Release Notes - Developer Documentation
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30th April 2021


We have worked hard to deliver a great MindSphere Private Standard experience, but we are still tracking some known issues. If you find others, please give us your feedback by contacting our MindSphere Support.

We recommend that you read the following release notes carefully. These notes contain important information for installation and use.

These release notes are relevant for MindSphere Private Standard Release in April 2021 with version V2103.LR.GBL.N0331/ V2103.LO.GBL.N0331.

MindSphere Private Standard

Within this release of MindSphere Private Cloud, the the Operations Insight, Usage transparency services, Integrated data lake and Predictive learning essentials are available in addition to the other services. These services are part of the standard package offering of MindSphere Private Cloud.

Operations Insight

Operations Insight is a MindSphere application that allows you to monitor your production lines and machines. With easy-to-use configurations, it is possible to monitor the performance and condition of the assets in real time, get full and harmonized transparency of the data from their connected assets and gain deeper insights into your production system and analyze the machine performance.

Operations Insight is a MindSphere solution. Operations Insight is an easy-to-use basic analytics application of time series data that enables the user to gain deeper insights into their production system and the machine performance. Operations Insight uses the MindSphere assets, aspects and variables as data model for its functions.

Operations Insight offers you the following functions:

  • Management, monitoring and representation of the assets distributed worldwide.
  • Visualize raw and aggregated timeseries data
  • Creation of rules for monitoring the assets
  • Visualization of asset relevant information on the Dashboard page
  • Comparison of variables of assets that enables analysis of the assets performance
  • Creating and analyzing the KPIs of different aspects
  • Creating and tracking of work orders related to specific assets

Usage Transparency

Usage Transparency is a component of MindSphere, the industrial IoT platform from Siemens. Usage Transparency collects various consumption data (metrics) on the MindSphere platform. It allows customers to access resource consumption metrics for tenant, view usage details for a specific time period and generate usage reports. The dashboards allow the users to access required usage metrics for a specific time period. Also, users can generate usage reports in the .csv file format for further analysis.

Notification Service

The Notification Service provides interfaces to communicate and share information among the users of MindSphere via e-mail. E-mails can be supported with attachments as an optional feature. Attachments and URLs in the content of e-mail would not be scanned.

Predictive learning essentials

Predictive learning essentials allows customers to run analysis that can help you anticipate upcoming events and predict when issues might arise. This will allow you to boost product quality and proactively reduce failures. Using predictive learning essentials, customer can enhance product performance by intervening with preventive maintenance and disrupt fatal sequence of manufacturing events.

Predictive Learning Essential Features:

  • User can develop and execute models using pre-provisioned Jupyter environments.
  • User can write models in python scripts to call MindSphere API's. User need to call data source specific MindSphere API's to use data sources like IoT, Data lake and Data exchange. Once the model development and execution is done, then user has to save the Jupyter notebook on the local machine before stopping the environment.
  • Jupyter notebook stored on the environment will not be permanently persisted.

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Last update: March 23, 2023