Introduction

PackOne provides a set of consistent interfaces of resources management of heterogeneous clouds. Resources include virtual machines, containers, storage volumes, etc. Clouds include OpenStack, H3CloudOS, EVCloud, CSTCloud, etc. It can bootstrap a big data cluster from scratch in a few clicks, and materialize the cluster into cloud images to boost following cluster creating procedures. Besides, PackOne can scale-out/in clusters by only one click.

This software is inspired by the “serverless” trend in cloud computing and big data processing, with the ambitions to bridge the IaaS to Apache Ambari seamlessly and coordinate Ambari Services into an elastic high-level workspace. Currently, It support to deploy and scale out Hadoop, Spark, Hive, Neo4j, MongoDB, Kylin, Redis and many other clustering software in several clicks or api callings.

Install method 1：Native

  1. Python 3.6, postgresql 10;
  2. yum install python36-pip and python36-devel;
  3. Create a postgresql db with its information (db_user, db_passwd, db_host, db_port, db_name) collected.

Then run:

pip3.6 install pk1

pip3.6 install -U pip setuptools

pk1 setup --database db_user:db_passwd:db_host:db_port:db_name

Install method 2：Docker

docker-compose up

docker exec -it pk1-app /bin/bash

pk1 setup --database pk1:pk1:pk1-pg:5432:pk1

Start Service

pk1 start [–listening 127.0.0.1:11001]

Access Service

https://127.0.0.1:11001/admin

Step 1: Add Cloud (OpenStack, for example)

open http://127.0.0.1:11001/clouds/cloud/add/, and fill the form like:

Step 2: Bootstrap an Ambari cluster

open http://127.0.0.1:11001/engines/cluster/add/, and fill the form like:

Step 3: Materialize/Scale clusters

open http://127.0.0.1:11001/engines/cluster/, select the target clusters, and click the following materialize…/scale… link:

Step 4: Boost cluster creation

Similar to Step 2, open http://127.0.0.1:11001/clouds/cloud/add/, but choose a scale whose name without ‘boostrap’.

Stop

pk1 stop

Uninstall

pk1 uninstall

Acknowledge

National Key Research Program of China: Scientific Big Data Management System (No.2016YFB1000600)