better Cloud Service Performance: Optimized bandwidth supports seamless cloud storage and computing.
  • Scalability and Reliability: Networks with high bandwidth and low latency can handle increased traffic efficiently.
  • Increased Productivity: Faster and more reliable networks enhance workplace efficiency by reducing downtime.

Conclusion

Network KPIs are fundamental for evaluating and improving network performance. As businesses and consumers rely more on digital services, optimizing these metrics becomes imperative for delivering seamless connectivity. By leveraging advanced network observability strategies of ASN, Networks can enhance user experience, reduce delays, and ensure robust performance. Monitoring and optimizing latency and bandwidth will continue to be essential in the evolution of next-generation networking technologies.
Categories
Aviz Service Nodes Network Observability

Enhancing Application Observability: Significance of ASN in IP Traffic Analysis

Introduction

In today’s digital landscape, data centers, edge & distributed infrastructure, enterprise & campus networks, and FTTH (Fiber to the Home) networks are critical components of the modern business, supporting everything from cloud services and enterprise applications to high-speed internet connectivity for consumers. As businesses grow and technology continues to advance, the need for more efficient and effective management of these network environments becomes ever more critical. This is where the Aviz Service Node (ASN) comes in. ASN is a powerful network solution designed to optimize network operations by providing enhanced traffic observability, performance metrics, and network management capabilities. By deploying ASN in a data center, edge & distributed infrastructure, enterprise & campus network or FTTH environment, organizations can ensure better control, improved application performance, and more efficient network traffic handling. In this blog, we’ll explore how ASN is revolutionizing network management and why it is becoming an essential tool for modern network operations.

Challenges Faced in Network Infrastructures

  • Growing Data Traffic: As data traffic continues to grow exponentially, data centers face challenges in managing congestion, optimizing bandwidth, and scaling efficiently. High traffic volumes can overwhelm networks, leading to delays and decreased application performance.
  • Application Performance: Ensuring consistent application performance is a major challenge. Data centers must manage high latency, minimize downtime, and optimize response times across dynamic and diverse workloads to meet service-level agreements (SLAs) and deliver quality user experiences.
  • Network observability: Without granular observability into network traffic, it becomes difficult to identify performance bottlenecks, security risks, and traffic anomalies. Lack of real-time monitoring makes proactive management and issue resolution challenging.

ASN for IP Traffic Analysis

IP Session Management

ASN has the capability to analyze high-volume traffic, extracting millions of IP sessions with precision.It stores all the sessions in memory to achieve high performance packet processing and higher throughput. Processing IP packets from DC/FTTH/Edge/Campus network and tracking sessions based on IP Tuples to create Metadata for each session. Data Center and FTTH Network Traffic Analysis involves the processing of IP packets originating from IP network environments. By analyzing these IP packets and tracking sessions, Metadata is generated for each unique session. This Metadata can include information like session duration, total bytes transferred, application protocol used, and potentially other relevant details depending on the analysis requirements. This extracted Metadata is then used for a variety of purposes, such as network performance monitoring, traffic engineering, capacity planning, security analysis, and application behavior understanding.

Protocol Decoding and Header Stripping

In the realm of network traffic analysis, gaining observability into the actual payload of encapsulated packets is crucial for comprehensive insights. To achieve this, ASN employs techniques like protocol decapsulation and header stripping. This process involves removing the outer headers of encapsulation protocols, revealing the original packet within.

Supported Protocols

  • GRE (Generic Routing Encapsulation)
  • ERSPAN (Encapsulated Remote SPAN
  • VxLAN (Virtual Extensible LAN)
  • PPPoE (Point-to-Point Protocol over Ethernet)
  • L2TP (Layer 2 Tunneling Protocol)
  • IPoE (IP over Ethernet)
By supporting decapsulation and header stripping, ASN helps achieve the following:
  • Reduces overhead by removing unnecessary headers, improving network efficiency and performance.
  • Facilitates deeper packet inspection, enabling detailed analysis of application-specific data and traffic patterns.
  • Improves troubleshooting by providing observability into the actual payload of packets, making it easier to identify and resolve network issues.

