How does observability enhance operations in cloud native voice networks?
The 17th century saw the onset of the Scientific Revolution. It was a time of knowledge explosion. During this time, scientific practices were still evolving, with no universally accepted protocols for data collection and analysis. Individuals documented any observation, resulting in the collection of massive amounts of information, but much of it was hard to leverage to draw useful conclusions. The development of the scientific method provided a common approach to capturing and analyzing data.
Today, we are encountering a similar issue with the evolution of network management and cloud native networks. These modern networks have evolved to report every operational event. There is an overwhelming amount of fine-grained, event-driven data, making it difficult to analyze efficiently. Simultaneously, there is insufficient “important” data being acted on in the network due to a lack of consistent mechanisms to capture and analyze it. Today, network administrators are turning to observability and analytics, much as their predecessors turned to the Scientific Methods for data collection and analysis.
Moving from probes to microservices
Today’s telcos are sitting on mountains of data but are unable to mine it effectively due to limitations in their technology. Putting more probes in the network isn’t the answer, especially as the amount of data in the network grows exponentially. Instead, the answer lies in observability and analytics. Observability is comprehending the internal state of a complex system by gathering and analyzing its data to enable proactive measures to ensure reliability and efficient troubleshooting.
In a cloud native architecture, telcos can embed observability into their cloud native functions (CNFs) as a microservice rather than building bespoke sentries around those network functions using physical probes. The cloud native environment differs significantly from traditional settings, requiring more of an internal east-to-west observability within the server rather than the external north-to-south observability of probes. Which isn’t to say that physical probes don’t have a part to play in network observability, but it’s a diminished role that focuses mostly on network traffic after it leaves the server.
Metrics and statistics collected from microservices are dynamic and ephemeral in nature. The traditional approach of sampling every 5 or 15 minutes isn’t granular enough to catch anomalies occurring in real-time. Let’s take a look at an example – how do you troubleshoot a call processed by an SBC instance that no longer exists? You can capture these fleeting anomalies based on accurate data by continuous sampling via telemetry and analysis in a cloud native environment. A cloud native SBC is comprised of multiple microservices that can be started, stopped, and moved across servers or clusters during their lifetime. Observability functions provide the infrastructure to collect and categorize the data, while analytics enables telcos to drill down into the data and troubleshoot the call even though the SBC instance no longer exists.
What are the benefits of cloud native observability and analytics?
All observability tools need to be able to scale up and down, which is where a cloud native architecture enters the picture. With a cloud native solution, you build and implement it once and then can scale it up or down as needed.
Deploying a cloud native observability and analytics solution has clear advantages for telcos. For mobile networks transitioning from 4G to 5G, a cloud native solution provides deeper insights into how 4G and 5G mobile calls are handled in the network. Another advantage is better detection of fraud patterns and cyberattacks (e.g., telephony denial-of-service) due to the improved ability to collect and analyze data.
Ribbon Analytics platform was originally built on a cloud native platform years before cloud native was an accepted standard. In fact, because many of Ribbon’s early customers were still using virtual machines, we often had to provide a Kubernetes architecture alongside our solution. The advantage to being ahead of the curve is that our solution now runs seamlessly in a hybrid virtual/cloud environment.
Ribbon Analytics Platform
At Ribbon, we created a cloud native analytics platform that intelligently collects data from a variety of network elements to improve network observability. Our solution lets you decide what to capture and how to handle that data, e.g., setting triggers for data capture based on specific network events. In this way, you can focus on the five percent of the data that is meaningful to the event (e.g., a service failure) instead of sifting through 100 percent of your data.
Included in Ribbon’s platform is a set of tools that focus on specific aspects of observability. Muse Network Planner, for example, collects and analyzes data for network capacity planning. Our Discover tool analyzes the voice network’s quality of experience. Most Probable Cause leverages machine learning algorithms to search through large data sets and improve network troubleshooting.
Embracing Cloud Native Observability for Future-Proof Operations
The industry is rapidly advancing towards a future-proof goal of dynamic scalability, ensuring ease and efficiency in operations through cloud native observability. This approach enables swift failure detection and remedial actions, significantly reducing Mean Time to Recover (MTTR) and delivering high-quality service to consumers. Ribbon’s cloud architecture integrates this intelligence, eliminating the need for third-party software. The observability layer seamlessly feeds data to Telco backends for deeper analysis.
With cloud native solutions, the industry is closer than ever to achieving a resilient architecture. Leading telcos are leveraging machine learning algorithms to enhance fraud detection, troubleshooting, and anomaly detection. They are developing best practices around network analytics based on robust data science and creating open architectures that facilitate the integration of artificial intelligence to optimize network operations.
Ribbon’s cloud native observability empowers enterprises and service providers to transition to smoother, more efficient, and faster operations, akin to web-scale companies. If you’re ready to gain a competitive edge with this transition, we invite you to connect with us.
