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.
- Python 3.6, postgresql 10;
- yum install python36-pip and python36-devel;
- 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
docker-compose up
docker exec -it pk1-app /bin/bash
pk1 setup --database pk1:pk1:pk1-pg:5432:pk1
pk1 start [--listening 127.0.0.1:11001]
open https://127.0.0.1:11001/clouds/cloud/add/, and fill the form like:
open https://127.0.0.1:11001/engines/cluster/add/, and fill the form like:
open https://127.0.0.1:11001/engines/cluster/, select the target clusters, and click the following materialize.../scale... link:
Similar to Step 2, open https://127.0.0.1:11001/clouds/cloud/add/, but choose a scale whose name without 'boostrap'.
pk1 stop
pk1 uninstall
National Key Research Program of China: Scientific Big Data Management System (No.2016YFB1000600)