Confluent Control Center Installation

This topic offers instruction for installing Control Center. For Confluent Platform installations, see Install Confluent Platform On-Premises.

For Control Center system requirements and compatibility with Confluent Platform, see System Requirements and Compatibility.

Single-node manual installation

Use these steps for single-node manual installation of Control Center with Confluent Platform.

Docker

The following steps install Confluent Platform 8.0 and Control Center 2.2.

To install Control Center with Docker

1. Clone Control Center public repo.

   git clone --branch control-center https://github.com/confluentinc/cp-all-in-one.git
   

2. Change directory into: cp-all-in-one

   cd cp-all-in-one/cp-all-in-one
   

3. Checkout branch: 8.0.0-post

   git checkout 8.0.0-post
   

4. Run the docker compose command.

   docker compose up -d
   

Archive

Install Control Center and Confluent Platform using archives on a single node.

Considerations:

• Control Center introduces a new directory structure that differs from the directory structure used with Control Center (Legacy).

• In earlier versions of the Confluent Platform, there was a single main directory, commonly referenced as CONFLUENT_HOME and all components, including Control Center (Legacy), were inside this main directory (i.e. CONFLUENT_HOME/control-center).

• Control Center now has its own top-level directory, CONTROL_CENTER_HOME.

• CONTROL_CENTER_HOME is placed at the same hierarchical level as CONFLUENT_HOME, not inside it.

• The steps below offer the optimal order in which to install Confluent Platform with Control Center.

Prerequisites:

• Provision a new virtual machine (VM) for Control Center on the same network as the Confluent Platform clusters that you want to monitor.

• For VM sizing recommendations, see System requirements.

• Install the same version of openjdk that is on your existing Control Center (Legacy) (openjdk-8-jdk, openjdk-11-jdk, or openjdk-17-jdk).

• On the Control Center VM, open ports 9090 (Control Center) and 9021 (Control Center user interface).

• On every broker or KRaft controller, ensure that you can send outgoing http traffic to port 9090 on the Control Center VM.

KRaft

Confluent Platform 8.1

Considerations:

• With local installations, the default port settings are as follows: Alertmanager uses port 9098 and controllers in KRaft mode use port 9093.

1. Download the Confluent Platform archive 8.1 and run these commands:

   wget https://packages.confluent.io/archive/8.1/confluent-8.1.0.tar.gz
   

   tar -xvf confluent-8.1.0.tar.gz
   

   cd confluent-8.1.0
   

   export CONFLUENT_HOME=`pwd`
   

2. Download the Control Center archive and run these commands:

   wget https://packages.confluent.io/confluent-control-center-next-gen/archive/confluent-control-center-next-gen-2.3.0.tar.gz
   

   tar -xvf confluent-control-center-next-gen-2.3.0.tar.gz
   

   cd confluent-control-center-next-gen-2.3.0
   

   export CONTROL_CENTER_HOME=`pwd`
   

3. Change directory to the $CONFLUENT_HOME/bin directory:

   export PATH=$PATH:$CONFLUENT_HOME/bin
   

4. Use the Confluent CLI to run the following command:

   confluent local services start
   

Confluent Platform 7.7 - 8.0

Considerations:

• You must use a special command to start Prometheus on MacOS.

• By default Alertmanager and controllers in KRaft mode use port 9093. To run Prometheus and Alertmanager and KRaft mode controllers on the same host, you must manually edit the provided Control Center scripts.

1. Download the Confluent Platform archive (7.7 to 8.0 supported) and run these commands:

   wget https://packages.confluent.io/archive/8.0/confluent-8.0.0.tar.gz
   

   tar -xvf confluent-8.0.0.tar.gz
   

   cd confluent-8.0.0
   

   export CONFLUENT_HOME=`pwd`
   

2. Update the broker and controller configurations to emit metrics to Prometheus by adding the following configurations to: etc/kafka/controller.properties and etc/kafka/broker.properties

   The fifth line (confluent.telemetry.exporter._c3.metrics.include=<value>) is very long. Simply copy the code block as provided and append it to the end of the properties files. Pasting the fifth line results in a single line, even though it shows as wrapped in the documentation.

