IoT & Connectivity Tips

Video Author:                      Stefan Taka Original Post Date:            June 6, 2016   Description: In part 2 of the ThingWorx REST API tutorial, we will demonstrate various common uses of the ThingWorx REST API.      

    Use Analytics Manager to automatically perform engine analytical calculations.   Guide Concept   This guide will use ThingWorx Analytics Manager to compare external-data from an Edge MicroServer (EMS) "Engine Simulator" to a previously-built analytical model.   Following the steps in this guide, you will learn how to deploy the model which you created in the earlier Builder guide.   We will teach you how to utilize this deployed model to investigate whether or not live data indicates a potential engine failure.   You'll learn how to   Deploy and execute computational models Define and trigger Analysis Events Map incoming data to the Model Map analytic outputs to applications   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete this guide is 60 minutes       Step 1: Scenario   In this guide, we're continuing the same MotorCo scenario, where an engine can fail catastrophically in a low-grease condition.   In previous guides, you've gathered and exported engine vibration-data from an Edge MicroServer (EMS) and used it to build an engine analytics model.   The goal of this guide is to now operationalize that previously-created model to analyze individual, external readings to see if the "low grease" condition is currently happening.     Analytical model creation can be extremely helpful for the automotive segment in particular. For instance, each car that comes off the factory line could have an EMS constantly sending data from which an analytical model could automatically detect engine trouble.   This could enable your company to offer an engine monitoring subscription service to your customers.   This guide will show you how to put an analytic model of your engine into service to actively monitor performance.       Step 2: Configure Provider   In ThingWorx terminology, an Analysis Provider is a mathematical analysis engine.   Analytics Manager can use a variety of Providers, such as Excel, Mathcad, or even Analytics Server pre-built ones.   In this guide, we use the built-in AnalyticsServerConnector, a Provider that has been specifically created to work seamlessly in Manager and to use Builder Models.   From the ThingWorx Composer Analytics tab, click Analytics Manager > Analysis Providers > New....   In the Provider Name field, type Vibration_Provider. In the Connector field, search for and select TW.AnalysisServices.AnalyticsServer.AnalyticsServerConnector.   Leave the rest of the options at default and click Save.     Step 3: Publish Analysis Model   Once you have configured an Analysis Provider, you can publish Models from Analytics Builder to Analytics Manager. On the ThingWorx Composer Analytics tab, click Analytics Builder > Models.   Select vibration_model_s1_only and click Publish.   On the Publish Model? pop-up, click Yes. A new browser tab will open with the Analytics Manager's Analysis Models menu. Close that new browser tab, and instead click Analysis Models in the ThingWorx Composer Analytics navigation. This is the same interface as the auto-opened tab which you closed.   Click the model to select it. At the top, click Enable. Note the pop-up indicating that the Enable was successful.       Step 4: Modify EdgeThing   In previous guides in this Vehicle Predictive Pre-Failure Detection Learning Path, you have created various Entities, including Things such as EdgeThing.   In order to automate the process of pushing data from EdgeThing to Analytics Manager, we need to add a few more Properties to EdgeThing.   These Properties are simple STRING variables, and we'll also set Default Values for them to configure parameters of Analytics Manager.   The first is causalTechnique, which tells Analytics Manager which criteria to use when measuring the impact of a feature on a range of goal values.   The second is goalField, which is simply the data field for which Analytics Manager should try to identify the correlation. In this case, it'll be our primary issue, i.e. low_grease.   It is not mandatory that these suggested Property names match, but they are the names used within ThingWorx Analytics. You could use any Property name you wanted, as you'll be mapping from a particular Property to the functionality within Analytics in a later step.   Return to EdgeThing > Properties and Alerts.   Click + Add.   In the Name field, type causalTechnique. Check Has Default Value. In the text field under "Has Default Value", type FULL_RANGE. Note that you MUST type FULL_RANGE, including capitalization, as that is a command within Analytics Server.   Click the "Check with a +" icon for Done and Add. In the Name field, type goalField. Check Has Default Value. In the text field under "Has Default Value", type low_grease. Note that you MUST type low_grease, including being all lower-case, as that is the exact name of the Analytics Server goal.   Click the "Check" icon for Done. Click Save.   Results Storage   We also need a place in which to store the results that Analytics Manager returns. We'll utilize a few additional Properties for that as well.   On the EdgeThing > Properties and Alerts tab, click + Add. In the Name field, type Result_low_grease. Check the Base Type to BOOLEAN. Check Persistent.   Click the "Check with a +" icon for Done and Add. In the Name field, type Result_low_grease_mo. Change the Base Type to NUMBER. Check Persistent.   Click the "Check" icon for Done. Click Save.       Step 5: Create Event   Events are automatic analysis jobs which are submitted based on a pre-defined condition. In this step, we'll configure an Analysis Event, which will execute automatically whenever there is a data-change in our simulated engine.   On the ThingWorx Composer Analytics tab, click Analytics Manager > Analysis Events.   Click New.... If not already selected, change Source Type (Required) to Thing.   In Source, search for and select EdgeThing. In Event, select DataChange. In Property, select s1_fb1. If there are multiple s1_fb1 Properties, select the first one, as the second one is the s1_fb1 entry in the Info Table Property. In Provider Name, select Vibration_Provider. In Model Name, select the published Model.   Click Save.       Click here to view Part 2 of this guide.  

