Configuring private RUM data collection
IBM NS1 Connect®'s real user monitoring (RUM) solution enables intelligent and dynamic DNS traffic routing based on real-time performance and availability metrics collected from shared or private resources. Data collected from these resources is ingested by the IBM NS1 Connect® platform, which can be used to inform how the platform distributes traffic across your application endpoints and services.
While the turnkey solution includes collecting community data from a pool of top CDNs and cloud services, users can configure RUM data collection from private resources using one of two methods:
- Option A: Collect private data via embedded JavaScript tag
- Embed a JavaScript tag on your web properties to measure your private application servers, web servers, or CDNs. The JavaScript executes asynchronously in the background with each page load to collect RUM data directly from your user "eyeballs" or impressions.
- Option B: Beaconing data via gRPC or HTTP
- If you are already collecting RUM data from your endpoints, you can beacon the telemetry to the IBM NS1 Connect® platform via API. This method allows you to "bring your own" (BYO) data from your CDN footprint or any combination of servers, data centers, or cloud providers. Beaconed data must contain a performance-based measurement, such as latency, to reference when routing.
Depending on your private data collection method, you will create RUM-based applications and jobs corresponding to a resource, specifying the job type (JavaScript or bulk beaconing) and other configuration settings.
Before you begin
Consult with the IBM NS1 Connect® support team or your dedicated support engineer for guidance on the best data collection method(s) for your organization and to overview the configuration process. If you plan to use the JavaScript tag for implementation, the NS1 support team will provide you with a custom JS tag.
Procedure
Refer to the relevant instructions below depending on the method you want to use for configuring private data collection.