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Monasca Analytics (MoNanas) is a statistical/machine-learning (SML) flow composition engine. Users can compose a sequence of algorithms to be executed by just providing a description as an input to MoNanas. The data flow is automatically handled by the framework.
Easy flow composition and reusability means that we can speed up the extraction of actionable infrastructure insight.
:thumbsup: Decouple algorithm design from execution.
:thumbsup: Reusable specification of the desired flow.
:thumbsup: Language independent flow definition.
:thumbsup: Data source and format independent.
:thumbsup: Transparently exploit data parallelism.
See: MoNanas/Design for details on MoNanas’s architecture, its functional requirements and core concepts.
MoNanas uses a number of third-party technologies:
There are multiple ways to contribute to the project. All are equally important to us!
For more information on setting up your development environment, see MoNanas/DevGuide.
For more information about Monanas, please visit the wiki page: Monanas wiki.
And for more information about Monasca, please visit the wiki page: Monasca wiki.
Copyright © 2016 Hewlett Packard Enterprise Development Company, L.P. Licensed under the Apache License, Version 2.0 (the “License”); you may not used this file except in compliance with the License. You may obtain a copy of the License at:
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.