Applicable Releases: ThingWorx Platform 7.0 to 8.5   Description:   Concepts and methodology to design a data model using an use case as example The following topics are covered: Real-world Product Example ThingWorx Terminology and concepts Formulate an implementation Strategy       Related Success Service

  Create Your Application Guide UI Part 4    Step 6: Apply Services   You now have an idea of what your Mashup will look like, but without Data Services, it won't accomplish anything productive. In the following steps you'll apply Mashup Data Services to the Widgets.   Add Data Services   Click the + button in the top-right in the Data tab.   In the Entity Filter field, search for and select MBQSThing. In the Select Services field, search for and select GetPropertyValues. Check the Execute on Load checkbox for GetPropertyValues. In the Services Filter field, search for and select SetProperties. In this case, you WILL NOT check the box for Mashup Loaded? because we do not want to call this Service upon initial Mashup load. 6. Click Done. Both the GetPropertyValues and SetProperties Services now appears under the Data tab as well. 7. Click Save.   GetPropertyValues   GetPropertyValues has brought all the values of our Thing's Properties into the Mashup. Now let's tie these values to the Widgets. Expand All Data under the GetPropertyValues Service on the right under the Data tab.   Drag-and-drop Gears_Count onto the textfield-gears-count Widget.   On the Select Binding Target pop-up, click Text.   Repeat Steps 2 and 3, binding Pistons_Count to textfield-pistons-count and Wheels_Count to textfield-wheels-count. Drag-and-drop Gears_Count_Manually_Set onto the checkbox-gears-manual Widget.   On the Select Binding Target pop-up, click State.   Repeat Steps 5 and 6, binding Pistons_Count_Manually_Set to checkbox-pistons-manual and Wheels_Count_Manually_Set to checkbox-wheels-manual. Click Save.   SetProperties   We want to tie the Widgets to the SetProperties Service to manually set the inventory counts in case something has gone wrong with our IoT sensors in the warehouse. On the right under the Data tab, minimize the GetPropertyValues Service and expand the SetProperties Service.        2. Click the textfield-gears-count Widget to select it. 3. Click the top-left drop-down of the TextBox to expand the options. 4. Drag-and-drop Text onto SetProperties > Gears_Count. 5. Repeat Steps 2 through 4, binding Text from textfield-pistons-count onto Pistons_Count and textfield-wheels-count onto Wheels_Count. 6. Click the checkbox-gears-manual Widget to select it. 7. Click the top-left drop-down of the Checkbox to expand the options. 8. Drag-and-drop State onto Gears_Count_Manually_Set. 9. Repeat Steps 6 through 8, binding State from both checkbox-pistons-manual to Pistons_Count_Manually_Set and checkbox-wheels-manual to Wheels_Count_Manually_Set. 10. Click the button-manual-set Widget to select it. 11. Click the top-left drop-down of the Button to expand the options. 12. Drag-and-drop the Clicked Event onto SetProperties under the Data tab. NOTE: The previous steps in this section where we bound Widgets to Properties simply defined what-goes-where in terms of storing the values into the ThingWorx Foundation backend.To actually push those values, the SetProperties Service itself must be called. 13. With the SetProperties Service selected, drag-and-drop SetProperties' ServiceInvokeCompleted Event (in the bottom-right Data Properties section) onto the GetPropertyValues Service (in the top-right Data tab). If you don't see ServiceInvokeCompleted, ensure that you have the Data Properties tab selected. This will cause the GUI to update once the new values have been saved to the platform’s backend. 14. Click Save.   Manual Data Retrieval   We want to tie a Button to GetPropertyValues to update the GUI with the backend's ever-changing inventory counts without requiring a page reload. Click button-manual-retrieve to select it. Click the top-left drop-down of this Button Widget to expand the options. Drag-and-drop the Clicked Event onto the GetPropertyValues Service. This will create another way to update the part counts in the GUI, other than reloading the page. 4. Click Save.   Click here to view Part 5 of this guide. 

    Learn how ThingWorx can be deployed in a clustered environment   Guide Concept   Web applications have increased reliability and performance by using a "pool" of independent servers called a cluster. It is important to understand what benefits the different methods of clustering provide, and what the different methods can mean for your system.   ThingWorx Foundation can be deployed in either an Active-Active clustered architecture or a standard single-server deployment. This guide describes the benefits of an Active-Active clustered architecture over other clustering methods and provides a system administrator with resources to navigate the different architecture options.     You'll learn how to   Overview of different server clustering techniques Pros and cons of the different clustering configurations that can be used with ThingWorx Where to find detailed information about ThingWorx server clustering   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete this guide is 30 minutes       Step 1: Clustering Overview   Clustering is the most common technique used by web applications to achieve high availability. By provisioning redundant software and hardware, clustering software can automatically handle failures and immediately make the application available on the standby system without requiring administrative intervention.   Depending on the business requirements for High Availability, clusters can be configured in any of the following configurations:    Cluster Configuration           Description                                                                                       Recovery Time Cold Standby Software is installed and configured on a back-up server when the primary system fails. Hours Active-Passive A second server is provisioned with a duplicate of all software components and is started in case of failure of the primary server. Minutes Hot Standby Duplicate software is installed and running on both primary and secondary servers. The secondary server does not process any data when the primary server is functional. Seconds Active-Active Both the primary and one or more secondary servers are active and processing data in parallel. Data is continuously replicated across all running servers. Instantaneous   Cold Standby   ThingWorx installed in a default single-server configuration is not inherently a cold standby system. Periodic system backups can be used to bring the system back online in the event of system failure.   Note: A cold standby configuration does not constitute high availability   Active-Passive   High availability can be achieved with an Active-Passive configuration.     One “active” ThingWorx server performs all processing and maintains the live connections to other systems such as databases and connected assets. Meanwhile, in parallel, there is a second “passive” ThingWorx server that is a mirror image and regularly updated with data but does not maintain active connections to any of the other systems.   If the “active” ThingWorx server fails, the “passive” ThingWorx server is made the primary server, but this can take a few minutes to establish connections to the other systems.   Active-Active   ThingWorx uses Active-Active architecture for achieving high availability.   Active-Active configuration differs from Active-Passive in that all the ThingWorx servers in the cluster are “active.” Not only is data mirrored across all ThingWorx servers, but also all servers maintain live connections with the other systems. This way, if any of the ThingWorx servers fail, the other ThingWorx servers take over instantaneously with no recovery time.   Because all ThingWorx servers are active and processing data in parallel, the cluster can handle higher loads than the single running server in an Active-Passive configuration. An Active-Active deployment leverages the investment made in multiple servers by providing not only greater reliabilility, but also giving the ability to handle demand spikes. When server utilizations exceed 50%, customers can easily scale their deployment by adding more ThingWorx servers to the cluster - horizontally scaling. This also avoids the limitations of vertically scaling - provisioning a single server with more and more CPU cores and RAM.   