---

id: version-0.55.2-pre-asf-user-guide-software-components title: Software Components sidebar_label: Software Components original_id: user-guide-software-components

This page contains all the software components that can be used within the StreamPipes framework. Some of them are mandatory but others are just necessary for a special capabilities. In the Installation Guide we already provide a docker-compose.yml file with all the necessary components for a minimal setup. Extend this configuration files with further containers described on this page and configure StreamPipes according to your needs.

StreamPipes Framework

Description

The StreamPipes Backend is the main component of the StreamPipes Framework. It contains the application logic to create and execute pipelines. Furthermore, it provides a REST-API that is used by other components for communication.

Docker Compose

backend:
  image: streampipes/backend
  depends_on:
    - "consul"
  ports:
    - "8030:8030"
  volumes:
    - ./config:/root/.streampipes
    - ./config/aduna:/root/.aduna
  networks:
    spnet:

Description

This service uses nginx and contains the UI of StreamPipes. The UI can, for example, be used to import new pipeline elements, create new pipelines and manage the pipeline execution. The UI communicates with the backend via the REST interface.

Docker Compose

nginx:
  image: streampipes/ui
  ports:
    - "80:80"
  depends_on:
    - backend
  networks:
    spnet:

StreamPipes Services

Docker Compose

consul:
    image: consul
    environment:
      - "CONSUL_LOCAL_CONFIG={\"disable_update_check\": true}"
      - "CONSUL_BIND_INTERFACE=eth0"
      - "CONSUL_HTTP_ADDR=0.0.0.0"
    entrypoint:
      - consul
      - agent
      - -server
      - -bootstrap-expect=1
      - -data-dir=/consul/data
      - -node=consul-one
      - -bind={{ GetInterfaceIP "eth0" }}
      - -client=0.0.0.0
      - -enable-script-checks=true
      - -ui
    volumes:
      - ./config/consul:/consul/data
    ports:
      - "8500:8500"
      - "8600:8600"
    networks:
      spnet:
        ipv4_address: 172.30.0.9

Docker Compose

zookeeper:
    image: wurstmeister/zookeeper
    ports:
      - "2181:2181"
    networks:
      spnet:

Description

Kafka is used as the primary message broker. It is possible to use other brokers or even multiple message brokers in a single pipeline, but Kafka is the default. The communication between the processing elements in a pipeline is mostly done via Kafka.

Docker Compose

  kafka:
    image: wurstmeister/kafka:0.10.0.1
    ports:
      - "9092:9092"
    environment:
      KAFKA_ADVERTISED_HOST_NAME: ###TODO ADD HOSTNAME HERE ###
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock
    networks:
      spnet:

Docker Compose

activemq:
  image: streampipes/activemq
  ports:
    - "61616:61616"
    - "61614:61614"
    - "8161:8161"
  networks:
    spnet:

    ```
</details>

<details class="tip">
<summary>CouchDB</summary>

#### Description
CouchDB is the main database for StreamPipes data that needs to be persisted such as pipelines, users and visualizations created in the dashboard.

#### Docker Compose
```yaml
couchdb:
  image: couchdb
  ports:
    - "5984:5984"
  volumes:
    - ./config/couchdb/data:/usr/local/var/lib/couchdb
  networks:
    spnet:

Docker Compose

jobmanager:
  image: streampipes/flink
  ports:
    - "8081:8099"
  command: jobmanager
  networks:
    spnet:


taskmanager:
  image: ipe-wim-gitlab.fzi.de:5000/streampipes/services/flink
  command: taskmanager
  environment:
    - FLINK_NUM_SLOTS=20
  networks:
    spnet:

Processing Elements

Docker Compose

    pe-examples-sources:
      image: streampipes/pe-examples-sources:
      depends_on:
        - "consul"
      ports:
        - "8098:8090"
      networks:
        spnet:

Description

This Processing Element Container contains some sink example implementations, like for example the real-time dashboard. This can be used to visualize data within StreamPipes.

Docker Compose

      pe-exanmples-jvm:
        image: streampipes/pe-examples-jvm
        depends_on:
          - "consul"
        environment:
          - STREAMPIPES_HOST=###TODO ADD HOSTNAME HERE ###
        ports:
          - "8096:8090"
        networks:
          spnet:

Description

The Flink Samples Processing Element Container contains some example algorithms that can be used within processing pipelines in the pipeline editor. Those algorithms are deployed to a Flink cluster once the pipeline is started.

Docker Compose

  pe-flink-samples:
    image: streampipes/pe-examples-flink
    depends_on:
      - "consul"
    ports:
      - "8094:8090"
    volumes:
      - ./config:/root/.streampipes
    networks:
      spnet:

Third Party Services

Description

This service can be used to run Elasticsearch. Data can be written into Elasticsearch with the Elasticsearch sink of the PE Flink samples conatiner.

Docker Compose

elasticsearch:
  image: ipe-wim-gitlab.fzi.de:5000/streampipes/services/elasticsearch
  ports:
    - "9200:9200"
    - "9300:9300"
  volumes:
    - ./config/elasticsearch/data:/usr/share/elasticsearch/data
  networks:
    spnet:

Docker Compose

kibana:
  image: kibana:5.2.2
  ports:
    - "5601:5601"
  volumes:
    - ./config/kibana/kibana.yml:/opt/kibana/config/kibana.yml
  environment:
    - ELASTICSEARCH_URL=http://elasticsearch:9200
  networks:
    spnet:

Description

The kafka web console can be used to monitor the kafka cluster. This is a good tool for debugging your newly developed pipeline elements.

Docker Compose

kafka-web-console:
  image: hwestphal/kafka-web-console
  ports:
    - "9000:9000"
  volumes:
    - ./config:/data
  networks:
    spnet: