5. Hystrix Timeouts And Ribbon Clients

When using Hystrix commands that wrap Ribbon clients you want to make sure your Hystrix timeout is configured to be longer than the configured Ribbon timeout, including any potential retries that might be made. For example, if your Ribbon connection timeout is one second and the Ribbon client might retry the request three times, than your Hystrix timeout should be slightly more than three seconds.

5.1 How to Include the Hystrix Dashboard

To include the Hystrix Dashboard in your project, use the starter with a group ID of org.springframework.cloud and an artifact ID of spring-cloud-starter-netflix-hystrix-dashboard. See the Spring Cloud Project page for details on setting up your build system with the current Spring Cloud Release Train.

To run the Hystrix Dashboard, annotate your Spring Boot main class with @EnableHystrixDashboard. Then visit /hystrix and point the dashboard to an individual instance’s /hystrix.stream endpoint in a Hystrix client application.

[Note]Note

When connecting to a /hystrix.stream endpoint that uses HTTPS, the certificate used by the server must be trusted by the JVM. If the certificate is not trusted, you must import the certificate into the JVM in order for the Hystrix Dashboard to make a successful connection to the stream endpoint.

5.2 Turbine

Looking at an individual instance’s Hystrix data is not very useful in terms of the overall health of the system. Turbine is an application that aggregates all of the relevant /hystrix.stream endpoints into a combined /turbine.stream for use in the Hystrix Dashboard. Individual instances are located through Eureka. Running Turbine requires annotating your main class with the @EnableTurbine annotation (for example, by using spring-cloud-starter-netflix-turbine to set up the classpath). All of the documented configuration properties from the Turbine 1 wiki apply. The only difference is that the turbine.instanceUrlSuffix does not need the port prepended, as this is handled automatically unless turbine.instanceInsertPort=false.

[Note]Note

By default, Turbine looks for the /hystrix.stream endpoint on a registered instance by looking up its hostName and port entries in Eureka and then appending /hystrix.stream to it. If the instance’s metadata contains management.port, it is used instead of the port value for the /hystrix.stream endpoint. By default, the metadata entry called management.port is equal to the management.port configuration property. It can be overridden though with following configuration:

eureka:
  instance:
    metadata-map:
      management.port: ${management.port:8081}

The turbine.appConfig configuration key is a list of Eureka serviceIds that turbine uses to lookup instances. The turbine stream is then used in the Hystrix dashboard with a URL similar to the following:

https://my.turbine.server:8080/turbine.stream?cluster=CLUSTERNAME

The cluster parameter can be omitted if the name is default. The cluster parameter must match an entry in turbine.aggregator.clusterConfig. Values returned from Eureka are upper-case. Consequently, the following example works if there is an application called customers registered with Eureka:

turbine:
  aggregator:
    clusterConfig: CUSTOMERS
  appConfig: customers

If you need to customize which cluster names should be used by Turbine (because you do not want to store cluster names in turbine.aggregator.clusterConfig configuration), provide a bean of type TurbineClustersProvider.

The clusterName can be customized by a SPEL expression in turbine.clusterNameExpression with root as an instance of InstanceInfo. The default value is appName, which means that the Eureka serviceId becomes the cluster key (that is, the InstanceInfo for customers has an appName of CUSTOMERS). A different example is turbine.clusterNameExpression=aSGName, which gets the cluster name from the AWS ASG name. The following listing shows another example:

turbine:
  aggregator:
    clusterConfig: SYSTEM,USER
  appConfig: customers,stores,ui,admin
  clusterNameExpression: metadata['cluster']

In the preceding example, the cluster name from four services is pulled from their metadata map and is expected to have values that include SYSTEM and USER.

To use the default cluster for all apps, you need a string literal expression (with single quotes and escaped with double quotes if it is in YAML as well):

turbine:
  appConfig: customers,stores
  clusterNameExpression: "'default'"

Spring Cloud provides a spring-cloud-starter-netflix-turbine that has all the dependencies you need to get a Turbine server running. To add Turbine, create a Spring Boot application and annotate it with @EnableTurbine.

[Note]Note

By default, Spring Cloud lets Turbine use the host and port to allow multiple processes per host, per cluster. If you want the native Netflix behavior built into Turbine to not allow multiple processes per host, per cluster (the key to the instance ID is the hostname), set turbine.combineHostPort=false.

5.2.1 Clusters Endpoint

In some situations it might be useful for other applications to know what custers have been configured in Turbine. To support this you can use the /clusters endpoint which will return a JSON array of all the configured clusters.

GET /clusters. 

[
  {
    "name": "RACES",
    "link": "http://localhost:8383/turbine.stream?cluster=RACES"
  },
  {
    "name": "WEB",
    "link": "http://localhost:8383/turbine.stream?cluster=WEB"
  }
]

This endpoint can be disabled by setting turbine.endpoints.clusters.enabled to false.

5.3 Turbine Stream

In some environments (such as in a PaaS setting), the classic Turbine model of pulling metrics from all the distributed Hystrix commands does not work. In that case, you might want to have your Hystrix commands push metrics to Turbine. Spring Cloud enables that with messaging. To do so on the client, add a dependency to spring-cloud-netflix-hystrix-stream and the spring-cloud-starter-stream-* of your choice. See the Spring Cloud Stream documentation for details on the brokers and how to configure the client credentials. It should work out of the box for a local broker.

On the server side, create a Spring Boot application and annotate it with @EnableTurbineStream. The Turbine Stream server requires the use of Spring Webflux, therefore spring-boot-starter-webflux needs to be included in your project. By default spring-boot-starter-webflux is included when adding spring-cloud-starter-netflix-turbine-stream to your application.

You can then point the Hystrix Dashboard to the Turbine Stream Server instead of individual Hystrix streams. If Turbine Stream is running on port 8989 on myhost, then put http://myhost:8989 in the stream input field in the Hystrix Dashboard. Circuits are prefixed by their respective serviceId, followed by a dot (.), and then the circuit name.

Spring Cloud provides a spring-cloud-starter-netflix-turbine-stream that has all the dependencies you need to get a Turbine Stream server running. You can then add the Stream binder of your choice — such as spring-cloud-starter-stream-rabbit.

Turbine Stream server also supports the cluster parameter. Unlike Turbine server, Turbine Stream uses eureka serviceIds as cluster names and these are not configurable.

If Turbine Stream server is running on port 8989 on my.turbine.server and you have two eureka serviceIds customers and products in your environment, the following URLs will be available on your Turbine Stream server. default and empty cluster name will provide all metrics that Turbine Stream server receives.

https://my.turbine.sever:8989/turbine.stream?cluster=customers
https://my.turbine.sever:8989/turbine.stream?cluster=products
https://my.turbine.sever:8989/turbine.stream?cluster=default
https://my.turbine.sever:8989/turbine.stream

So, you can use eureka serviceIds as cluster names for your Turbine dashboard (or any compatible dashboard). You don’t need to configure any properties like turbine.appConfig, turbine.clusterNameExpression and turbine.aggregator.clusterConfig for your Turbine Stream server.

[Note]Note

Turbine Stream server gathers all metrics from the configured input channel with Spring Cloud Stream. It means that it doesn’t gather Hystrix metrics actively from each instance. It just can provide metrics that were already gathered into the input channel by each instance.