Subject Mapping and Traffic Shaping

Supported since NATS Server version 2.2

Subject mapping is a very powerful feature of the NATS server, useful for canary deployments, A/B testing, chaos testing, and migrating to a new subject namespace.

The mappings stanza can occur at the top level to apply to the global account or be scoped within a specific account.

mappings = {
# Simple direct mapping. Messages published to foo are mapped to bar.
foo: bar
# remapping tokens can be done with $<N> representing token position.
# In this example bar.a.b would be mapped to baz.b.a.
bar.*.*: baz.$2.$1
# You can scope mappings to a particular cluster
foo.cluster.scoped : [
{ destination: bar.cluster.scoped, weight:100%, cluster: us-west-1 }
# Use weighted mapping for canary testing or A/B testing. Change dynamically
# at any time with a server reload.
myservice.request: [
{ destination: myservice.request.v1, weight: 90% },
{ destination: myservice.request.v2, weight: 10% }
# A testing example of wildcard mapping balanced across two subjects.
# 20% of the traffic is mapped to a service in QA coded to fail.
myservice.test.*: [
{ destination: myservice.test.$1, weight: 80% },
{ destination:$1, weight: 20% }
# A chaos testing trick that introduces 50% artificial message loss of
# messages published to foo.loss
foo.loss.>: [ { destination: foo.loss.>, weight: 50% } ]

Simple Mapping

The example of foo:bar is straightforward. All messages the server receives on subject foo are remapped and can be received by clients subscribed to bar.

Subject Token Reordering

Wildcard tokens may be referenced via $<position>. For example, the first wildcard token is $1, the second is $2, etc. Referencing these tokens can allow for reordering.

With this mapping:

bar.*.*: baz.$2.$1

Messages that were originally published to bar.a.b are remapped in the server to baz.b.a. Messages arriving at the server on would be mapped to, and so forth.

Weighted Mappings for A/B Testing or Canary Releases

Traffic can be split by percentage from one subject to multiple subjects. Here's an example for canary deployments, starting with version 1 of your service.

Applications would make requests of a service at myservice.requests. The responders doing the work of the server would subscribe to myservice.requests.v1. Your configuration would look like this:

myservice.requests: [
{ destination: myservice.requests.v1, weight: 100% }

All requests to myservice.requests will go to version 1 of your service.

When version 2 comes along, you'll want to test it with a canary deployment. Version 2 would subscribe to myservice.requests.v2. Launch instances of your service (don't forget about queue subscribers and load balancing).

Update the configuration file to redirect some portion of the requests made to myservice.requests to version 2 of your service. In this case we'll use 2%.

myservice.requests: [
{ destination: myservice.requests.v1, weight: 98% },
{ destination: myservice.requests.v2, weight: 2% }

You can reload the server at this point to make the changes with zero downtime. After reloading, 2% of your requests will be serviced by the new version.

Once you've determined Version 2 stable switch 100% of the traffic over and reload the server with a new configuration.

myservice.requests: [
{ destination: myservice.requests.v2, weight: 100% }

Now shutdown the version 1 instances of your service.

Traffic Shaping in Testing

Traffic shaping is useful in testing. You might have a service that runs in QA that simulates failure scenarios which could receive 20% of the traffic to test the service requestor.

myservice.requests.*: [
{ destination: myservice.requests.$1, weight: 80% },
{ destination:$1, weight: 20% }

Artificial Loss

Alternatively, introduce loss into your system for chaos testing by mapping a percentage of traffic to the same subject. In this drastic example, 50% of the traffic published to foo.loss.a would be artificially dropped by the server.

foo.loss.>: [ { destination: foo.loss.>, weight: 50% } ]

You can both split and introduce loss for testing. Here, 90% of requests would go to your service, 8% would go to a service simulating failure conditions, and the unaccounted for 2% would simulate message loss.

myservice.requests: [
{ destination: myservice.requests.v3, weight: 90% },
{ destination:, weight: 8% }
# the remaining 2% is "lost"

Note: Subject Mapping and Traffic Shaping are also supported in the NATS JWT model, although currently only through the JWT API. nsc tooling support for subject mapping is coming soon.