Environment Setup

Built with Love and Scale by ex-Netflix, Databricks, and Tensorflow Engineers

Videos

Continuously Train & Deploy Spark ML and Tensorflow AI Models from Jupyter Notebook to Production (StartupML Conference Jan 2017)
Recent Advancements in Data Science Workflows: From Jupyter-based Notebook to NetflixOSS-based Production (Big Data Spain Nov 2016)

Reference Architecture

100% Open Source

Completely Kubernetes and Docker Based

PMML + Native C++/Java Code Generation for Optimized CPU/GPU Performance

Deploy directly from Jupyter Notebook to Hybrid-Cloud Microservices

NetflixOSS-based Microservices for High Scalability and Availability

Continuous Train/Deploy Spark ML and Tensorflow AI Pipelines to Production

KINESIS

Environment Setup

Pipeline on Mini (Local Laptop)

Small Kubernetes cluster for your laptop

Pipeline on AWS

Kubernetes cluster on any cloud provider or on-premise

Pipeline on Google

Kubernetes cluster across many cloud providers and/or on-premise

PipelineIO on Azure

Global 24x7 Support for Everyone!

Create a Ticket
Email help@pipeline.io

Name		Name	Last commit message	Last commit date
Latest commit History 1,766 Commits
apachespark.ml		apachespark.ml
api.ml		api.ml
cassandra.ml		cassandra.ml
chaosmonkey.ml		chaosmonkey.ml
clustered.ml		clustered.ml
dashboard.ml		dashboard.ml
databricks.ml		databricks.ml
education.ml		education.ml
elasticsearch.ml		elasticsearch.ml
explore.ml		explore.ml
gpu.ml		gpu.ml
hdfs.ml		hdfs.ml
jupyterhub.ml		jupyterhub.ml
keyvalue.ml		keyvalue.ml
kibana.ml		kibana.ml
kubernetes.ml		kubernetes.ml
loadtest.ml		loadtest.ml
metastore.ml		metastore.ml
metrics.ml		metrics.ml
online.ml		online.ml
oreilly.ml		oreilly.ml
package.ml		package.ml
prediction.ml		prediction.ml
presto.ml		presto.ml
scheduler.ml		scheduler.ml
scripts		scripts
sql.ml		sql.ml
stream.ml		stream.ml
web.ml		web.ml
zeppelin.ml		zeppelin.ml
zookeeper.ml		zookeeper.ml
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md

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xuezhizeng/pipeline

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Built with Love and Scale by ex-Netflix, Databricks, and Tensorflow Engineers

Videos

Reference Architecture

100% Open Source

Completely Kubernetes and Docker Based

PMML + Native C++/Java Code Generation for Optimized CPU/GPU Performance

Deploy directly from Jupyter Notebook to Hybrid-Cloud Microservices

NetflixOSS-based Microservices for High Scalability and Availability

Continuous Train/Deploy Spark ML and Tensorflow AI Pipelines to Production

Environment Setup

Pipeline on Mini (Local Laptop)

Pipeline on AWS

Pipeline on Google

PipelineIO on Azure

Global 24x7 Support for Everyone!

Additional Resources

Training Repo and Workshop Schedule

Global Advanced Spark and Tensorflow Meetup

Slideshare Slides

YouTube Videos

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