Benefits of Active-Active Clustering   Higher Availability You can avoid single points of failure and configure the ThingWorx Foundation platform in an Active-Active cluster mode to achieve the highest availability for your IIoT systems and applications. Increased Scalability You can horizontally scale from one to many ThingWorx servers to easily manage large amounts of your IIoT data at scale more smoothly than ever before.     Step 2: ThingWorx Active-Active Architecture   An Active-Active Cluster configuration introduce two software components and two components that are optional in a standard ThingWorx architecture are now required.   The reference architecture diagram below shows ThingWorx deployed with multiple ThingWorx Foundation servers configured in an Active-Active Cluster deployment.   Note: This is an example of a possible ThingWorx deployment. The business requirements of an application will determine the specific configuration in an Active-Active clustered environment.   Load balancer was optional in a single-server deployment, is now a requirement. ThingWorx Connection Server is also now required. Apache ZooKeeper is used to coordinate multiple running servers. Apache Ignite is used to share current state between servers.  Component       Description                                                                                          Provider Load Balancer Distributes network traffic to servers ready to accept it. In Active-Active Cluster configuration, the load balancer is used to direct WebSocket based traffic to the ThingWorx Connection Services while user requests (http/https) traffic is directly distributed to the ThingWorx Foundation servers. Example load balancers: HA Proxy Azure Application Gateway AWS ALB See the ThingWorx High Availability Documentation for details. ThingWorx Connection Server Handles AlwaysOn connections with devices and multiplexes all messages over one connection to ThingWorx Foundation Servers. In an Active-Active configuration, it handles all WebSocket based traffic to and from the ThingWorx Foundation Server. PTC Apache ZooKeeper A centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. It is a coordination service for distributed application that enables synchronization across a cluster. Apache Software Foundation Apache Ignite Used by ThingWorx Foundation Servers to share state. It may be embedded with each ThingWorx instance or can be run as a standalone cluster for larger scale. Apache Software Foundation Data and Model Provider Provides persistent storage of application data. All ThingWorx 9 supported database options: PostgreSQL Microsoft SQL Server Microsoft Azure SQL InfluxDB (only available as a data provider)         Step 3: Next Steps   Congratulations! You've successfully completed the Active-Active Clustering with ThingWorx guide.   At this point, you can make an educated decision regarding which clustering architecture is best suited for your ThingWorx application. Whether you already use ThingWorx or pursuing ThingWorx, its important to understand how Active-Active clustering is achieved and whether it is right for your system.   Learn More   We recommend the following resources to continue your learning experience:       Capability Guide Manage ThingWorx Application Development Reference Build Get Started with ThingWorx for IoT Experience Create Your Application UI   Additional Resources   To learn more about Active-Active Clustering and general ThingWorx deployment guidelines, there are ample resources available through our Help Center and PTC Community:   Resource Link Community Developer Community Forum Support ThingWorx Platform Sizing Guide Support ThingWorx Deployment Architecture Guide Support ThingWorx High Availability Documentation