   metric.reporters=io.confluent.telemetry.reporter.TelemetryReporter
   confluent.telemetry.exporter._c3.type=http
   confluent.telemetry.exporter._c3.enabled=true
   confluent.telemetry.exporter._c3.metrics.include=io.confluent.kafka.server.request.(?!.*delta).*|io.confluent.kafka.server.server.broker.state|io.confluent.kafka.server.replica.manager.leader.count|io.confluent.kafka.server.request.queue.size|io.confluent.kafka.server.broker.topic.failed.produce.requests.rate.1.min|io.confluent.kafka.server.tier.archiver.total.lag|io.confluent.kafka.server.request.total.time.ms.p99|io.confluent.kafka.server.broker.topic.failed.fetch.requests.rate.1.min|io.confluent.kafka.server.broker.topic.total.fetch.requests.rate.1.min|io.confluent.kafka.server.partition.caught.up.replicas.count|io.confluent.kafka.server.partition.observer.replicas.count|io.confluent.kafka.server.tier.tasks.num.partitions.in.error|io.confluent.kafka.server.broker.topic.bytes.out.rate.1.min|io.confluent.kafka.server.request.total.time.ms.p95|io.confluent.kafka.server.controller.active.controller.count|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.total|io.confluent.kafka.server.request.total.time.ms.p999|io.confluent.kafka.server.controller.active.broker.count|io.confluent.kafka.server.request.handler.pool.request.handler.avg.idle.percent.rate.1.min|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.rate.1.min|io.confluent.kafka.server.controller.unclean.leader.elections.rate.1.min|io.confluent.kafka.server.replica.manager.partition.count|io.confluent.kafka.server.controller.unclean.leader.elections.total|io.confluent.kafka.server.partition.replicas.count|io.confluent.kafka.server.broker.topic.total.produce.requests.rate.1.min|io.confluent.kafka.server.controller.offline.partitions.count|io.confluent.kafka.server.socket.server.network.processor.avg.idle.percent|io.confluent.kafka.server.partition.under.replicated|io.confluent.kafka.server.log.log.start.offset|io.confluent.kafka.server.log.tier.size|io.confluent.kafka.server.log.size|io.confluent.kafka.server.tier.fetcher.bytes.fetched.total|io.confluent.kafka.server.request.total.time.ms.p50|io.confluent.kafka.server.tenant.consumer.lag.offsets|io.confluent.kafka.server.session.expire.listener.zookeeper.expires.rate.1.min|io.confluent.kafka.server.log.log.end.offset|io.confluent.kafka.server.broker.topic.bytes.in.rate.1.min|io.confluent.kafka.server.partition.under.min.isr|io.confluent.kafka.server.partition.in.sync.replicas.count|io.confluent.telemetry.http.exporter.batches.dropped|io.confluent.telemetry.http.exporter.items.total|io.confluent.telemetry.http.exporter.items.succeeded|io.confluent.telemetry.http.exporter.send.time.total.millis|io.confluent.kafka.server.controller.leader.election.rate.(?!.*delta).*|io.confluent.telemetry.http.exporter.batches.failed
   confluent.telemetry.exporter._c3.client.base.url=http://localhost:9090/api/v1/otlp
   confluent.telemetry.exporter._c3.client.compression=gzip
   confluent.telemetry.exporter._c3.api.key=dummy
   confluent.telemetry.exporter._c3.api.secret=dummy
   confluent.telemetry.exporter._c3.buffer.pending.batches.max=80
   confluent.telemetry.exporter._c3.buffer.batch.items.max=4000
   confluent.telemetry.exporter._c3.buffer.inflight.submissions.max=10
   confluent.telemetry.metrics.collector.interval.ms=60000
   confluent.telemetry.remoteconfig._confluent.enabled=false
   confluent.consumer.lag.emitter.enabled=true
   

3. Download the Control Center archive and run these commands:

   wget https://packages.confluent.io/confluent-control-center-next-gen/archive/confluent-control-center-next-gen-2.3.0.tar.gz
   

   tar -xvf confluent-control-center-next-gen-2.3.0.tar.gz
   

   cd confluent-control-center-next-gen-2.3.0
   

   export C3_HOME=`pwd`
   

4. Start Prometheus and Alertmanager

   To start Control Center, you must have three dedicated command windows: one for Prometheus, another for the Control Center process, and a third dedicated command window for Alertmanager. Run the following commands from $C3_HOME in all command windows.

   1. Open etc/confluent-control-center/prometheus-generated.yml and change localhost:9093 to localhost:9098

      alerting:
         alertmanagers:
            - static_configs:
               - targets:
                  - localhost:9098
      

   2. Start Prometheus.

      All operating systems except MacOS:

      bin/prometheus-start
      

      MacOS:

      bash bin/prometheus-start
      

      Note

      Prometheus runs but does not output any information to the screen.

   3. Start Alertmanager.

      1. Run this command:

         export ALERTMANAGER_PORT=9098
         

      2. All operating systems except MacOS:

         bin/alertmanager-start
         

         MacOS

         bash bin/alertmanager-start
         

5. Start Control Center.

   1. Open etc/confluent-control-center/control-center-dev.properties and update port 9093 to 9098:

      confluent.controlcenter.alertmanager.url=http://localhost:9098
      

   2. Run this command:

      bin/control-center-start etc/confluent-control-center/control-center-dev.properties
      

6. Start Confluent Platform.

   To start Confluent Platform, you must have two dedicated command windows, one for the controller and another for the broker process. All the following commands are meant to be run from CONFLUENT_HOME in both command windows. The Confluent Platform start sequence requires you to generate a single random ID and use that same ID for both the controller and the broker process.

