ParallelM announced a partnership with Cloudera to add
options for bringing machine learning (ML) models from Cloudera ML
development environments, including Cloudera Data Science Workbench
(CDSW) and the upcoming cloud-native Cloudera Machine Learning platform,
into production using ParallelM's MCenter. MCenter allows for
centralized management of ML models taking full advantage of existing
infrastructure investments so Cloudera customers can start deploying AI
applications at scale.
"Automating
the deployment and management of machine learning models in production
is a key part of our strategy to industrialize AI," said Hilary Mason,
General Manager, Machine Learning, Cloudera. "Our customers are asking
for full model lifecycle management including advanced model health
monitoring, and our partnership with ParallelM delivers that and more
while leveraging our customers' investments in Cloudera to help build
the environment for the enterprise AI factories of the future."
The
first step in the integration between CDSW, and later, Cloudera Machine
Learning, with MCenter is a new model deployment connector. With the
new connector, CDSW models are now easily imported in MCenter where they
immediately enter an automated production process where they can be
managed on any cloud or on-premise. MCenter provides full capabilities
for batch, real-time and streaming deployments with integrated model
health monitoring and full model governance to track every detail
regarding the model's use in production. Also, CDSW models deployed in
MCenter can also leverage the CDH infrastructure for processing
including dynamic retraining for streaming or batch predictions. In
addition, with production statistics from MCenter, CDSW users can
further optimize model updates and new model development using actual
production stats, thereby creating a seamless, continuous model
lifecycle from development to production.
"Cloudera
has a clear vision of what the future looks like for AI-driven
companies that leverage investments in big data and put them to work in
actual ML-based applications using Cloudera tools for data science and
machine learning," said Sivan Metzger, CEO of ParallelM. "We are excited
to be part of this vision and to put our industry-leading MLOps
platform, MCenter, to work for Cloudera's customers."
The new MCenter connector is available immediately to Cloudera customers.