Morpheus not "Morpheus SDK" (nv-morpheus#534)

* Morpheus is an SDK, "Morpheus SDK" and "Morpheus SDK Client" are redundant
* We do have a helm chart named `morpheus-sdk-client`, so references to the helm chart retain the "sdk client".
* Update elevator pitch paragraph in `docs/source/index.rst` to match that of the `README.md`
* Add license comment to `README.md` and `CONTRIBUTING.md` files
* Includes changes from PR nv-morpheus#522

relates to issue nv-morpheus#495

Authors:
  - David Gardner (https://github.com/dagardner-nv)

Approvers:
  - Michael Demoret (https://github.com/mdemoret-nv)

URL: nv-morpheus#534

CONTRIBUTING.md

@@ -1,3 +1,20 @@
+<!--
+SPDX-FileCopyrightText: Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+SPDX-License-Identifier: Apache-2.0
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+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.
+-->
+
 # Contributing to Morpheus
 
 Contributions to Morpheus fall into the following three categories.

README.md

@@ -1,3 +1,20 @@
+<!--
+SPDX-FileCopyrightText: Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+SPDX-License-Identifier: Apache-2.0
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+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.
+-->
+
 ![NVIDIA Morpheus](./img/morpheus-banner.png "Morpheus banner image")
 
 # NVIDIA Morpheus

docs/source/cloud_deployment_guide.md

@@ -48,7 +48,7 @@ limitations under the License.
   - [Installing Cloud Native Core Stack on NVIDIA Certified Systems](#installing-cloud-native-core-stack-on-nvidia-certified-systems)
 - [Appendix B](#appendix-b)
   - [Kafka Topic Commands](#kafka-topic-commands)
-  - [Using Morpheus SDK Client to Run Pipelines](#using-morpheus-sdk-client-to-run-pipelines)
+  - [Using Morpheus to Run Pipelines](#using-morpheus-to-run-pipelines)
 - [Appendix C](#appendix-c)
   - [Additional Documentation](#additional-documentation)
   - [Troubleshooting](#troubleshooting)
@@ -440,7 +440,7 @@ To publish messages to a Kafka topic, we need to copy datasets to locations wher
 kubectl -n $NAMESPACE exec sdk-cli-helper -- cp -R /workspace/examples/data /common
 ```
 
-Refer to the Using Morpheus SDK Client to Run Pipelines section of the Appendix for more information regarding the commands.
+Refer to the [Using Morpheus to Run Pipelines](#using-morpheus-to-run-pipelines) section of the Appendix for more information regarding the commands.
 
 **Note**: Before running the example pipelines, ensure that the criteria below are met:
 -   Ensure that models specific to the pipeline are deployed.
@@ -821,9 +821,9 @@ kubectl -n $NAMESPACE exec deploy/broker -c broker -- kafka-topics.sh \
       --topic <YOUR_KAFKA_TOPIC>
 ```
 
-### Using Morpheus SDK Client to Run Pipelines
+### Using Morpheus to Run Pipelines
 
-The Morpheus SDK client allows you to configure several supported pipelines and provides flexibility to execute the pipeline in multithread mode.
+Morpheus allows you to configure several supported pipelines and provides flexibility to execute the pipeline in multithread mode.
 
 ```bash
 (morpheus) root@sdk-cli:/workspace# morpheus run --help
@@ -859,7 +859,7 @@ Four different pipelines are currently supported: a pipeline running an NLP mode
 For details of running `pipeline-other`, please refer to the GNN Fraud Detection use case in the `examples` source directory.
 
 
-The Morpheus SDK Client provides the commands below to run the NLP pipeline:
+The Morpheus command line tool provides the commands below to run the NLP pipeline:
 
 ```bash
 (morpheus) root@sdk-cli:/workspace# morpheus run pipeline-nlp --help
@@ -917,7 +917,7 @@ Commands:
   validate      Validate pipeline output for testing.
 ```
 
-Morpheus SDK Client provides the commands below to run the FIL pipeline:
+The Morpheus command line tool provides the commands below to run the FIL pipeline:
 
 ```bash
 (morpheus) root@sdk-cli:/workspace# morpheus run pipeline-fil --help
@@ -973,7 +973,7 @@ Commands:
   validate        Validate pipeline output for testing.
 ```
 
-Morpheus SDK Client provides the commands below to run the AutoEncoder pipeline:
+The Morpheus command line tool provides the commands below to run the AutoEncoder pipeline:
 
 ```bash
 (morpheus) root@sdk-cli:/workspace# morpheus run pipeline-ae --help

docs/source/developer_guide/guides/5_digital_fingerprinting.md

@@ -28,7 +28,7 @@ The data we will want to use for the training and inference will be any sensitiv
 The location of these logs could be either local to the machine running Morpheus, a shared file system like NFS or on a remote store such as [Amazon S3](https://aws.amazon.com/s3/).
 