Hello ThingWorx community!   I’d like to invite you to join me and our ThingWorx experts for an exclusive webinar on October 30 at 11:00 AM (EDT) to explore the transformative potential of Agentic AI within the ThingWorx Industrial IoT and AI platform. In this session, you’ll gain insights into ThingWorx’s AI strategy, focused on delivering actionable intelligence and accelerating digital transformation across the product lifecycle. You’ll also see in action: Hands-on demos integrating Large Language Models (LLMs) with ThingWorx 10.X How to enable agentic automation using Model Context Protocol (MCP) Ways to enhance industrial apps with real-time decisions, natural language, and computer vision AI So, register here:   [Webinar]: ThingWorx Innovation With Industrial IoT and AI    Also, here is a personal video invitation message to you all!      Post webinar, please provide your feedback and comments below!    We look forward to having you join us!     Cheers, Ayush Tiwari Director Product Management  

  Learn how to create factory line solutions the can help take you to the next level     Guide Concept   This project will introduce more complex aspects of the ThingWorx application and solution building.   Following the steps in this guide, you will develop your own IoT application or get a jump start in how to utilize ThingWorx for your needs.   We will teach you how to create a focused rules engine or service level logic to be used with the ThingWorx Platform.     You'll learn how to   Create automated machine processes Use Services, Alerts, and Subscriptions to handle processes without human interaction Integrating complex logic with straight forward step by step systems   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete ALL parts of this guide is 60 minutes     Step 1: Examples and Strategy   Download the attached FoodIndustry.zip and extract/import the contents. This is to be used as you work through this learning path. For the completed example, download, extract, and import FoodIndustryComplete.zip. These downloads provide three Users and a Security Group. Please watch your count for Users or the import could fail. If you're at your User count limit, delete Users before attempting to import these downloads. Unzip the download and import the Entities included.   In this tutorial we continue with our real-world scenario for the Fizos food company. We should already have our factory data in data tables and will expand on how we can make the factory line smarter. The best processed are built on great timing, quality materials, a great design, and a method to keep track of everything that is happening. We won't have control of materials here, but we can formulate a simple, but great design. Our design will be based on Alerts, Subscriptions, and Schedules.   One of the same questions we will need to ask ourselves that we did in the last guide pertaining to products, is whether to create an entity per machine used in the factory OR create data entries in a data table and process everything through services. Since we would like to have more detailed and up to date information about our machines, I will create a data model that is tied back to our factories.   We will need to start by creating our templates for overall machines, templates for specialized machines, and then entities for the particular machines we have in our factories.       Click here to view Part 2 of this guide.

This video covers the new features of ThingWorx Analytics Builder 8.1   Updated Link for access to this video: What's New in ThingWorx Analytics Builder 8.1

Please refer to the release notes: PTC Here are some common questions and answers in regards to the Uprade change: Extension: The removal of dependencies was almost impossible. Do the changes allow extension updates without removal? That is correct Is uninstalling extensions "easier" possible? For example, having extensions with many dependencies which results in a struggle when manually deleting all include files...it would be great to have just 1 uninstall function. Unfortunately, that is still the case when one is uninstalling extension Is there an easy way to see all entity dependencies on an extension (vs. on any one template etc)? Not currently at the extension level.  That's certainly something to be considered adding If one made a mistake on changing an extension mashup, how do  they recover? Is it necessary to remove and then import newer extension? Yes, at the moment that is the only recourse.

Hello Navigate Community -     In case you haven't heard, Navigate 8.5 was released last Thursday, 9/26 and is now available for download! This release includes a lot of exciting functionality:   1. Improvements to View Apps -  Updated ThingView 3D Viewing Component - which is now documented & supported for use in custom mashups;  Support for distributed vaults;  Display of security labels & values. 2. BETA release of the first Reusable Components for rapid application development  3. First Navigate Contribute App for review & approval of Windchill Change Requests Want to learn more? Read on!   Introducing change can result in higher costs if not fully considered.  That’s why collaboration is a necessity across people and processes from the initial state of product ideation through to manufacturing, device connectivity and field service.  There is a need to not just access product and enterprise data easily, but to participate in strategic product lifecycle processes in order to avoid unintended consequences.   ThingWorx Navigate 8.5 introduces the first App in the Contribute Series. This App allows key stakeholders to be directly involved in the change process by enabling them to voice their opinions. The first of the Contribute apps for Change Management stitches all these voices together within the digital thread.   Inter-operable with Windchill 11.2 and Windchill 11.1 M020 CPS06, this change management app provides a list of open approval tasks and access to full details of the Change Request, along with attachments and affected items.   Configurable by role, this latest Navigate App enables a broad set of users inside and outside of engineering to fully participate in a digital change management workflow. Cross-functional users who review their task list, via “My Tasks”, are best able to complete changes online. These users can then assess change impacts at time of review, resulting in improved quality by eliminating the need to manually capture input and avoiding errors.   Role-based tailoring facilitates faster, clearer decision making and higher quality changes.  Better participation in the change management process adds the value of faster time to market. This Contribute app is the first to be built from reusable components, thus lowering costs and improving efficiency.   The Thingworx Navigate Contribute app for Change Management enables the wider spread of input to realize the best possible design since products are no longer designed in a silo.   If you have any questions about Navigate or want to connect with an account rep, reach out to me at elarkin@ptc.com.