   1. In the command window dedicated to running the controller, change directories into CONFLUENT_HOME.

      cd CONFLUENT_HOME
      

   2. Generate a random value for KAFKA_CLUSTER_ID.

      KAFKA_CLUSTER_ID="$(bin/kafka-storage random-uuid)"
      

   3. Use the following command to get the random ID and save the output. You need this value to start the controller and the broker.

      echo $KAFKA_CLUSTER_ID
      

   4. Format the log directories for the controller:

      bin/kafka-storage format --cluster-id $KAFKA_CLUSTER_ID -c etc/kafka/kraft/controller.properties --standalone
      

   5. Start the controller:

      bin/kafka-server-start etc/kafka/kraft/controller.properties
      

   6. Open a command window for the broker and navigate to CONFLUENT_HOME.

      cd CONFLUENT_HOME
      

   7. Set the KAFKA_CLUSTER_ID variable to the random ID you generated earlier with kafka-storage random-uuid.

      export KAFKA_CLUSTER_ID=<KAFKA-CLUSTER-ID>
      

   8. Format the log directories for this broker:

      bin/kafka-storage format --cluster-id $KAFKA_CLUSTER_ID -c etc/kafka/kraft/broker.properties
      

   9. Start the broker:

      bin/kafka-server-start etc/kafka/kraft/broker.properties
      

ZooKeeper

Considerations:

• You must use a special command to start Prometheus on MacOS.

1. Download the Confluent Platform archive (7.7 to 7.9 supported) and run these commands:

   wget https://packages.confluent.io/archive/7.9/confluent-7.9.0.tar.gz
   

   tar -xvf confluent-7.9.0.tar.gz
   

   cd confluent-7.9.0
   

   export CONFLUENT_HOME=`pwd`
   

2. Update broker configurations to emit metrics to Prometheus by adding the following configurations to: etc/kafka/server.properties

   metric.reporters=io.confluent.telemetry.reporter.TelemetryReporter
   confluent.telemetry.exporter._c3.type=http
   confluent.telemetry.exporter._c3.enabled=true
   confluent.telemetry.exporter._c3.metrics.include=io.confluent.kafka.server.request.(?!.*delta).*|io.confluent.kafka.server.server.broker.state|io.confluent.kafka.server.replica.manager.leader.count|io.confluent.kafka.server.request.queue.size|io.confluent.kafka.server.broker.topic.failed.produce.requests.rate.1.min|io.confluent.kafka.server.tier.archiver.total.lag|io.confluent.kafka.server.request.total.time.ms.p99|io.confluent.kafka.server.broker.topic.failed.fetch.requests.rate.1.min|io.confluent.kafka.server.broker.topic.total.fetch.requests.rate.1.min|io.confluent.kafka.server.partition.caught.up.replicas.count|io.confluent.kafka.server.partition.observer.replicas.count|io.confluent.kafka.server.tier.tasks.num.partitions.in.error|io.confluent.kafka.server.broker.topic.bytes.out.rate.1.min|io.confluent.kafka.server.request.total.time.ms.p95|io.confluent.kafka.server.controller.active.controller.count|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.total|io.confluent.kafka.server.request.total.time.ms.p999|io.confluent.kafka.server.controller.active.broker.count|io.confluent.kafka.server.request.handler.pool.request.handler.avg.idle.percent.rate.1.min|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.rate.1.min|io.confluent.kafka.server.controller.unclean.leader.elections.rate.1.min|io.confluent.kafka.server.replica.manager.partition.count|io.confluent.kafka.server.controller.unclean.leader.elections.total|io.confluent.kafka.server.partition.replicas.count|io.confluent.kafka.server.broker.topic.total.produce.requests.rate.1.min|io.confluent.kafka.server.controller.offline.partitions.count|io.confluent.kafka.server.socket.server.network.processor.avg.idle.percent|io.confluent.kafka.server.partition.under.replicated|io.confluent.kafka.server.log.log.start.offset|io.confluent.kafka.server.log.tier.size|io.confluent.kafka.server.log.size|io.confluent.kafka.server.tier.fetcher.bytes.fetched.total|io.confluent.kafka.server.request.total.time.ms.p50|io.confluent.kafka.server.tenant.consumer.lag.offsets|io.confluent.kafka.server.session.expire.listener.zookeeper.expires.rate.1.min|io.confluent.kafka.server.log.log.end.offset|io.confluent.kafka.server.broker.topic.bytes.in.rate.1.min|io.confluent.kafka.server.partition.under.min.isr|io.confluent.kafka.server.partition.in.sync.replicas.count|io.confluent.telemetry.http.exporter.batches.dropped|io.confluent.telemetry.http.exporter.items.total|io.confluent.telemetry.http.exporter.items.succeeded|io.confluent.telemetry.http.exporter.send.time.total.millis|io.confluent.kafka.server.controller.leader.election.rate.(?!.*delta).*|io.confluent.telemetry.http.exporter.batches.failed
   confluent.telemetry.exporter._c3.client.base.url=http://localhost:9090/api/v1/otlp
   confluent.telemetry.exporter._c3.client.compression=gzip
   confluent.telemetry.exporter._c3.api.key=dummy
   confluent.telemetry.exporter._c3.api.secret=dummy
   confluent.telemetry.exporter._c3.buffer.pending.batches.max=80
   confluent.telemetry.exporter._c3.buffer.batch.items.max=4000
   confluent.telemetry.exporter._c3.buffer.inflight.submissions.max=10
   confluent.telemetry.metrics.collector.interval.ms=60000
   confluent.telemetry.remoteconfig._confluent.enabled=false
   confluent.consumer.lag.emitter.enabled=true
   

