What is RUM data?
Contrary to what you might think, RUM data isn’t a performance indicator for Captain Morgan, Cuban tourism, or a Disney film franchise.
Real User Monitoring (RUM) data is information about how people interact with online applications and services. Think of it like an always-on, real-time survey of what your users experience online.
RUM data is a critical component of optimizing the performance of online applications and services. By analyzing information on where users are going and what they experience, companies can proactively deal with misconfigurations, slow connections, and other indicators of service quality.
Are there alternatives to RUM data?
Why “real”? Does that imply that there are “fake” user metrics as well?
Actually, yes! Synthetic data is where algorithms and simulations attempt to create the experience of an “average” user based on representative data samples.
Plenty of analytics companies use synthetic data to analyze the performance of online applications and services. The main reason is cost: it takes a fair amount of resources in the form of compute and configurations to capture RUM data in real-time.
Synthetic data is a statistical representation of reality. That might work well for training AI, but it’s far less reliable in detecting performance anomalies in networks and applications. By definition, anomalous network performance is unpredictable. There’s really no substitute for real user experiences when it comes to optimizing real-world applications and services.
How does RUM data improve application performance?
NS1 uses RUM data to inform DNS routing decisions through its Pulsar active traffic steering product. The RUM data acts as a monitor, gathering information from online applications and services. By comparing RUM data from multiple sources, Pulsar can calculate the best option to resolve a DNS query.
Some network service providers use RUM data to inform individual traffic steering decisions. NS1 adds a unique layer of functionality by stacking those decisions, forming a customizable chain. With Pulsar, you don’t have to choose between optimizing for things like the user’s ISP and their geographical location. You can use RUM data to take the status of both factors into account, prioritizing them based on the logic you create.
This delivers business value in several ways:
Pulsar improves performance by choosing the fastest connection to a particular geography, the fastest available CDN, or other metrics you define.
Pulsar improves reliability by choosing connections to services that are the most available, avoiding CDNs or clouds which may be down or experiencing the deprecated performance.
Pulsar reduces costs by choosing the CDN or cloud provider with the lowest contracted rate at any particular time.
RUM data provides the real-time information needed to make these decisions at network speed, optimizing applications and services in a highly granular, customizable way.
How is RUM data collected and processed?
For those who like to geek out on the details, here’s a technical overview of how NS1 gathers and analyzes RUM data to inform traffic steering decisions.
It all starts with the configuration of a web property - whether that’s an application, service, or other content delivery mechanism. NS1 adds javascript tags to that web property which collect information about inbound user traffic.
When an end-user visits the web property, that javascript tag performs a series of tests that collect data on performance and availability.
Those test results are then sent to NS1 for analysis. Using a sophisticated hierarchy of equations and processing techniques, NS1 focuses on relevant data elements to draw conclusions about performance and availability.
Those results are then pushed back into NS1’s Pulsar engine and used for traffic steering decisions. Pulsar receives new traffic steering instructions roughly every five minutes, ensuring up-to-date results that reflect constantly changing internet conditions (sometimes referred to as “internet weather”).
Learn more about what you can do with RUM data using NS1 Pulsar.
