In this section you will find all currently published services that can be used. This section will be updated regularly as we continuously enrich our ecosystem. Refer to the concepts section for information on the API Versioning and the API Lifecycle in MindSphere.
MindSphere APIs are either HTTP-based or messaging-based. HTTP-based APIs come with an OpenAPI specification, describing the HTTP operations offered by a service to be called by clients. Messaging-based APIs come with an AsyncAPI specification, describing the topics and messages offered by a service to either subscribe to or publish to by a client.
The following tables list all available MindSphere services with a description and the available API versions in the respective regions. By default, API versions are HTTP-based APIs. In case an AsyncAPI is provided the version is annotated accordingly.
Warning
Do not set the ContentType header of GET requests to application/json if the request body is empty. Many firewalls block this as it is identified as invalid request.
Note
MindSphere will adhere to the API request URL validations in the upcoming release. This is a step to make the platform more secure.
The API request URLs will be validated based on the use of trailing slash characters in requests pointing to dedicated resources.
Please refer to the list below which contains examples of incorrect URLs and correct URLs. This will be applicable to all APIs in MindSphere.
Examples of malformed requests
Examples of well-formed requests
GET https://gateway.{region}.{mindsphere-domain}/api/iottsaggregates/v3/aggregates/{assetId}/{aspectName}/
GET https://gateway.{region}.{mindsphere-domain}/api/iottsaggregates/v3/aggregates/{assetId}/{aspectName}
GET https://{tenantName}-assetmanagement.{region}.{mindsphere-domain}/api/assetmanagement/v3/assets/{id}/?includeShared=true
GET https://{tenantName}-assetmanagement.{region}.{mindsphere-domain}/api/assetmanagement/v3/assets/{id}?includeShared=true
PUT https://{tenantName}-assetmanagement.{region}.{mindsphere-domain}/api/assetmanagement/v3/assettypes/{id}/
PUT https://{tenantName}-assetmanagement.{region}.{mindsphere-domain}/api/assetmanagement/v3/assettypes/{id}
Usage Transparency Service offers a UI giving insight on your resource consumption on the MindSphere platform. For Developers it as offers an API to track a metric defined by the developers. This metric can also be retrieved via an API of UTS.
File Service to read, write and delete files: upload, update and delete files associated to assets; store metadata information, and search for files by metadata.
Integrated Data Lake is an application in MindSphere to import and store the historical IoT data, access cross accounts and perform analytics on the data.
Use Time Series to create, read, update and delete dynamic data. Since time series data are always related to an asset, the instance of an asset must have been created by you beforehand.
Use Time Series Aggregates Service to read aggregated time series values. Retrieve the following aggregated values per interval: Count, Sum, Average, Minimum, Maximum, First Value, Last Value,Standard Deviation.
Represent physical assets from your site in MindSphere. Use models and create instances, set relations to others and create structures such as hierarchies.
The Data Exchange Service provides remote file storage and management support through simple REST API calls. The service offers support for uploading, downloading, renaming, and publishing within the same tenant files or folders.
The Event Analytics Service provides the essential functionality for a data-driven analysis of event data. It enables the user to get a better grasp of what is happening inside the system through statistical analysis.
The Job Manager Service allows customers to execute Zeppelin Notebooks using a scheduling mechanism, also providing full support for the execution environment, cleanup, storage and library support required to run the models.
The KPI Calculation Service computes Key Performance Indicators (KPIs) for an asset. It uses data source such as sensors, control events and calendar entries.
The Model Management Service provides analytical model management file storage with versioning support. The service provides help in maintaining version, dependency, parameters and authorship information.
The Signal Calculation Service processes sensor time series data of an entity. The service aggregates, modifies, smoothes and transforms the original sensor data for further analysis or storage along with the original data.
The Trend Prediction Service predicts future values for time series using linear and non-linear regression models. It is a forecasting framework, that has many useful applications in the area of Process & Condition Monitoring.