SD-WAN analytics is the process of collecting and analyzing data generated by a software defined wide area network, or SD-WAN.
As businesses increasingly shift from traditional WANs to SD-WANs, the ability to monitor networks using SD-WAN analytics is essential for achieving the network performance and security goals that SD-WANs are supposed to enable.
To understand the role played by SD-WAN analytics in modern network operations, it’s first necessary to understand the goals that businesses seek to achieve when shifting from WANs to SD-WANs.
One of the main reasons why organizations migrate from WANs (which use physical hardware to manage network connections and traffic) to SD-WANs is that modern network operations often involve complex, distributed applications that are hosted in the cloud. Compared to traditional monolithic applications that run inside a local data center, modern applications generate more connections and much higher volumes of traffic. Some of the most common reasons why include:
Although it’s technically possible to manage complex networking requirements like these using a WAN, SD-WANs are more efficient and easier to work with because they allow teams to define complex networking rules using software, rather than having to configure physical devices to handle each facet of network operations. In addition, because a single SD-WAN can typically manage all of an organization’s networking requirements through a single interface, SD-WANs simplify administration and help to centralize network monitoring.
Because WANs are usually used in cases where network operations are simple, there is typically relatively little data that you can collect and analyze from a WAN. You can monitor basic metrics like packet loss and latency for your applications as a whole, and you may be able to analyze WAN performance data on a per-user or per-location basis. Beyond this, however, there is little granularity or nuance associated with traditional WAN monitoring.
When you manage your network using an SD-WAN, however, end-to-end network monitoring is a paramount priority for ensuring that SD-WANs can adequately handle the complex networking configurations that they are intended to support. Without carefully monitoring your SD-WAN, you may fail to detect performance issues such as high latency within traffic between two cloud services or improper network load balancing across redundant cloud regions.
In other words, SD-WAN analytics is the only way to know that your SD-WAN is actually achieving what you intend it to achieve. Without deep visibility into the health of your SD-WAN via analytics, you run the risk of investing in an SD-WAN that fails to deliver the agility and reliability that distinguish SD-WANs from conventional WANs.
SD-WAN analytics can also play a role in security by exposing unusual traffic patterns or other anomalies that may be signs of a breach. Although complete network security requires much more than just SD-WAN analytics, the latter offers one means of detecting security issues that you may otherwise miss.
No two networks are identical, and SD-WAN analytics solutions should always be tailored to the architecture of your organization’s SD-WAN, as well as the monitoring goals that you prioritize. However, in general, you should expect any SD-WAN solution to deliver a core set of features, including:
While the core use case for SD-WAN analytics involves monitoring an SD-WAN once it is up and running, an additional role that SD-WAN analytics can play is helping teams to validate network configuration plans before they are implemented.
Admins can define the requirements that an SD-WAN needs to meet, such as the bandwidth and latency baselines it needs to ensure for different transport circuits. Then, they can deploy SD-WAN analytics tools to help assess the ability of their proposed SD-WAN configuration to meet those requirements.
Using SD-WAN analytics to test configurations before you roll out an SD-WAN (or before you make changes to an existing SD-WAN configuration) helps avoid unforeseen performance or security issues and reduces the number of networking problems that impact live production environments.