 ### Defining a New Data Source
-Additional data sources and remote stores can easily be added using the Morpheus SDK.  The key to applying DFP to a new data source is through the process of feature selection. Any data source can be fed into DFP after some preprocessing to get a feature vector per log/data point​.  In order to build a targeted model for each entity (user/service/machine... etc.), the chosen data source needs a field that uniquely identifies the entity we're trying to model.
+Additional data sources and remote stores can easily be added using the Morpheus API.  The key to applying DFP to a new data source is through the process of feature selection. Any data source can be fed into DFP after some preprocessing to get a feature vector per log/data point.  In order to build a targeted model for each entity (user/service/machine... etc.), the chosen data source needs a field that uniquely identifies the entity we're trying to model.
 
 Adding a new source for the DFP pipeline requires defining five critical pieces:
 1. The user_id column in the Morpheus config attribute `ae.userid_column_name`. This can be any column which uniquely identifies the user, account or service being fingerprinted. Examples of possible user_ids could be:

docs/source/getting_started.md

@@ -1,6 +1,6 @@
 # Getting Started with Morpheus
 There are three ways to get started with Morpheus:
-- Using pre-built Docker containers
+- [Using pre-built Docker containers](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/morpheus/collections/morpheus_)
 - Building the Morpheus Docker container
 - Building Morpheus from source
 

docs/source/index.rst

@@ -23,10 +23,7 @@
 Welcome to Morpheus Documentation
 =================================
 
-NVIDIA Morpheus is an open AI application framework that provides cybersecurity developers with a highly optimized AI
-pipeline and pre-trained AI capabilities that, for the first time, allow them to instantaneously inspect all IP traffic
-across their data center fabric. Bringing a new level of security to data centers, Morpheus provides dynamic protection,
-real-time telemetry, adaptive policies, and cyber defenses for detecting and remediating cybersecurity threats.
+NVIDIA Morpheus is an open AI application framework that provides cybersecurity developers with a highly optimized AI framework and pre-trained AI capabilities that allow them to instantaneously inspect all IP traffic across their data center fabric. The Morpheus developer framework allows teams to build their own optimized pipelines that address cybersecurity and information security use cases. Bringing a new level of security to data centers, Morpheus provides development capabilities around dynamic protection, real-time telemetry, adaptive policies, and cyber defenses for detecting and remediating cybersecurity threats.
 
 Features
 --------

examples/digital_fingerprinting/production/README.md

@@ -168,7 +168,7 @@ MLflow for this production digital fingerprint use case can be installed from NG
 
 The deployment of the [Morpheus SDK Client](../../../docs/source/cloud_deployment_guide.md#install-morpheus-sdk-client) is also done _almost_ the same way as what's specified in the Quick Start Guide. However, you would specify command arguments differently for this production DFP use case.
 
-NOTE: The published SDK image includes a minimal set of packages for launching JupyterLab but you will likely still want to update the conda environment inside the running pod with the `conda_env.yml` file in this same directory to install other use case dependencies such as boto3 and s3fs.
+NOTE: The published Morpheus image includes a minimal set of packages for launching JupyterLab but you will likely still want to update the conda environment inside the running pod with the `conda_env.yml` file in this same directory to install other use case dependencies such as boto3 and s3fs.
 
 #### Notebooks
 

examples/log_parsing/README.md

@@ -16,7 +16,7 @@
 
 # Example cyBERT Morpheus Pipeline for Apache Log Parsing
 
-Example Morpheus pipeline using Docker containers for Triton Inference server and Morpheus SDK/Client.
+Example Morpheus pipeline using Triton Inference server and Morpheus.
 
 ### Set up Triton Inference Server
 

examples/ransomware_detection/README.md

@@ -17,7 +17,7 @@ limitations under the License.
 
 # Example Ransomware Detection Morpheus Pipeline for AppShield Data
 
-Example Morpheus pipeline using Docker containers for Triton Inference server and Morpheus SDK/Client.
+Example Morpheus pipeline using Triton Inference server and Morpheus.
 
 ## Setup Triton Inference Server