Application Identification

ASN with a robust Deep Packet Inspection (DPI) engine enhances the granular observability and control over network traffic within a data center environment. This approach enables the identification and classification of a wide array of applications traversing the network. Currently, the DPI engine supports the identification of over 500+ applications, showcasing its extensive capabilities in application observability. Furthermore, there are plans to significantly expand this capability, with a roadmap aiming to support the identification and classification of over 1000 applications in the near future. This expansion will provide even greater insights into application usage patterns and potential network optimization opportunities.
Application identification in ASN is achieved by below methods:
  • Pattern Matching
  • SNI Matching
  • Global IP Based Identification
  • Port Based Identification

KPI Calculation

Exporting Session Metadata

Comprehensive session metadata, encompassing APP (Application), KPI (Key Performance Indicator), and detailed session information, can be exported to external systems via Kafka. This facilitates further analysis, long-term storage, and integration with other network management and monitoring tools.

High-Frequency KPI Export

To maintain optimal performance and rapid anomaly detection, KPI data is exported every 5 seconds—a crucial capability that ensures real-time insights into network health. This is achieved through efficient buffering, parallel processing, and low-latency Kafka integration, ensuring that large volumes of session data are aggregated and transmitted without bottlenecks. The system to maintain consistent throughput, even under peak network load to support time-bound KPI insights without delays or data loss.

Real-Time Alerts

Critical scenarios within the network, such as session deletion, release, or handover based on priority, can trigger real-time alerts. These alerts are immediately exported via Kafka to notification systems, enabling rapid response and mitigation of potential network issues.

Timestamping for Time Series Analysis

To enable granular time-based analysis, both packets and sessions are meticulously timestamped within the ASN. These timestamps record the creation time, the last seen time, and the export time, providing valuable insights into network traffic patterns and trends over time.
KPIS Per Session Per Application Per Region
Throughput/Bandwidth
Uplink Latency
Downlink Latency
Retransmit count
Total Packets and Bytes

Packet Deduplication

In a data center environment, there can be a significant amount of duplicate traffic, particularly in applications that involve large file transfers or streaming media. ASN Packet deduplication can help to reduce this redundancy by identifying and removing duplicate packets before they are transmitted across the network. ASN provides a powerful tool for customizing deduplication configurations in network traffic analysis. Packet deduplication within ASN involves customizable parameters like Packet Source, Anchor, Offset, and Window Size.

Packet Capture

In dynamic network environments like Data Centers (DC) deployments, where traffic patterns and types vary unpredictably, Aviz Service Node (ASN) systems are essential for handling traffic at line rate. To ensure smooth operations and address any issues in real-time, packet capture becomes an invaluable tool.The packet capture feature allows network administrators to monitor live traffic flowing through the ASN without disrupting its primary functions. This capability is crucial for effective debugging, troubleshooting, and performance analysis in complex, high-traffic environments, where insights from live network data are vital to maintaining operational stability. By enabling live traffic capture, packet capture ensures that administrators can diagnose and analyze network behavior instantly, supporting proactive management in ever-evolving network landscapes

Benefits of ASN for IP Traffic Analysis

  • Enhanced Network observability: Better insights into traffic flow, application behavior, and performance metrics.
  • Network Application Insights: ASN provides per user level application data and related metrics which helps admin to address any network performance issues.
  • Network Optimization: ASN enables continuous measurement and optimization of network health, traffic handling, and resource allocation.
  • Scalability: ASN’s flexible architecture can scale to meet the demands of large data centers with high traffic loads.

FAQs

1. What is ASN and how does it enhance IP traffic analysis in modern networks?

 Aviz Service Node (ASN) is a high-performance observability solution designed for data centers, edge, FTTH, and enterprise networks. It enables real-time IP traffic analysis by tracking millions of IP sessions, generating metadata, and delivering actionable insights on application behavior, throughput, and latency.

ASN uses a robust Deep Packet Inspection (DPI) engine that supports over 500+ applications (with plans to expand beyond 1000), identifying them via pattern matching, Server Name Indication (SNI), global IP mapping, and port-based techniques for precise application-level observability.

Yes. ASN supports protocol decapsulation and header stripping for GRE, ERSPAN, VxLAN, PPPoE, L2TP, and IPoE, enabling deeper packet inspection by revealing encapsulated payloads—essential for troubleshooting, efficiency, and root cause analysis.