Scoring is the process of making the prediction on the basis of the available data. Scoring is the process of assigning a predicted outcome to an individual record based on running that record’s conditions through the trained model. It allows you to request and retrieve individual record level prediction scores for a defined data set for a set of prediction topics. The accuracy of the score will likely be a direct reflection of the error rate produced by the Trained Model. Why the score value exceeds min or max value range of feature There are a few concepts to address with regards to this: Scoring outputs: It is important to note that when training an analytics model, the method is to create a generalizable model from a relatively small training dataset. By its nature, we expect the training process to see a limited subset and not an exhaustive list of all possible values for many constraints, especially time and practicality. As such, these generalized models will be expected to handle unseen data in the form of new combinations or values outside of previously observed ranges (more on this below). One common way to see scores that exceed the observed ranges in training, under the assumption that the goals are continuous, is to use prescriptive scoring. Prescriptive scoring attempts to find optimal values for lever, meaning tunable, features in order to maximize or minimize score values. Min/Max constraints: these are constraints that are placed upon the inputs for training and expected inputs for scoring. For training: If theses ranges were provided as part of the upload process, then training will raise exceptions regarding invalid data. However, if the ranges are not provided - they will be inferred from the data and, as such, training will not see values outside of observed ranges. For scoring: validation of the ranges will only be performed on the inputs - not the outputs. It is very important to note that the handling of these "constraints" is dependent upon the data type. For categorical (e.g. colors) and ordinal data (e.g. shirt sizes), the constraints are strict and data that was not observed in training will raise exceptions during scoring. However, for continuous values (e.g. temperature ranges) these constraints are more informational in nature. For predictive scoring, our code will accept records with values outside of those ranges. The rule of thumb is that values slightly outside these ranges are acceptable and that as the values stray farther from the ranges, the accuracy of the model degrades very quickly. For prescriptive scoring, these constraints are used to determine the acceptable ranges of values to try when determining the optimal values. Values outside of these constraints will NOT be tried. How to handle goal values while scoring What should be the value for the goal(objective TRUE) column in new data which would be scored using existing prediction model? <Dataset for making prediction model> Independent value goal field -0.65 0 -0.75 0 -0.85 0 0.85 1 0.45 1 ~~~ ~~~ <New data to be scored> Independent value goal field -0.25 ?? 0.35 ?? -0.45 ?? 0.95 ?? 0.15 ?? ~~~ ~~~ Now scoring, by its definition, does not take into consideration the goal column when being run. Seeing as the goal column above is a Boolean, we can populate the yet to be scored records with either a 0 or 1 and it won’t matter when it comes to scoring.

Interested in learning how others using and/or hosting ThingWorx solutions can comply with various regulatory and compliance frameworks?   Based on inquiries regarding the ability of customers to meet a wide range of obligations – ranging from SOC 2 to ISO 27001 to the Department of Defense’s Cybersecurity Maturity Model Certification (CMMC) – the PTC's IoT Product Management and EDC teams have collaborated on a set of detailed articles explaining how to do so.   Please check out the ThingWorx Compliance Hub (support.ptc.com login required) for more information!

