Understanding Observability in Cloud Native Voice Networks
As we navigate through the complexities of modern network management, we find ourselves in a situation reminiscent of the Scientific Revolution of the 17th century. Just as that era marked a profound shift in knowledge and understanding, today’s telecom industry is experiencing a similar transformation. The evolution of cloud native networks has generated an overwhelming amount of operational data, akin to the data collection struggles faced by early scientists. However, unlike the past, the key to harnessing this data lies in observability.
Observability refers to the ability to understand the internal state of a system through its external outputs. For telecom operators, embracing observability means effectively collecting and analyzing data to ensure network reliability and optimize troubleshooting processes. In this article, we will explore how observability enhances operations in cloud native voice networks.
The Shift from Probes to Microservices
Traditionally, telecoms relied heavily on physical probes to monitor network performance. However, as networks evolved, the sheer volume of data generated made this approach insufficient. Instead of adding more probes, which would only complicate the data analysis, telecom operators are turning towards observability and analytics.
In a cloud native architecture, observability can be integrated directly into cloud native functions (CNFs) as microservices. This shift allows operators to monitor their networks more dynamically and effectively. Unlike older systems that focused on external north-to-south observability, cloud native environments require an internal east-to-west approach. This enables more granular insights into the system’s performance and health.
For instance, consider the nature of metrics collected from microservices. They are often dynamic and ephemeral, meaning that traditional sampling methods—such as collecting data every 5 or 15 minutes—may miss crucial real-time anomalies. In a cloud native environment, continuous telemetry and analysis are vital for capturing fleeting anomalies, particularly when troubleshooting issues like a call processed by a Session Border Controller (SBC) that no longer exists.
Benefits of Cloud Native Observability and Analytics
Implementing a cloud native observability and analytics solution presents several significant advantages for telecom operators, especially those transitioning from older technologies like 4G to 5G. A cloud native architecture allows for scalability: solutions can be built and deployed once and then adjusted as needed to handle varying loads.
One of the primary benefits of adopting cloud native observability is the enhanced ability to detect fraud patterns and cyberattacks. Improved data collection and analysis capabilities enable telecoms to respond more swiftly to threats, such as telephony denial-of-service attacks. This proactive approach to network security is vital in today’s digital landscape.
Ribbon Analytics Platform: A Case Study
Ribbon Communications has been at the forefront of developing cloud native analytics solutions. Their Ribbon Analytics platform was designed with observability in mind, allowing telecom operators to collect data from various network elements intelligently. This platform provides users with the flexibility to determine what data to capture and how to process it. For example, operators can set specific triggers for data capture based on network events, focusing on the most relevant data rather than sifting through enormous datasets.
Included within the Ribbon Analytics platform are several tools designed for specific observability tasks. The Muse Network Planner aids in network capacity planning by analyzing data trends. Meanwhile, the Discover tool assesses the quality of experience in voice networks, ensuring that operators can maintain high service standards. Additionally, the Most Probable Cause tool employs machine learning algorithms to sift through vast datasets, enhancing troubleshooting efficiency.
Future-Proofing Operations with Cloud Native Observability
The rapid advancement of technology in the telecom industry necessitates a focus on future-proof operations. By adopting cloud native observability, telecommunications companies can achieve dynamic scalability and improve operational efficiency. This approach facilitates quick failure detection and remedial actions, significantly reducing Mean Time to Repair (MTTR) and enhancing the quality of service offered to consumers.
Leading telecoms are increasingly leveraging machine learning algorithms to improve fraud detection, troubleshooting, and anomaly recognition. By developing best practices around network analytics, based on robust data science, they are creating open architectures that integrate artificial intelligence into their operations, further optimizing network performance.
As telecom operators continue to embrace cloud native observability, they position themselves to offer smoother, more efficient services similar to those of web-scale companies. The transition to cloud native solutions is not merely an upgrade; it is a strategic move towards gaining a competitive edge in a rapidly evolving market. By prioritizing observability, telecom operators can ensure they remain at the forefront of industry advancements and deliver superior service to their customers.
In conclusion, the journey towards enhanced operations in cloud native voice networks is just beginning. Telecom operators must continue to invest in observability and analytics to navigate the complexities of modern network management effectively. By doing so, they will not only improve operational reliability but also enhance their ability to respond to challenges swiftly and efficiently.
Source Article:https://ribboncommunications.com/company/media-center/blog/how-does-observability-enhance-operations-cloud-native-voice-networks