ASN exports enriched session metadata and KPIs via Kafka every 5 seconds, allowing real-time visibility and fast anomaly detection. It also triggers alerts for critical events like session deletions or handovers, ensuring swift incident response.

Duplicate packets inflate bandwidth usage and distort performance metrics. ASN uses intelligent, configurable packet deduplication to eliminate redundant traffic, improving monitoring accuracy and network efficiency across high-throughput environments.

Categories
Aviz Service Nodes

Introducing Aviz Service Nodes R2.0 – Empowering Enterprise, Data Center and Telco Deployments

In today’s ever-evolving network landscape, staying ahead means continuously innovating. Building on the trusted foundation of our previous releases—including the robust telco features of 1.3.1—we are excited to introduce R2.0. This release is not just an update; it’s a reimagining of how enterprise and telco networks operate, bringing you enhanced performance, precision, and peace of mind

What’s New in R2.0

In R2.0, we’ve focused on adding tangible value for our customers. Here’s a quick look at what you can expect:
  • Enterprise & Telco Readiness: Fully ASN-ready for seamless deployment across large-scale networks.
  • Packet Deduplication for DC: Optimizes network performance by eliminating redundant packet processing.
  • Advanced DPI for IP Packets: Leverages cutting-edge deep packet inspection for precise application identification.
  • Enhanced Packet Capture: Delivers robust support tailored for both telco and enterprise environments.
The image below provides a concise overview of ASN.

5G Core Advancements

ASN 2.0 is designed to handle the scale and complexity of both enterprise and telecom networks, ensuring seamless deployment and operational efficiency. It processes incoming telecommunication traffic, extracting critical metadata from 4G-LTE, 5G-NSA, and 5G-SA networks, providing end-to-end visibility for mobile operators and service providers.
With intelligent control-plane (C-Plane) and user-plane (U-Plane) correlation, ASN enables precise tracking of subscriber sessions, mobility events, and service quality metrics. Enhanced KPI monitoring now delivers sub-5-second precision for bandwidth and latency calculations, ensuring real-time network optimization. Additionally, optimized Kafka metadata export improves data accuracy and reduces processing latency, enabling faster insights and seamless analytics across modern network infrastructures.

Packet Deduplication

Our new packet deduplication feature is designed to streamline data flow. Removing redundant packets not only boosts processing efficiency but also improves real-time network analytics, ensuring your systems run at peak performance.
  • Deduplication Process: Traffic is continuously analyzed in real-time with a granularity of up to 8 milliseconds, enabling the rapid detection and elimination of duplicate packets. The analysis process begins by inspecting ingress packets for familiarity based on their type and fields. If a packet is found to exist within the customer-defined time frame, it is identified as a duplicate and dropped. Users can configure the Packet Source (Full or Routed Packet) to filter out redundant traffic, even across multiple hops. Anchor & Offset settings define where and how packet data is compared, while the Window Size (2-8ms) ensures efficient real-time deduplication. For detailed configuration, refer to the GitBook.
Below is the FlowVision UI snapshot for Packet Deduplication

Application Identification with Advanced DPI

With ASN 2.0, we extend beyond telco packet correlation to deliver end-to-end IP network observability, making ASN a powerful solution for data centers, FTTH, edge, and campus networks. By leveraging Deep Packet Inspection (DPI), ASN can now classify over 500 applications at line rate, extracting critical network intelligence for enhanced traffic analysis and security. ASN’s advanced DPI engine uses pattern recognition, SNI matching, IP geolocation, and port-based analysis to identify applications with high accuracy. It also captures user agent metadata, bandwidth usage, and key performance indicators (latency, packet loss, and jitter), enabling operators to optimize network performance in real time.

Additionally, enhanced KPI monitoring in ASN 2.0 delivers sub-5-second precision for bandwidth and latency metrics, while optimized Kafka metadata export ensures faster processing and improved analytics. Here is a snapshot of our Kibana dashboard, showcasing metadata extracted by ASN along with application insights identified by ASN’s advanced DPI engine.