3. Download the Control Center archive and run these commands:

   wget https://packages.confluent.io/confluent-control-center-next-gen/archive/confluent-control-center-next-gen-2.3.0.tar.gz
   

   tar -xvf confluent-control-center-next-gen-2.3.0.tar.gz
   

   cd confluent-control-center-next-gen-2.3.0
   

4. Start Control Center.

   To start Control Center, you must have three dedicated command windows: one for Prometheus, another for the Control Center process, and a third for Alertmanager. Run the following commands from CONTROL_CENTER_HOME in all command windows.

   1. Start Prometheus.

      bin/prometheus-start
      

   2. Start Alertmanager.

      bin/alertmanager-start
      

   3. Start Control Center.

      bin/control-center-start etc/confluent-control-center/control-center-dev.properties
      

5. Start Confluent Platform.

   Start ZooKeeper.

   bin/zookeeper-server-start etc/kafka/zookeeper.properties
   

   Start Kafka.

   bin/kafka-server-start etc/kafka/server.properties
   

Multi-node manual installation

Use these steps for multi-node manual installation of Control Center and Confluent Platform.

1. Provision a new node using any of the Confluent Platform supported operating systems. For more information, see Supported operating systems. Login to the VM on which you will install Confluent Platform.

   Install Control Center on a new node/VM. To ensure a smooth transition, allow Control Center (Legacy) users to continue using Control Center (Legacy) until the Control Center has gathered 7-15 days of historical metrics. For more information, see Migration.

2. Login to the VM and install Control Center. For more information, see Compatibility with Confluent Platform.

   Use the instructions for installing Confluent Platform but make sure to use the base URL and properties from these instructions to install Control Center.

   For more information, see Confluent Platform System Requirements, Install Confluent Platform using Systemd on Ubuntu and Debian, and Install Confluent Platform using Systemd on RHEL, CentOS, and Fedora-based Linux.

   Ubuntu and Debian

   export BASE_URL=https://packages.confluent.io/confluent-control-center-next-gen/deb/
   sudo apt-get update
   wget ${BASE_URL}archive.key
   sudo apt-key add archive.key
   sudo add-apt-repository -y "deb ${BASE_URL} stable main"
   sudo apt update
   

   sudo apt install -y confluent-control-center-next-gen
   

   RHEL, CentOS, and Fedora-based Linux

   export base_url=https://packages.confluent.io/confluent-control-center-next-gen/rpm/
   cat <<EOF | sudo tee /etc/yum.repos.d/Confluent.repo > /dev/null
   [Confluent]
   name=Confluent repository
   baseurl=${base_url}
   gpgcheck=1
   gpgkey=${base_url}archive.key
   enabled=1
   EOF
   

   sudo yum install -y confluent-control-center-next-gen cyrus-sasl openssl-devel
   

3. Install Java for your operating system (if not installed).

   sudo yum install java-17-openjdk -y  ---- RHEL/CentOs/Fedora
   

   sudo apt install openjdk-17-jdk -y ---- Ubuntu/Debian
   

4. Copy /etc/confluent-control-center/control-center-production.properties from your current Control Center (Legacy) into the Control Center node on the VM and add this property:

   confluent.controlcenter.id=10
   confluent.controlcenter.prometheus.enable=true
   confluent.controlcenter.prometheus.url=http://localhost:9090
   confluent.controlcenter.prometheus.rules.file=/etc/confluent-control-center/trigger_rules-generated.yml
   confluent.controlcenter.alertmanager.config.file=/etc/confluent-control-center/alertmanager-generated.yml
   

5. If you are using SSL, copy the certs at /var/ssl/private from your current Control Center (Legacy) into the Control Center node on the VM. If you are not using SSL, skip this step.

