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 | |||
| 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.
