Kafka and Zookeeper
Preferring local clusters in Frontend and Consumers
To ensure the lowest possible response times, it is recommended to connect to local zookeeper and kafka clusters. In the configuration, you can specify the properties of multiple clusters. For example:
consumer:
datacenter:
name:
source: "ENV"
env: "DC"
zookeeper:
clusters:
- datacenter: "dc-1"
connectionString: "zk-1:2181"
- datacenter: "dc-2"
connectionString: "zk-2:2181"
kafka:
clusters:
- datacenter: "dc-1"
brokerList: "kafka-1:9092"
- datacenter: "dc-2"
brokerList: "kafka-2:9092"
If you don't specify the {modulePrefix}.datacenter.name.source
property hermes will look for a cluster in properties with the datacenter: "dc"
property.
Hermes also supports retrieving information about the name of the datacenter based on an environment variable. All you have to do is specify
{modulePrefix}.datacenter.name.source
to ENV
just like above, and the name of variable {modulePrefix}.datacenter.name.env
in which the datacenter name is stored.
Zookeeper
Hermes uses Zookeeper as metadata store. It does not have to be the same Zookeeper as the one used by Kafka.
Option in Frontend/Consumers | Option in Management | Description | Default value |
---|---|---|---|
{modulePrefix}.zookeeper.clusters.[n].connectionString | storage.connectionString | Zookeeper connection string | localhost:2181 |
{modulePrefix}.zookeeper.clusters.[n].connectionTimeout | storage.connectTimeout | connection timeout in seconds | 10s |
{modulePrefix}.zookeeper.clusters.[n].maxRetries | storage.retryTimes | retry count when connection fails | 2 |
{modulePrefix}.zookeeper.clusters.[n].baseSleepTime | storage.retrySleep | time to wait between subsequent retries in seconds | 1s |
{modulePrefix}.zookeeper.clusters.[n].root | storage.pathPrefix | prefix for Hermes data (if not specified in connection string) | /hermes |
{modulePrefix}.zookeeper.clusters.[n].authorization.enabled | n/a | enable Zookeeper authorization | false |
{modulePrefix}.zookeeper.clusters.[n].authorization.scheme | storage.authorization.scheme | authorization scheme | digest |
{modulePrefix}.zookeeper.clusters.[n].authorization.user | storage.authorization.user | username | user |
{modulePrefix}.zookeeper.clusters.[n].authorization.password | storage.authorization.password | password | password |
Kafka
Single Kafka cluster
In simple case, Hermes is connected to just one Kafka cluster. Frontend and Consumers connect to Kafka to publish and pull messages. Management connects to Kafka to manage existing topics and initiate retransmissions.
Frontend and Consumers options:
Option | Description | Default value |
---|---|---|
kafka.broker.list | list of all brokers in the cluster (or at least some contact points); separated with ',' | localhost:9092 |
kafka.namespace | namespace is a prefix prepended to all Kafka topics and consumer groups used by Hermes | |
kafka.zookeeper.connect.string | [Consumers only] connection string to Kafka Zookeeper | localhost:2181 |
kafka.cluster.name | name of Kafka cluster (relevant only when connecting to multiple clusters) | primary |
Zookeeper connection specific options (retries etc) are read from Metadata Zookeeper options.
Management module can connect to multiple Kafka clusters at once (see section below), thus when specifying connection option is done per cluster. Simple configuration for single cluster looks following:
kafka:
defaultNamespace: // namespace shared by all clusters, default: <empty>
clusters:
-
clusterName: // name of cluster, can be any arbitrary string, default: primary
connectionString: // connection string to cluster Zookeeper, default: localhost:2181
Multiple Kafka and Zookeeper clusters
Hermes can be configured to publish and read messages to/from multiple Kafka clusters and to store metadata in multiple Zookeeper clusters. We use this feature on production environment where we have separated kafka clusters in different data centers. If Kafka in one DC fails, whole traffic can be routed to the second DC. This scenario assumes, that Kafka clusters hold different set of messages. There is no support for multiple clusters each holding the same copy of data.
This is the schematics of two data center architecture:
- there are specific Frontend and Consumers instances per cluster:
- each Frontend instance writes data to single cluster
- each Consumers instance reads data from single cluster
- each Management instance:
- connects to all Kafka clusters and keeps topics and subscriptions in-sync
- connects to all Zookeeper clusters and keeps metadata in-sync
Configuring Frontend and Consumers is easy: use configuration options from previous chapter to
connect to given clusters. Remember about specifying proper kafka.cluster.name
.
Since Management instances need to know all clusters, their configuration is bit more complex. Example configuration for the schematics provided above:
kafka:
clusters:
-
datacenter: dc1
clusterName: kafka_primary
connectionString: kafka-zookeeper:2181/clusters/dc1
-
datacenter: dc2
clusterName: kafka_secondary
connectionString: kafka-zookeeper:2181/clusters/dc2
storage:
pathPrefix: /run/hermes
clusters:
-
datacenter: dc1
clusterName: zk1
connectionString: metadata-zookeeper.dc1:2181
-
datacenter: dc2
clusterName: zk2
connectionString: metadata-zookeeper.dc2:2181
Multiple Hermes on single Kafka cluster
It’s also possible to run multiple Hermes clusters on a single Kafka cluster, e.g. to separate different test environments.
To do this, on each Hermes cluster you have to provide different value for:
* kafka.namespace
property in Frontend and Consumers. In Management it’s named kafka.defaultNamespace
and also need to be changed.
* zookeeper.root
property in Frontend and Consumers if you use the same Zookeeper cluster for all Hermes clusters.
In Management it’s named storage.pathPrefix
and also need to be changed.
kafka.namespace
property also can used to distinguish Hermes-managed topics on multi-purpose Kafka cluster.