In today's fast-changing networking world, Telecoms need top performance, robust security, and smooth operations. Network telemetry can help achieve this by acting as a “crumb trail” of the network. Let’s explore network telemetry, the protocols and standards that drive it, and how they collectively illuminate the path to network intelligence.
Network telemetry is a multidimensional practice that entails the collection, analysis, and reporting of network data, providing an unobstructed view into the inner workings of network infrastructures. It captures a variety of data types, such as packet headers, flow statistics, device metrics, and more, to offer a perspective on network performance and behaviour. These insights are useful for diagnosing issues, optimising operations, ensuring security, and making informed decisions. Network telemetry operates in real-time, ensuring that network administrators and engineers have up-to-the-second information at their fingertips to manage and secure their networks effectively.
To learn more about:
➡ How Network Telemetry is currently used?
➡ What are the unique features of Network Telemetry?
➡ What AI approaches are there for Network Telemetry analytics?
➡ How can you implement AI Network Ops into your Operations?
read our recent article 'The AI-Driven Future of real-time Telemetry Analytics'.
To fully understand network telemetry, we need to look at the role of protocols and standards in facilitating the collection and interpretation of telemetry data. These communication mechanisms and guidelines lay the foundation for the accurate, efficient, and reliable transmission of data across complex network infrastructures.
Let's embark on our exploration of key telemetry protocols and standards that are instrumental in modern network monitoring and management.
Widely recognised as a fundamental network management protocol, SNMP has been a staple in the networking industry for decades. SNMP is an Internet Standard protocol for collecting and organising information about managed devices on IP networks and for modifying that information to change device behaviour. It is widely used to monitor and manage network devices, including routers, switches, servers, printers, and more.
At its core, SNMP is a protocol designed to facilitate the exchange of crucial management information between network devices, fostering communication that ensures optimal performance. It operates through a triad of essential components — the SNMP manager, SNMP agents, and managed devices. The SNMP manager is responsible for collecting and processing information from SNMP agents, which are software modules running on network devices. The information collected includes various metrics and statistics related to the performance and health of the network devices.
SNMP is particularly useful because it provides a standardised way to retrieve data from network devices, making it easier to monitor and manage diverse types of equipment in a network. It enables the collection of performance data from network devices, aiding in the monitoring and troubleshooting of issues. SNMP is extensible and supports different versions, with SNMPv3 being the most secure version, providing features like authentication and encryption.
OptOSS AI harnesses SNMP telemetry data to provide real-time, actionable insights across the OSI model layers. Learn more about the OSI model and how OptOSS AI can help to monitor device applications within any OSI layer in our recent article.
NetFlow is a protocol for the collection and monitoring of traffic data within IP networks. NetFlow operates on the principle of flow monitoring, tracking the interactions between source and destination IP addresses, ports, and protocols.
Similar to SNMP, NetFlow relies on a structured communication model involving flow exporters (equivalent to SNMP agents), flow collectors (similar to SNMP managers), and network devices (equivalent to managed devices). This synergy ensures a streamlined exchange of flow data, creating a comprehensive dataset that aids in the understanding of network behaviour.
NetFlow is particularly valuable in network telemetry due to its standardised approach to data collection. By providing a common language for describing network flows, NetFlow facilitates interoperability across a diverse range of network devices. NetFlow's focus on flow-level data complements other telemetry methods, offering a more granular view of network activity.
The influence of NetFlow extends across vendor landscapes, with analogous flow-based telemetry technologies such as sFlow and IPFIX gaining adoption.
SFlow operates by sampling packets at the interface level, offering a representative view of overall network traffic. This sampling approach ensures efficiency in data collection without overwhelming the network infrastructure. sFlow captures key information such as source and destination addresses, ports, and protocol types.
The structured nature of sFlow data enhances interoperability across diverse devices and vendors, fostering seamless integration into various network environments. This standardisation ensures that network administrators can leverage sFlow alongside other telemetry protocols, creating a unified and comprehensive monitoring strategy.