6. Change ownership of the configuration files. Give the Control Center process write permissions to the alert manager, so that the process can properly manage alert triggers. Use the chown command to set the Control Center process as the owner of the trigger_rules-generated.yml and alertmanager-generated.yml files.

   chown -c cp-control-center /etc/confluent-control-center/trigger_rules-generated.yml
   chown -c cp-control-center /etc/confluent-control-center/alertmanager-generated.yml
   

7. Start the following services on the Control Center node:

   systemctl enable prometheus
   systemctl start prometheus
   
   systemctl enable alertmanager
   systemctl start alertmanager
   
   systemctl enable confluent-control-center
   systemctl start confluent-control-center
   

8. Login to each broker you intend to monitor and verify brokers can reach the Control Center node on port 9090.

   curl http://<c3-internal-dns-url>:9090/-/healthy
   

   All brokers must have access to the Control Center node on port 9090, but port 9090 does not require public access. Restrict access as you prefer.

9. Update the following properties for every Kafka broker and KRaft controller. Pay attention to the notes on the highlighted lines that follow the code example.

   KRaft controller properties are located here: /etc/controller/server.properties

   metric.reporters=io.confluent.telemetry.reporter.TelemetryReporter,io.confluent.metrics.reporter.ConfluentMetricsReporter --- [1]
   confluent.telemetry.exporter._c3.type=http
   confluent.telemetry.exporter._c3.enabled=true
   confluent.telemetry.exporter._c3.metrics.include=io.confluent.kafka.server.request.(?!.*delta).*|io.confluent.kafka.server.server.broker.state|io.confluent.kafka.server.replica.manager.leader.count|io.confluent.kafka.server.request.queue.size|io.confluent.kafka.server.broker.topic.failed.produce.requests.rate.1.min|io.confluent.kafka.server.tier.archiver.total.lag|io.confluent.kafka.server.request.total.time.ms.p99|io.confluent.kafka.server.broker.topic.failed.fetch.requests.rate.1.min|io.confluent.kafka.server.broker.topic.total.fetch.requests.rate.1.min|io.confluent.kafka.server.partition.caught.up.replicas.count|io.confluent.kafka.server.partition.observer.replicas.count|io.confluent.kafka.server.tier.tasks.num.partitions.in.error|io.confluent.kafka.server.broker.topic.bytes.out.rate.1.min|io.confluent.kafka.server.request.total.time.ms.p95|io.confluent.kafka.server.controller.active.controller.count|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.total|io.confluent.kafka.server.request.total.time.ms.p999|io.confluent.kafka.server.controller.active.broker.count|io.confluent.kafka.server.request.handler.pool.request.handler.avg.idle.percent.rate.1.min|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.rate.1.min|io.confluent.kafka.server.controller.unclean.leader.elections.rate.1.min|io.confluent.kafka.server.replica.manager.partition.count|io.confluent.kafka.server.controller.unclean.leader.elections.total|io.confluent.kafka.server.partition.replicas.count|io.confluent.kafka.server.broker.topic.total.produce.requests.rate.1.min|io.confluent.kafka.server.controller.offline.partitions.count|io.confluent.kafka.server.socket.server.network.processor.avg.idle.percent|io.confluent.kafka.server.partition.under.replicated|io.confluent.kafka.server.log.log.start.offset|io.confluent.kafka.server.log.tier.size|io.confluent.kafka.server.log.size|io.confluent.kafka.server.tier.fetcher.bytes.fetched.total|io.confluent.kafka.server.request.total.time.ms.p50|io.confluent.kafka.server.tenant.consumer.lag.offsets|io.confluent.kafka.server.session.expire.listener.zookeeper.expires.rate.1.min|io.confluent.kafka.server.log.log.end.offset|io.confluent.kafka.server.broker.topic.bytes.in.rate.1.min|io.confluent.kafka.server.partition.under.min.isr|io.confluent.kafka.server.partition.in.sync.replicas.count|io.confluent.telemetry.http.exporter.batches.dropped|io.confluent.telemetry.http.exporter.items.total|io.confluent.telemetry.http.exporter.items.succeeded|io.confluent.telemetry.http.exporter.send.time.total.millis|io.confluent.kafka.server.controller.leader.election.rate.(?!.*delta).*|io.confluent.telemetry.http.exporter.batches.failed
   confluent.telemetry.exporter._c3.client.base.url=http://c3-internal-dns-hostname:9090/api/v1/otlp --- [2]
   confluent.telemetry.exporter._c3.client.compression=gzip
   confluent.telemetry.exporter._c3.api.key=dummy
   confluent.telemetry.exporter._c3.api.secret=dummy
   confluent.telemetry.exporter._c3.buffer.pending.batches.max=80 --- [3]
   confluent.telemetry.exporter._c3.buffer.batch.items.max=4000 --- [4]
   confluent.telemetry.exporter._c3.buffer.inflight.submissions.max=10 --- [5]
   confluent.telemetry.metrics.collector.interval.ms=60000 --- [6]
   confluent.telemetry.remoteconfig._confluent.enabled=false
   confluent.consumer.lag.emitter.enabled=true
   

   • [1] To enable metrics for both Control Center (Legacy) and Control Center, update your existing Control Center (Legacy) property metric.reporters to use the following values:

     metric.reporters=io.confluent.telemetry.reporter.TelemetryReporter,io.confluent.metrics.reporter.ConfluentMetricsReporter
     

