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: myservice.test.fail.$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 bar.one.two
would be mapped to baz.two.one
, 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: myservice.requests.fail.$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: myservice.requests.v3.fail, 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.