Flow-based protocols like sFlow (as well as J-Flow, and cFlowd) extend the capabilities of traditional flow monitoring. They sample packets to create flow records, offering a granular view of network activity. These protocols enhance visibility into network behaviour, enable the identification of performance bottlenecks and security incidents, and are valuable for real-time analysis, and proactive management.
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For detailed flow-level telemetry data, IPFIX emerges as a crucial standard. IPFIX allows network devices to export information about flows, including details such as source and destination IP addresses, ports, and protocol types. This standardised format aids in the consistent interpretation of flow data across diverse devices and vendors, enabling network administrators to make informed decisions and respond promptly to evolving network conditions.
IPFIX operates on the principle of defining information elements, encapsulating specific attributes and characteristics of network flows. These elements are then exported to a collector, forming a comprehensive dataset that can be analysed for performance monitoring, security analysis, and network troubleshooting.
IPFIX specifically focuses on the export of flow-level information, providing a more granular view of network activity. This granularity proves invaluable in scenarios where detailed insights into individual communication patterns are essential for comprehensive network analysis.
NetFlow, sFlow, and IPFIX are all protocols used for flow-based telemetry in network monitoring, but they differ in their origins, implementations, and specific features. Here's a comparison of NetFlow, sFlow, and IPFIX:
In summary, while all three protocols serve the purpose of flow-based telemetry, NetFlow is closely associated with Cisco, sFlow is an open standard with a focus on packet sampling, and IPFIX is an industry-standard protocol designed for interoperability and flexibility. The choice between them depends on specific network requirements, vendor preferences, and the desired level of granularity in telemetry data.
OpenTelemetry is an open-source observability framework.It standardises the collection and processing of observability data, ensuring a unified approach that simplifies the integration of telemetry across diverse environments. OpenTelemetry offers a set of APIs, libraries, agents, and instrumentation to enable observability in modern, dynamic environments, and supports multiple programming languages, making it versatile for a wide range of applications. OpenTelemetry focuses on three primary types of telemetry data: logs, metrics, and traces.
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OpenTelemetry provides APIs and SDKs for various programming languages, allowing developers to instrument their applications with minimal effort. These tools enable the collection of telemetry data in a consistent manner across different environments. The OpenTelemetry Collector is another critical component that receives, processes, and exports telemetry data, acting as a centralised hub for managing data pipelines and ensuring that logs, metrics, and traces are efficiently handled and transmitted to analysis platforms. Additionally, OpenTelemetry offers instrumentation libraries for popular frameworks and libraries, which simplify the process of adding observability to existing applications without extensive code modifications.
Streaming Telemetry introduces an approach to data collection by providing real-time insights into network performance. Unlike traditional polling methods, Streaming Telemetry offers a continuous flow of data, enabling network engineers to stay ahead of issues and respond promptly to evolving network conditions.
YANG (Yet Another Next Generation) serves as a data modelling language used to define the structure, semantics, and relationships of data models in a standardised way. These models provide a standardised format that facilitates communication and understanding between different network devices, software applications, and management systems. By offering a common language for expressing the structure of data, YANG enables automation, programmability, and ease of communication in complex network architectures. OpenConfig and the IETF (Internet Engineering Task Force) are two key avenues through which networking leverages YANG models, with OpenConfig emphasising vendor-neutral models, and the IETF providing a broader standardisation framework for diverse networking requirements. The IETF-standardised YANG models cover a wide range of networking functionalities, including routing protocols, network security, and service provisioning. OpenConfig's contribution to standardised YANG models ensures that the networking industry benefits from a comprehensive and interoperable framework, fostering a more unified and streamlined approach to managing modern network architectures.
Streaming telemetry protocols, particularly gRPC (Google Remote Procedure Call) and NETCONF (Network Configuration Protocol) with YANG data models, are at the core of Streaming Telemetry. Their primary focus is on real-time data streaming, providing a continuous flow of information that allows for instant updates. In dynamic network environments, these protocols play a pivotal role in meeting the demand for real-time insights.