     If you decommission Control Center (Legacy), enable only TelemetryReporter plugin with the following value:

     metric.reporters=io.confluent.telemetry.reporter.TelemetryReporter
     

   • [2] Ensure the URL in confluent.telemetry.exporter._c3.client.base.url is the actual Control Center URL, reachable from the broker host.

     confluent.telemetry.exporter._c3.client.base.url=http://c3-internal-dns-hostname:9090/api/v1/otlp
     

   • [3] [4] [5] [6] Use the following configurations for clusters up to 100,000 or fewer replicas. To get an accurate count of replicas, use the sum of all replicas across all clusters monitored in Control Center (Legacy) (including the Control Center (Legacy) bootstrap cluster).

     confluent.telemetry.exporter._c3.buffer.pending.batches.max=80
     confluent.telemetry.exporter._c3.buffer.batch.items.max=4000
     confluent.telemetry.exporter._c3.buffer.inflight.submissions.max=10
     confluent.telemetry.metrics.collector.interval.ms=60000
     

   Configurations for clusters with 100,000 to 400,000 replicas

   Clusters with a replica count of 100,000 - 200,000:

   confluent.telemetry.exporter._c3.buffer.pending.batches.max=80
   confluent.telemetry.exporter._c3.buffer.batch.items.max=4000
   confluent.telemetry.exporter._c3.buffer.inflight.submissions.max=20
   confluent.telemetry.metrics.collector.interval.ms=60000
   

   Clusters with a replica count of 200,000 - 400,000:

   confluent.telemetry.exporter._c3.buffer.pending.batches.max=80
   confluent.telemetry.exporter._c3.buffer.batch.items.max=4000
   confluent.telemetry.exporter._c3.buffer.inflight.submissions.max=20
   confluent.telemetry.metrics.collector.interval.ms=120000
   

   For clusters with a replica count of 200,000 - 400,000, also update the following Control Center (Legacy) configuration:

   confluent.controlcenter.prometheus.trigger.threshold.time=2m
   

10. Perform a rolling restart for the brokers (zero downtime). For more information, see Rolling restart.

    systemctl restart confluent-server
    

11. (Optional) Setup log rotation for Prometheus and Alertmanager.

    Prometheus

    1. Create a new configuration file at /etc/logrotate.d/prometheus with the following content:

       /var/log/confluent/control-center/prometheus.log {
          size 10MB
          rotate 5
          compress
          delaycompress
          missingok
          notifempty
          copytruncate
       }
       

    2. Create a script at /usr/local/bin/logrotate-prometheus.sh:

       #!/bin/bash
       /usr/sbin/logrotate -s /var/lib/logrotate/status-prometheus /etc/logrotate.d/prometheus
       

    3. Make the script executable

       chmod +x /usr/local/bin/logrotate-prometheus.sh
       

    4. To schedule with Cron, add the following line to your crontab (crontab -e):

       */10 * * * * /usr/local/bin/logrotate-prometheus.sh >> /tmp/prometheus-rotate.log 2>&1
       

    5. Restart Prometheus

       systemctl restart prometheus
       

    6. Perform similar steps for Alertmanager logs.

    Alertmanager

    1. Create a new configuration file at /etc/logrotate.d/alertmanager with the following content:

       /var/log/confluent/control-center/alertmanager.log {
          size 10MB
          rotate 5
          compress
          delaycompress
          missingok
          notifempty
          copytruncate
       }
       

    2. Create a script at /usr/local/bin/logrotate-alertmanager.sh:

       #!/bin/bash
       /usr/sbin/logrotate -s /var/lib/logrotate/status-alertmanager /etc/logrotate.d/alertmanager
       

    3. Make the script executable

       chmod +x /usr/local/bin/logrotate-alertmanager.sh
       

    4. To schedule with Cron, add the following line to your crontab (crontab -e):

       */10 * * * * /usr/local/bin/logrotate-alertmanager.sh >> /tmp/alertmanager-rotate.log 2>&1
       

    5. Restart Alertmanager

       systemctl restart alertmanager
       

Verify Control Center is running

After the installation is complete, visit http(s)://<c3-url>:9021 and wait for the metrics to start showing up in Control Center. It may take a couple of minutes. Control Center looks exactly like Control Center (Legacy).

To confirm Control Center is running, use the following steps:

1. Open the network tab in Control Center.

2. Reload Control Center.

3. Locate the following API call: /2.0/feature/flags

4. Verify the following key is present in the response: confluent.controlcenter.prometheus.enable: true

Confluent Ansible installation steps

For Confluent Ansible installation of Control Center, see Configure Ansible Playbooks for Confluent Platform.

Confluent for Kubernetes installation steps

For Confluent for Kubernetes (CFK) installation of Control Center, see Monitor Confluent Platform with Confluent for Kubernetes.