Comprehensive Packet Capture

Effective troubleshooting and network analysis are at your fingertips with our enhanced packet capture capabilities. Designed to meet the rigorous demands of both enterprise and telco deployments, this feature empowers your team to quickly diagnose and resolve issues. ASN 2.0 allows users to configure interface capture settings, selecting specific ports for Tx/Rx traffic analysis. Capture duration can be set between 1-10,000 ms, with a file size limit of 1-1,000 MB. Users can define filenames for captured data and enable automatic cleanup of old PCAP files. For detailed configuration, refer to the GitBook.

Enhanced packet capture capabilities in ASN 2.0 enable users to generate live traffic in PCAP format for real-time network analysis. Designed for both enterprise and telco environments, this feature streamlines troubleshooting by facilitating faster diagnostics and issue resolution

Below is the FlowVision UI snapshot for Packet Capture

Real-World Impact: Benefits You Can See

Imagine a network where every packet is optimized for performance, every application is clearly identified, and troubleshooting is more efficient than ever. R2.0 is designed to empower your team, reduce operational costs, and provide the reliable network performance that modern enterprises and telcos demand.

R2.0 isn’t just an upgrade—it’s our commitment to continually pushing the boundaries of network observability. We’re excited for you to experience these innovations firsthand and look forward to supporting your journey into the future of enterprise and telco networking.

Book your demo to see how ASN R2.0 transforms network observability, optimizes traffic, and enhances real-time analytics for enterprise and telco deployments!

Book Your Demo

FAQs

1. What’s new in Aviz Service Node (ASN) R2.0 for enterprise and telco networks?

 ASN R2.0 introduces packet deduplication, advanced deep packet inspection (DPI), enhanced packet capture, and real-time KPI monitoring. It’s designed for scalable deployment in enterprise, telco, and FTTH environments, optimizing performance and observability across complex infrastructures.

 ASN uses 8ms granularity to detect and eliminate duplicate packets using configurable anchors, offsets, and time windows. This reduces processing overhead and boosts analytics accuracy—especially vital for high-throughput data center and telco deployments.

 

ASN’s DPI engine supports over 500+ application signatures and identifies them using pattern matching, SNI, port-based rules, and geolocation data. It also captures user agents, bandwidth usage, and KPIs like jitter and packet loss for full traffic visibility.

Yes, ASN 2.0 supports 4G-LTE, 5G-NSA, and 5G-SA traffic analysis. It correlates control and user planes, tracks subscriber sessions, and exports enriched Kafka-based metadata for accurate, real-time visibility in mobile operator environments.

ASN enables interface-specific packet capture with customizable file size, duration, and auto-cleanup settings. It supports Rx/Tx traffic filters, making it ideal for on-demand diagnostics and troubleshooting across large-scale enterprise and telco networks.

Categories
Aviz Service Nodes

Evaluating Aviz Service Node capabilities using the Spirent Landslide ability

5G PlugFest Summary

Introduction:

Aviz Service Nodes(ASN) enhance network observability, which operates on general-purpose hardware and offer significant cost savings and optimal performance. ASN provides essential Subscriber intelligence by metadata extraction and correlation for 4G-LTE, 5G-NSA, and 5G-SA networks to achieve comprehensive network analytics.

To validate accuracy and performance along with the KPIs of the ASN product, we utilized the Spirent Landslide to emulate the 5G and 5G-NSA components.

Landslide is a versatile platform designed to test and emulate 5G and O-RAN mobile networks on both traditional and cloud-native infrastructures. It simulates real-world traffic from millions of mobile subscribers to extensively test the 5G core in standalone and non-standalone configurations. 

Master Topology

Features validated by Spirent

Metadata Extraction and Validation:

ASN works on different 5G-SA, 5G-NSA and 4G-LTE interfaces for metadata extraction and achieves the correlation between User and Control Plane. It involves identifying, retrieving, and verifying relevant metadata from various interfaces of Telecom networks, to ensure its accuracy and consistency. Effective metadata extraction and correlation by ASN are crucial for ensuring better data management, analysis, and decision-making.

"The comprehensive metadata extraction and correlation capabilities of ASN are designed to provide unparalleled network insights, ensuring our clients can make informed decisions quickly and accurately."

