An orchestration platform for Docker containers running data mining algorithms.

This project exposes a web interface to execute on demand data mining algorithms defined in Docker containers and implemented using any tool or language (R, Python, Java and more are supported).

It relies on a runtime environment containing Mesos and Chronos to control and execute the Docker containers over a cluster.

 docker run --rm --env [list of environment variables] --link woken hbpmip/woken:3.0.2

where the environment variables are:

• CLUSTER_IP: Name of this server advertised in the Akka cluster
• CLUSTER_PORT: Port of this server advertised in the Akka cluster
• CLUSTER_NAME: Name of Woken cluster, default to 'woken'
• WOKEN_PORT_8088_TCP_ADDR: Address of Woken master server
• WOKEN_PORT_8088_TCP_PORT: Port of Woken master server, default to 8088
• DOCKER_BRIDGE_NETWORK: Name of the Docker bridge network. Default to 'bridge'
• NETWORK_INTERFACE: IP address for listening to incoming HTTP connections. Default to '0.0.0.0'
• WEB_SERVICES_PORT: Port for the HTTP server in Docker container. Default to 8087
• WEB_SERVICES_SECURE: If yes, HTTPS with a custom certificate will be used. Default to no.
• WEB_SERVICES_USER: Name used to protected the web servers protected with HTTP basic authentication. Default to 'admin'
• WEB_SERVICES_PASSWORD: Password used to protected the web servers protected with HTTP basic authentication.
• LOG_LEVEL: Level for logs on standard output, default to WARNING
• LOG_CONFIG: on/off - log configuration on start, default to off
• VALIDATION_MIN_SERVERS: minimum number of servers with the 'validation' functionality in the cluster, default to 0
• SCORING_MIN_SERVERS: minimum number of servers with the 'scoring' functionality in the cluster, default to 0
• KAMON_ENABLED: enable monitoring with Kamon, default to no
• ZIPKIN_ENABLED: enable reporting traces to Zipkin, default to no. Requires Kamon enabled.
• ZIPKIN_IP: IP address to Zipkin server. Requires Kamon and Zipkin enabled.
• ZIPKIN_PORT: Port to Zipkin server. Requires Kamon and Zipkin enabled.
• PROMETHEUS_ENABLED: enable reporting metrics to Prometheus, default to no. Requires Kamon enabled.
• PROMETHEUS_IP: IP address to Prometheus server. Requires Kamon and Prometheus enabled.
• PROMETHEUS_PORT: Port to Prometheus server. Requires Kamon and Prometheus enabled.
• SIGAR_SYSTEM_METRICS: Enable collection of metrics of the system using Sigar native library, default to no. Requires Kamon enabled.
• JVM_SYSTEM_METRICS: Enable collection of metrics of the JVM using JMX, default to no. Requires Kamon enabled.
• MINING_LIMIT: Maximum number of concurrent mining operations. Default to 100
• EXPERIMENT_LIMIT: Maximum number of concurrent experiments. Default to 100
• RELEASE_STAGE: Release stage used when reporting errors to Bugsnag. Values are dev, staging, production
• DATA_CENTER_LOCATION: Location of the datacenter, used when reporting errors to Bugsnag
• CONTAINER_ORCHESTRATION: Container orchestration system used to execute the Docker containers. Values are mesos, docker-compose, kubernetes

Follow these steps to get started:

1. Git-clone this repository.

  git clone https://github.com/LREN-CHUV/woken.git

2. Change directory into your clone:

  cd woken

3. Build the application

You need the following software installed:

• Docker 18.09 or better with docker-compose

  ./build.sh

4. Run the application

You need the following software installed to execute some tests:

• Httppie

  cd tests
  ./run.sh

tests/run.sh uses docker-compose to start a full environment with Mesos, Zookeeper and Chronos, all of those are required for the proper execution of Woken.

5. Create a DNS alias in /etc/hosts

  127.0.0.1       localhost frontend

6. Browse to http://frontend:8087 or run one of the query* script located in folder 'tests'.

The Docker containers that can be executed on this platform require a few specific features.

TODO: define those features - parameters passed as environment variables, in and out directories, entrypoint with a 'compute command', ...

The project algorithm-repository contains the Docker images that can be used with woken.

Performs a data mining task.

Path: /mining/job Verb: POST

Takes a Json document in the body, returns a Json document.

Json input should be of the form:

  {
    "user": {"code": "user1"},
    "variables": [{"code": "var1"}],
    "covariables": [{"code": "var2"},{"code": "var3"}],
    "grouping": [{"code": "var4"}],
    "filters": [],
    "algorithm": "",
    "datasets": [{"code": "dataset1"},{"code": "dataset2"}]
  }

where:

• variables is the list of variables
• covariables is the list of covariables
• grouping is the list of variables to group together
• filters is the list of filters. The format used here is coming from JQuery QueryBuilder filters, for example {"condition":"AND","rules":[{"id":"FULLNAME", "field":"FULLNAME","type":"string","input":"text","operator":"equal","value":"Isaac Fulmer"}],"valid":true}
• datasets is an optional list of datasets, it can be used in distributed mode to select the nodes to query and in all cases add a filter rule of type {"condition":"OR","rules":[{"field":"dataset","operator","equals","value":"dataset1"},{"field":"dataset","operator","equals","value":"dataset2"}]}
• algorithm is the algorithm to use.

Currently, the following algorithms are supported:

• data: returns the raw data matching the query
• linearRegression: performs a linear regression
• summaryStatistics: performs a summary statistics than can be used to draw box plots.
• knn
• naiveBayes

Performs an experiment comprised of several data mining tasks and an optional cross-validation step used to compute the fitness of each algorithm and select the best result.

TODO: document API

You need the following software installed:

• Bumpversion
• Precommit

Execute the following commands to distribute Woken as a Docker container:

  ./publish.sh

For production, woken requires Mesos and Chronos. To install them, you can use either:

• mip-microservices-infrastructure, a collection of Ansible scripts deploying a full Mesos stack on Ubuntu servers.
• mantl.io, a microservice infrstructure by Cisco, based on Mesos.
• Mesosphere DCOS DC/OS (the datacenter operating system) is an open-source, distributed operating system based on the Apache Mesos distributed systems kernel.

Woken :

• the Woken river in China - we were looking for rivers in China
• passive form of awake - it launches Docker containers and computations
• workflow - the previous name, not too different

This work has been funded by the European Union Seventh Framework Program (FP7/2007­2013) under grant agreement no. 604102 (HBP)

This work is part of SP8 of the Human Brain Project (SGA1).

Thanks for the generous support of who offered us a Standard plan allowing us to inspect and report efficiently errors in our software.

We use the following tools for development:

• IntelliJ IDEA
• to report errors in real time to our development team
• CircleCI for continuous integration