High-availability setup

Use these steps to configure Control Center for Active/Active high-availability deployment.

Considerations:

• You must manually duplicate alerts in one of your Control Center instances.

• For a Confluent Ansible example of Control Center Active/Active high-availability setup, see: GitHub repo

• For CFK example of Control Center Active/Active high-availability setup, see: GitHub repo

To configure Control Center Active/Active high-availability, use the following steps:

1. Configure two instances of Control Center for your Kafka cluster.

2. For every Kafka broker and KRaft controller, you must add and configure two HttpExporters.

   Consider the following example HttpExporter configurations:

   confluent.telemetry.exporter._c3-1.client.base.url=http://{C3-1-internal-dns-hostname}:9090/api/v1/otlp
   
   confluent.telemetry.exporter._c3-2.client.base.url=http://{C3-2-internal-dns-hostname}:9090/api/v1/otlp
   

   • Replace {C3-1-internal-dns-hostname} with the base URL for the corresponding Prometheus instance in your cluster.

3. For every Kafka broker and KRaft controller, add the following configurations:

   #common configs
   
   confluent.telemetry.metrics.collector.interval.ms=60000
   confluent.telemetry.remoteconfig._confluent.enabled=false
   confluent.consumer.lag.emitter.enabled=true
   metric.reporters=io.confluent.telemetry.reporter.TelemetryReporter
   
   # instance 1 configs
   
   confluent.telemetry.exporter._c3.type=http
   confluent.telemetry.exporter._c3.enabled=true
   confluent.telemetry.exporter._c3.client.base.url=http://{C3-1-internal-dns-hostname}:9090/api/v1/otlp
   confluent.telemetry.exporter._c3.client.compression=gzip
   confluent.telemetry.exporter._c3.api.key=dummy
   confluent.telemetry.exporter._c3.api.secret=dummy
   confluent.telemetry.exporter._c3.buffer.pending.batches.max=80
   confluent.telemetry.exporter._c3.buffer.batch.items.max=4000
   confluent.telemetry.exporter._c3.buffer.inflight.submissions.max=10
   confluent.telemetry.exporter._c3.metrics.include=io.confluent.kafka.server.request.(?!.*delta).*|io.confluent.kafka.server.server.broker.state|io.confluent.kafka.server.replica.manager.leader.count|io.confluent.kafka.server.request.queue.size|io.confluent.kafka.server.broker.topic.failed.produce.requests.rate.1.min|io.confluent.kafka.server.tier.archiver.total.lag|io.confluent.kafka.server.request.total.time.ms.p99|io.confluent.kafka.server.broker.topic.failed.fetch.requests.rate.1.min|io.confluent.kafka.server.broker.topic.total.fetch.requests.rate.1.min|io.confluent.kafka.server.partition.caught.up.replicas.count|io.confluent.kafka.server.partition.observer.replicas.count|io.confluent.kafka.server.tier.tasks.num.partitions.in.error|io.confluent.kafka.server.broker.topic.bytes.out.rate.1.min|io.confluent.kafka.server.request.total.time.ms.p95|io.confluent.kafka.server.controller.active.controller.count|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.total|io.confluent.kafka.server.request.total.time.ms.p999|io.confluent.kafka.server.controller.active.broker.count|io.confluent.kafka.server.request.handler.pool.request.handler.avg.idle.percent.rate.1.min|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.rate.1.min|io.confluent.kafka.server.controller.unclean.leader.elections.rate.1.min|io.confluent.kafka.server.replica.manager.partition.count|io.confluent.kafka.server.controller.unclean.leader.elections.total|io.confluent.kafka.server.partition.replicas.count|io.confluent.kafka.server.broker.topic.total.produce.requests.rate.1.min|io.confluent.kafka.server.controller.offline.partitions.count|io.confluent.kafka.server.socket.server.network.processor.avg.idle.percent|io.confluent.kafka.server.partition.under.replicated|io.confluent.kafka.server.log.log.start.offset|io.confluent.kafka.server.log.tier.size|io.confluent.kafka.server.log.size|io.confluent.kafka.server.tier.fetcher.bytes.fetched.total|io.confluent.kafka.server.request.total.time.ms.p50|io.confluent.kafka.server.tenant.consumer.lag.offsets|io.confluent.kafka.server.session.expire.listener.zookeeper.expires.rate.1.min|io.confluent.kafka.server.log.log.end.offset|io.confluent.kafka.server.broker.topic.bytes.in.rate.1.min|io.confluent.kafka.server.partition.under.min.isr|io.confluent.kafka.server.partition.in.sync.replicas.count|io.confluent.telemetry.http.exporter.batches.dropped|io.confluent.telemetry.http.exporter.items.total|io.confluent.telemetry.http.exporter.items.succeeded|io.confluent.telemetry.http.exporter.send.time.total.millis|io.confluent.kafka.server.controller.leader.election.rate.(?!.*delta).*|io.confluent.telemetry.http.exporter.batches.failed
   