Chid Perumal, CTO of Aviz Networks

Handling Handovers:

In 5G networks, handover entails shifting an active call or data session from one cell or base station to another. The ASN manages the smooth extraction and correlation of control and user packets throughout this handover process. The ASN possesses the capability to manage all potential handovers in both 5G and 5G-NSA scenarios.

Application identification:

The primary purposes of identifying applications in telco traffic are traffic management, quality of service (QoS), security, billing, and analytics. ASN’s deep packet inspection identifies applications using the Server Name Indication (SNI), application IP address, destination port and application behavior.

Performance and scalability:

The ASN possesses the capability to manage a maximum of three million subscribers in both 5G and 5G-NSA networks. Additionally, it extracts and correlates control packets for a user plane traffic of up to 150 Gbps. The ASN’s validation includes handling mixed packet sizes of traffic equivalent to real-world scenarios.

Landslide's ability to emulate complex 5G network environments has been instrumental in validating the high performance and scalability of Aviz Service Nodes, ensuring the solutions meet the rigorous demands of modern telecom networks.

Masayuki Takemura-San, Spirent Japan Team

For the detailed test report and the performance benchmarking, click here.

FAQs

1. What is the role of the Aviz Service Node (ASN) in 4G-LTE, 5G-NSA, and 5G-SA networks?

Aviz Service Nodes (ASN) enhance network observability by extracting, correlating, and analyzing metadata from user and control planes across 4G-LTE, 5G-NSA, and 5G-SA interfaces. ASN provides deep subscriber intelligence to optimize network performance, security, QoS, and analytics across mobile core networks.

Spirent Landslide was used to emulate large-scale 5G network environments, generating traffic from millions of mobile subscribers. This allowed Aviz Networks to validate ASN’s metadata extraction accuracy, handover management, application identification, and performance scalability under real-world telecom conditions.

ASN uses deep packet inspection (DPI) techniques to identify applications by analyzing Server Name Indication (SNI), destination IP addresses, ports, and behavioral patterns. This ensures better traffic classification, QoS enforcement, billing accuracy, and security threat detection within telecom networks.

Aviz Service Nodes demonstrated the ability to support up to 3 million subscribers while managing correlated user plane traffic at up to 150 Gbps. This performance was validated under mixed packet size scenarios, ensuring ASN’s readiness for large-scale 5G deployments.

During 5G and 5G-NSA handovers, ASN ensures seamless metadata extraction and packet correlation between old and new base stations. This guarantees uninterrupted subscriber session tracking and maintains full network visibility even during complex mobility events.

 

Yes. ASN runs reliably on traditional telecom hardware and cloud-native cores. This ensures operators modernizing their 5G infrastructure retain continuous observability and deep subscriber intelligence.

 ASN is vendor-agnostic and supports:

  • Standard 4G/5G interfaces
  • Diverse RAN and core elements

Consistent metadata extraction and correlation across multi-vendor environments
 This makes it ideal for open RAN and heterogeneous networks.

Absolutely. ASN’s lightweight, x86-based architecture enables efficient edge deployment. This allows operators to perform local correlation, app detection, and anomaly checks close to the user, reducing latency and improving real-time insights.

By using deep packet inspection (DPI) and behavioral analysis, ASN:

  • Detects unauthorized or malicious apps
  • Enhances security enforcement
  • Provides context-rich metadata for proactive incident response and compliance reporting

ASN combines:

  • High-scale subscriber intelligence (up to 3M subscribers)
  • Real-time handover correlation
  • 4G/5G multi-interface support

Spirent-validated performance up to 150 Gbps
 All delivered in a single, platform-agnostic package purpose-built for modern telecom networks.

Contact Us

Evaluating Aviz Service Node capabilities using the Spirent Landslide ability

5G PlugFest Summary Introduction: Aviz Service Nodes(ASN) enhance network observability, which operates on general-purpose hardware and offer significant cost savings and optimal performance. ASN provides essential Subscriber intelligence by metadata extraction and correlation for 4G-LTE, 5G-NSA, and 5G-SA networks to achieve comprehensive network analytics. To validate accuracy and performance along with the KPIs of the […]