You can find a wide variety of use cases and success stories on MindSphere.io "Made with MindSphere"
There are three ways that you can login to MindSphere the first time:
1. Use the Link from your MindSphere Welcome E-mail.
2. If you know the URL of your Environment, you can type it directly in your Browser.
3. You can also go to MindShere.io and click the login button on the top right of the page (this method is only available to users with a standard IDP webkey). You can login with Webkey and see all Environments listed which you have access to. Chose one.
The user name and passwort will depend on the identity provider (IDP) you use. There are several options for Identity Provider (IDP) Access. Our Standard IDP provider is "Webkey" or you can work with other federateded IDP authorized providers such as Mendix ID or Siemens ID. If your Environment Admin is using the Custom IDP Feature, then you can Login with your own familiar Login window. This will be provided by your own IDP Provider.
You can check our MindSphere Community for Support or customers may contact our Support center. Additional information and videos are also available here: Documentation
Normally you can create a Webkey during the Strat for Free Registration Process. In the Commercial MindSphere deployments, the Welcome E-Mail guides you through the WebKey creation process. If you already own a Webkey account because you are using it for other Siemens Software, you can use your existing webkey to access MindSphere.
MindSphere public versions are available on Azure, AWS and Alibaba. We also offer a private version which is cloud dedicated (VPC) and privately administered (LPC).
Summary of the differences between LPC and VPC:
MindSphere for Private Cloud (LPC) The customer has their own data center & their own infrastructure services and will need to install RedHat OpenShift or Rancher on top of MindSphere.
MindSphere Cloud dedicated (VPC) The customer puts MindSphere on an already existing HyperScaler Account like AWS or Asure.
Yes, You also can deploy MindSphere in your own Azure and AWS account (hyper scaler) (Mindsphere Cloud dedicated (VPC )) or even on your own Datacenter with our Mindsphere for Private Cloud (LPC).
Currently the public Version of MindSphere runs on: AWS, Azure, Alibaba.
Depending on your use case, there are lots of out of the box solutions and Apps available (Apps and Solutions)
Only your organization knows this. The Users and their roles are only visible for the admin in your organization. You have to find out within your organization who owns this role.
Yes you can chose the Mindsphere for Private Cloud (LPC) or the MindSkphere Cloud Dedicated (VPC) to ensure data policies meet the requirements of the respective country. Additionaly you have to make sure that the infrastructure provider offers the required services (please talk to our sales and operations team to verify).
If both options would not work for you, please contect our sales team they will work together with you to find a solution.
This depends on the public version in different locations:
If you choose to host your application using the MindSphere hosting environment, which is based on Cloud Foundry, use the following buildpacks: Java, Node.js, .Net Core, Python, PHP, Go, Ruby, staticfile,binary and Mendix. If you host the app in another infratructure, you are free to choose the programing laguage.
Yes you can use your own IDE.
You can host your applications either on the MindSphere CLoud Foundry application runtime or your own infrastructure.
You can manage your MindSphere applications with MindSphere Developer Cockpit and Operator Cockpit and CloudFoundry CLI (comand line interface).
Yes, MindSphere supports the development and integration of plugins into Operations Insights.
No, MindSphere is mainly focused on multi tenant capable applications which means that the Application runs only in your Production Environment and is only provisioned to your customers through the MindSphere Developer/Operator functionality.
Yes, MindSphere supports the development and integration of plugins into Operations Insights.
Yes, MindSphere Web Components offer exactly that.
Yes, the Mendix academy offers several Learning Paths where this is explained in detail.
Yes, can use non-Siemens hardware and software that supports standard communication protocols and develop your own connectivity solutions to send data to MindSphere. (Using MQTT, MindConnect API, MindConnect LIB and so on)
Beside these possibilities, many Siemens hardware devices and software already can connect easily to MindSphere. Such as MindConnect Nano, MindConnect IoT 2040, MindConnect Software Agent and more.
Yes, you can develop your own hardware. Use our MindConnect Lib SDK with C Programming (see) or the MindConnect API with any programming language of you choice. You can use SDK of your choice and connect to MindSphere using MindConnect MQTT. Or you use the connectivity solution Mindconnect Software Agend (MCSA).