   # instance 2 configs
   
   confluent.telemetry.exporter._c3-2.type=http
   confluent.telemetry.exporter._c3-2.enabled=true
   confluent.telemetry.exporter._c3-2.client.compression=gzip
   confluent.telemetry.exporter._c3-2.api.key=dummy
   confluent.telemetry.exporter._c3-2.api.secret=dummy
   confluent.telemetry.exporter._c3-2.buffer.pending.batches.max=80
   confluent.telemetry.exporter._c3-2.buffer.batch.items.max=4000
   confluent.telemetry.exporter._c3-2.buffer.inflight.submissions.max=10
   confluent.telemetry.exporter._c3-2.client.base.url=http://{C3-2-internal-dns-hostname}:9090/api/v1/otlp
   confluent.telemetry.exporter._c3-2.metrics.include=io.confluent.kafka.server.request.(?!.*delta).*|io.confluent.kafka.server.server.broker.state|io.confluent.kafka.server.replica.manager.leader.count|io.confluent.kafka.server.request.queue.size|io.confluent.kafka.server.broker.topic.failed.produce.requests.rate.1.min|io.confluent.kafka.server.tier.archiver.total.lag|io.confluent.kafka.server.request.total.time.ms.p99|io.confluent.kafka.server.broker.topic.failed.fetch.requests.rate.1.min|io.confluent.kafka.server.broker.topic.total.fetch.requests.rate.1.min|io.confluent.kafka.server.partition.caught.up.replicas.count|io.confluent.kafka.server.partition.observer.replicas.count|io.confluent.kafka.server.tier.tasks.num.partitions.in.error|io.confluent.kafka.server.broker.topic.bytes.out.rate.1.min|io.confluent.kafka.server.request.total.time.ms.p95|io.confluent.kafka.server.controller.active.controller.count|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.total|io.confluent.kafka.server.request.total.time.ms.p999|io.confluent.kafka.server.controller.active.broker.count|io.confluent.kafka.server.request.handler.pool.request.handler.avg.idle.percent.rate.1.min|io.confluent.kafka.server.session.expire.listener.zookeeper.disconnects.rate.1.min|io.confluent.kafka.server.controller.unclean.leader.elections.rate.1.min|io.confluent.kafka.server.replica.manager.partition.count|io.confluent.kafka.server.controller.unclean.leader.elections.total|io.confluent.kafka.server.partition.replicas.count|io.confluent.kafka.server.broker.topic.total.produce.requests.rate.1.min|io.confluent.kafka.server.controller.offline.partitions.count|io.confluent.kafka.server.socket.server.network.processor.avg.idle.percent|io.confluent.kafka.server.partition.under.replicated|io.confluent.kafka.server.log.log.start.offset|io.confluent.kafka.server.log.tier.size|io.confluent.kafka.server.log.size|io.confluent.kafka.server.tier.fetcher.bytes.fetched.total|io.confluent.kafka.server.request.total.time.ms.p50|io.confluent.kafka.server.tenant.consumer.lag.offsets|io.confluent.kafka.server.session.expire.listener.zookeeper.expires.rate.1.min|io.confluent.kafka.server.log.log.end.offset|io.confluent.kafka.server.broker.topic.bytes.in.rate.1.min|io.confluent.kafka.server.partition.under.min.isr|io.confluent.kafka.server.partition.in.sync.replicas.count|io.confluent.telemetry.http.exporter.batches.dropped|io.confluent.telemetry.http.exporter.items.total|io.confluent.telemetry.http.exporter.items.succeeded|io.confluent.telemetry.http.exporter.send.time.total.millis|io.confluent.kafka.server.controller.leader.election.rate.(?!.*delta).*|io.confluent.telemetry.http.exporter.batches.failed
   

Security configuration

Control Center introduces components like Prometheus and Alertmanager. The security configuration you use to secure communication for Control Center depends on the version of Confluent Platform you use.

Considerations:

• Control Center supports TLS + Basic Auth for Confluent Platform versions 7.5.x and higher

• Control Center supports mTLS for Confluent Platform versions 7.9.1 and higher

For more information, see Control Center Security on Confluent Platform.

Migration

Migration of metrics from Control Center (Legacy) to Control Center is not supported. For migration of alerts, see Control Center (Legacy) to Confluent Control Center Alert Migration.

Considerations:

• For clusters where historical metrics are of no value, you can shut down Control Center (Legacy) as soon as Control Center is up and running.

• For clusters where historical metrics are needed (say, for a period of N days), consider the following recommendations:

  • Run both Control Center (Legacy) and Control Center simultaneously for N days.

  • Control Center (Legacy) users should continue using Control Center (Legacy) until the N days of history is populated in Control Center.

  • Once historical metrics are available in Control Center, you can shut down Control Center (Legacy) and move users to Control Center.