How Time Series Data Empowers Telcos to Stay Competitive
The telecommunications industry is undergoing rapid change as a handful of new technologies and government actions change the underlying business landscape and create space for new companies to innovate and disrupt the established players.
In this article, we will take a look at some of the biggest problems facing modern telecommunications companies, look at some potential solutions to these problems and how these solutions are being used in the real world by major companies.
The Changing Telecommunications Landscape
The problems businesses face depend on where they are in their life cycle. For established companies in the telecommunications space, the biggest challenge is having to deal with maintaining their legacy infrastructure while also modernizing and moving toward the future.
This modernization process is made even more important due to many governments across the world pushing regulations meant to increase competition in the telecommunications industry to drive better service for customers. Established telecommunications companies won’t be able to rely on captive customers to generate steady revenue in the future. They will need to compete head-on with new competitors.
Let’s take a look at some of the biggest challenges these companies need to address:
- Reliability is more important than ever: A huge number of people are still working remotely and need reliable internet to be productive. This kind of reliability will require smarter networks with better monitoring to identify issues quickly and automation to resolve these issues.
- More devices generating more data: More hardware is needed to handle the increased number of people connected to the internet. This means more data is being generated to monitor all these devices, which may pose a challenge for legacy tools storing and analyzing data.
- Rise of edge computing: Consumers want lower latency and better performance. Different forms of edge computing are rising to help deliver. But edge computing brings about even more complexity to networks and software architecture, which needs to be accounted for to maintain reliability.
- Supporting legacy hardware: Dealing with different hardware communicating over different protocols and in some cases using vendor-specific tools slows down companies.
- Disruptive technologies: New technology like Starlink is making it easier for companies to negate the infrastructure advantages of established companies. T-Mobile for example recently partnered with Starlink to provide cellular network access to people in areas that was previously not possible due to cost. 5G is another new technology that will have a major impact on telcos due to the complexity of rolling out and managing all the new required hardware.
- Security: Securing these networks is more critical than ever. It seems like almost every week we learn about a new major security breach. Being able to reliably monitor networks in real time to detect potential security breaches is essential.
How Time Series Databases Can Help Solve These Problems
Many of the issues discussed above constitute problems related to time series data. Monitoring applications, anomaly detection, cybersecurity and tracking network reliability — all of these rely on different forms of time series data. Having a specialized tool for storing and analyzing this data is one way to make the challenges easier for telecommunications companies to face. Let’s look at a few of these problems and how real-world companies are using time series databases to solve them.
Performance, Scalability and Reliability
The most basic benefit of a time series database (TSDB) for telecom companies is the ability to store and query their data more efficiently. With the rapid increase in the number of devices generating data, to deliver more reliable services, companies require finer granularity like being able to collect metrics every second instead of every minute.
Cisco, for example, uses InfluxDB to monitor its internal SaaS solution and provides real-time monitoring for end users by providing alerting based on things like uptime, loading speed and availability. Cisco also uses InfluxDB to monitor its network infrastructure for its annual Cisco Live conference to make sure in-person users have stable internet access and that virtual attendees have reliable video streams.
Vonage is another company using time series databases to provide reliable service. Vonage provides a contact center solution for business customers with a 99.999% uptime guarantee. To make sure it hits this number, it relies on InfluxDB to ensure real-time visibility into its infrastructure and millisecond resolution into its metrics. This type of analysis would be very challenging without a specialized database designed to work with this type of data.
Network to Code works with enterprise customers who are trying to modernize their network infrastructure. A huge part of this is getting visibility into that infrastructure, which is a challenge when dealing with many different vendor-specific hardware and network protocols. It leans heavily on Telegraf to transform and store this data with minimal effort. Many time series databases will also provide additional native integrations for ingesting data without having to deal with external services or write custom code.
To maintain high service-level agreements (SLAs) for customers, automation is mandatory. Humans simply can’t react quickly enough in many situations, especially when problems are complex across huge networks.
Comcast uses a time series database to analyze a number of performance metrics across its infrastructure to not only improve the reliability of its software but also to identify potential cost savings by forecasting hardware requirements based on the metrics it collects.
Red Hat was also able to automate a number of things to become more efficient and reliable. Red Hat has hardware spread across 60 different locations, with over 1,600 devices and 14,000 network interfaces. Red Hat was able to automate things like compliance reporting, anomaly detection and capacity planning by taking advantage of the benefits of a time series database.
Time series databases are often used for cybersecurity by tracking events and looking for anomalies by comparing recent data to historical data. If your time series database is open source, you can avoid exposing sensitive data to potential network risk by storing data on-premises to further reduce the risk of a security breach. For less sensitive data, some TSDBs give you the option of replicating data to other storage locations. This gives you the benefit of low latency processing at the edge and the scalability and reliability of the cloud.
There’s a lot of change going on in the telecommunication industry from a technology, business and regulatory perspective. From the technology perspective at least, a few major problems can be solved by using new technologies like time series databases to make companies more reliable, efficient and productive.