Within our How To section you will find tutorials for onboarding devices via our various connectivity options. (Learn more)
MindSphere is agnostic to machines.
To connect your machines there are a variatiy of hardware and softeware solutions avaiable (see).
Yes, you can use S7, OPC-UA and MQTT protocols for bi-directional communication between MindSphere and your on-site devices/machines using our MindConnect elements such as MindConnect Nano and MindConnect IoT 2040. You can also use MindConnect MQTT for bidirectional communication using your hardware of choice.
All communication to and from MindSphere is secured with TLS v1.2.
Yes, for more information see: MindServices or offerings from our MindSphere partners (MindServices & Partners)
MindConnect Software Agent, MindConnect Nano and MindConnect IoT 2040 can easily be used to connect a Siemens PLC to MindSphere. There are some PLCs such as S7-1500, -1200 that can be connected directly to MindSphere.
This highliy depends on the PLCs and can only be evaluated on a case by case basis.
Different kinds of data can be stored: Timeseries data in our Timeseries database, unstructured data in Integrated Data Lake, files in our file storage. Other data such as log files and events can also be stored in MindSphere.
There are different ingest possibilites for hardware to software solutions. Importing to different storage possibilites includes, for example, IoT Database or Integrated Data lake.
For more information see: How Tos or open source repositories on GitHub (learn more).
You can quickly check if you are connected and data arrives. Here are the two most common ways to check your connection:
1) Within the system tool "Asset Manager", you can check the connection of every onboarded Agent/Device. For detailed information see this document.
2) You can also view incoming data using the Application Operations Insight.
Yes, using MindConnect Integration, data from both cloud and on-premise based systems in your setup can be brought into MindSphere for further contexualization, visualization, and advanced analytics.
Yes with Semantic Data Interconnect (SDI) it is possible to correlate data in Integrated Data Lake and timeseries data from machines providing context to your data.
You can store any kind of data including structured, semi-structured and unstructured data in the Integrated Data Lake.
Yes you can share your S3 resources with our Integrated Data Lake.
Yes.
Yes. Data from AWS/Azure storage services can be brought into MindSphere for contexualization, visualization, and advanced analytics.
Yes. MindConnect Integration has a feature called recipes (configured integration flows) that can be reused for different instances of source and destination systems configured in a recipe.
Yes. MindConnect Integration can read files from your FTP server and then transfer them into MindSphere for contexualization, visualization, and advanced analytics.
Yes. MindConnect Integration allows scheduling of integration workflows.
Yes. MindConnect Integration allows detailed montoring of integration workflows giving details on their status.
Semantic Data Interconnect (SDI) is a framework that enables users to provide a context to IoT, OT and IT data by establishing semantic relationship between different sources.
A semantic layer is a an abstraction of the technical implementation layer. It provides citizen data practitioners with an easy way to understand the data without worrying about the technical complexity and implementation of the underlying data source. The semantic layer presents the underlying data model using familiar domain definitions (dimensions, measures, hierarchies) and easy-to-understand terms.
Yes. Semantic Data Interconnect (SDI) allows you to query contexualized data use the query response for further analysis.
Yes. Query responses from Semantic Data Interconnect are available over REST interface and also available as files in Integrated Data Lake.
Yes. Multiple capabilities in MindSphere such as system integration, transformation, orchestration and contexualization provide users with intuative ways to design, execute and monitor data workflows e.g. Visual Flow Creator also offers a graphical workflow editor that uses drag and drop to connect a collection of preconfigured and local nodes to perform a range a functions.
Yes. With Operations Insights and Visual Flow Creator it is possible to define and save KPIs on timeseries data in MindSphere.
Yes, it is possible to use native tools from Amazon and Microsoft on top of Integrated Data Lake. Details are available in the MindSphere documentation.
Currently, there is no possiblity of connecting on-premise data lakes with MindSphere Integrated Data Lake. However, it is possible to transfer data between MindSphere and on-premise Data Lakes.
Integrated Data Lake supports upload of up to 5 GB on AWS tenants and up to 256 MB for Azure tenants.
Yes, you can import your time series data into the Integrated Data Lake using the Time Series import feature available on the Data Lake.