NETCONF enables the configuration and management of network devices, while YANG data models provide a standardised framework for defining the structure and semantics of exchanged data. Together, they form a powerful combination for effective data representation and interpretation. gRPC facilitates remote procedure calls between applications. Its utilisation of Protocol Buffers for serialisation ensures a more compact and efficient representation of data, aligning seamlessly with the demands of dynamic network environments.
By understanding the role of these protocols in streaming telemetry, network engineers and architects can craft a comprehensive approach to embrace real-time insights and ensure the optimal performance of their networks.
As networks grow in complexity and scale, the need for accurate, timely, and standardised telemetry data becomes paramount. Let’s explore the advantages that standardised network telemetry brings, catering specifically to the Telecom sector:
Interoperability
Networks consist of a diverse array of devices and solutions from various vendors. Standardised telemetry protocols act as universal languages, enabling communication and data exchange between network elements. This interoperability not only facilitates integration but also empowers network engineers with the flexibility to choose best-of-breed solutions.
Real-time Insights
Timely insights into network performance can make the difference between smooth operations and service disruptions. Standardised telemetry protocols empower network engineers with real-time visibility into the intricate workings of the network. By providing instantaneous access to critical data points, these standards enable swift identification of potential issues, facilitating proactive problem resolution and enhancing overall network resilience. Telcos need this to meet the high expectations of their consumers.
Scalability
Telecom networks are constantly scaling to accommodate the increasing demands of users and applications. Standardised network telemetry plays an enabling role in this scalability. Whether it's the addition of new devices, increased data volumes, or expanded service offerings, standardised protocols ensure that telemetry solutions can grow in tandem, mitigating the challenges associated with network expansion.
Consistency
Standardised telemetry protocols establish a uniform set of rules and formats, ensuring a consistent approach to data acquisition across the entire network. This consistency streamlines the monitoring process and facilitates more accurate analysis and long-term planning. With a solid foundation of reliable data, network engineers can make informed decisions and maintain a high level of service quality.
Security
Standardised protocols bring a level of security assurance by incorporating industry-best practices for data integrity and confidentiality. By adhering to established standards, telecom organisations can fortify their networks against potential vulnerabilities and unauthorised access, safeguarding sensitive telemetry data and ensuring the integrity of their operations.
Network Telemetry protocols and standards enable us to understand what happens in our Network Infrastructure. That being said, in an attempt to capture comprehensive insights on everything, it can sometimes lead to an overwhelming influx of data. The sheer volume can strain network resources, making it difficult for engineers to extract meaningful insights in a timely manner to avoid service disruptions.
Recognising the need for flexibility, OptOSS AI incorporates an adaptive telemetry framework. This framework seamlessly integrates with various standardised protocols, accommodating the diverse range of devices within your network through the implementation of specific Knowledge Packs. The adaptability ensures that the telemetry solution remains effective even as the network evolves and expands.
The integration of OptOSS AI with network telemetry protocols and standards is a marriage of necessity and innovation. Network telemetry protocols provide the raw data necessary for OptOSS AI to work its magic, while the AI-driven insights from OptOSS AI enhance the value of the telemetry data.
In the journey towards standardised network telemetry, OptOSS AI emerges as a transformative ally for Telecoms. The convergence of OptOSS AI with standardised telemetry empowers Telecom networks with proactive insights, predictive analytics, and unparalleled control.
As the industry embraces the advantages of standardisation, OptOSS AI stands at the forefront, ready to propel Telecom networks into a future of heightened intelligence, efficiency, and adaptability.
Contact us to start this transformative journey, where standardisation meets innovation, and networks thrive in an era of unparalleled connectivity!
P.S. In upcoming articles, we will explore a range of topics including network management systems, advanced network frameworks, and the integration of telemetry protocols for comprehensive network intelligence and security. Stay tuned to discover how these innovations can enhance your network's performance and resilience!
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