While RFC9199 (are we really in the 9000’s?) is targeted at large-scale DNS deployments–specifically root zone operators–so it might seem the average operator won’t find a lot of value here.
This is, however, far from the truth. Every lesson we’ve learned in deploying large-scale DNS root servers applies to any other large-scale user-facing service. Internally deployed DNS recursive servers are an obvious instance, but the lessons here might well apply to a scheduling, banking, or any other multi-user application accessed from a lot of places by a lot of different users. There are some unique points in DNS, such as the relatively slower pace of database synchronization across nodes, but the network-side lessons can still be useful for a lot of applications.
What are those lessons?
First, using anycast dramatically improves performance for these kinds of services. For those who aren’t familiar with the concept, anycase turns an IP address into a service identifier. Any host with a copy (or instance) or a given service advertises the same address, causing the routing table to choose the (topologically) closest instance of the service. If you’re using anycast, traffic destined to your service will automatically be forwarded to the closest server running the application, providing a kind of load sharing among multiple instances through routing. If there are instances in New York, California, France, and Taipei, traffic from users in North Carolina will be routed to New York and traffic from users in Singapore will be routed to Taipei.
You can think of an anycast address something like a cell tower; users within a certain desintance will be “captured” by a particular instance. The more copies of the service you deploy, the smaller the geographic region the service will support. Hence you can control the number of users using a particular copy of the service by controlling the number and location of service copies.
To understand where and how to deploy service instances, create anycast catchment maps. Again, just like a wifi signal coverage map, or a cellphone tower coverage map, it’s important to understand which users will be directed to which instances. Using a catchment map will help you decide where new instances need to be deployed, which instances need the fastest links and hardware, etc. The RIPE ATLAS pobes and looking glass servers are good ways to start building such a map. If the application supports a large number of users, you might be able to convince the application developer to include some sort of geographic information in requests to help build these maps.
Third, when deploying service instance, pay as much attention to routing and connectivity as you do the number of instances deployed. As the authors note, sometimes eight instances will provide the same level of service as several thousand instances. The connectivity available into each instance of the service–bandwidth, delay, availability, etc.–still has a huge impact on service speed.
Fourth, reduce the speed at which the database needs to be synchronized where possible. Not every piece of information needs to be synchronized at the same rate. The less data being synchronized, the more consistent the view from multiple users is going to be.
RFC9199 is well worth reading, even for the average network engineer.