  Ever dreamed of participating in the design of the latest ThingWorx features? Now’s your chance! Join the UX Lab in usability and research sessions to help inform the design of your favorite ThingWorx features from the Edge to Kepware to remote monitoring to Solution Central and more!   For those of you newer to PTC, the UX Lab is an opportunity to see early views of product mockups, wireframes, etc. to provide your direct feedback; the UX Lab is part of LiveWorx, our definitive event for digital transformation, and this year both are virtual!   Click here to influence the design of Edge, Kepware, remote monitoring, Solution Central, and so much more!   Reach out with any questions!   Stay connected, Kaya

    Step 10: Building and Importing   After you’ve completed your code updates, it’s time to build and import! Below are instructions for building with the framework you have set for the project.   Build Extension with Ant   Go to the Package explorer view. Right click on build-extension.xml. Hover over Run As and select Ant Build.   Your console output will indicate BUILD SUCCESSFUL. This will build your project and create the extension zip in the your_project->build->distributions folder of your project.   Build Extension with Gradle   Right click on your project ->Gradle (STS)->Tasks Quick Launcher.   Set Project from the drop-down menu to your project name and type Tasks as build. Press Enter.   Your console window will display BUILD SUCCESSFUL. Your extension has been created and stored as a zip file in your_project->build->distributions folder.     Import Extension   Go to ThingWorx Composer. In the lower left, click Import/Export, then select Import under.   Select Extension for the type of import.   Choose the zip file in the distributions folder under the build directory. Click Import. Click Close on the prompt to refresh your Composer instance.   After you have imported your new widget and refreshed Composer, you will see your new widget as an option on the Mashup Design tab.     Step 11: Tips   When a new version of an extension contains model changes for one or more of its entities, the previous version of the extension and any entities created from that extension must be deleted before installing the new version of the extension. To avoid having to recreate the entities after the new extension is installed, you can include an extension migrator with the extension that imports the entities created with the previous version.   Adding an Extension Migrator   To create a migrator class for your extensions, follow these steps: Choose the ThingWorx menu and select New Extension Migrator. Select or enter your source folder and package. Enter a name, such as CustomMigrator. Click Finish. The Java source file is created and the configfiles/metadata.xml file is updated automatically.   NOTE: If a migrator has already been created, the previous migrator class name will be replaced in the metadata.xml file with the new migrator class name. The previous migrator Java file will not be changed.   Element Selection   Use this.jqElement to limit your element selections. This will reduce the chance of introducing unwanted behaviors in the application when there might be duplicate IDs and/or classes in the DOM.   ///Don’t do the following: $('.add- btn').click(function(e){...do something...}); ///Do this: this.jqElement.find('.add-btn').click(function(e){ ...do something...});   Logging   We recommend that you use the following methods to log in the Mashup Builder and runtime environment: TW.log.trace(message[,message2,...][,exception]) TW.log.debug(message[,message2,...][,exception]) TW.log.info(message[,message2,...][,exception]) TW.log.warn(message[,message2,...][,exception]) TW.log.error(message[,message2,...][,exception]) TW.log.fatal(message[,message2,...][,exception])   You can view the log messages in the Mashup Builder by opening the log window via the Help->Log menu item; in the Mashup runtime, you can now click on the Show Log button on the top left corner of the page to show log window. If the browser you use supports console.log(), then the messages will also appear in the debugger console.   Formatting   If you have a property with baseType of STYLEDEFINITION, you can get the style information by calling: var formatResult = TW.getStyleFromStyleDefinition( widgetProperties['PropertyName']);   If you have a property of baseType of STATEFORMATTING: var formatResult = TW.getStyleFromStateFormatting({ DataRow: row, StateFormatting: thisWidget.properties['PropertyName'] });   In both cases formatResult is an object with the following defaults: { image: '', backgroundColor: '', foregroundColor: '', fontEmphasisBold: false, fontEmphasisItalic: false, fontEmphasisUnderline: false, displayString: '', lineThickness: 1, lineStyle: 'solid', lineColor: '', secondaryBackgroundColor: '', textSize: 'normal' };     Step 12: Next Steps   Congratulations! You've successfully completed the Create A Mashup Widget Extension tutorial.   You've learned how to:   Utilize the Eclipse Plugin and Extension SDK Create and configure an Extension project Create a mashup widget Extension Build and import an Extension   Learn More   We recommend the following resources to continue your learning experience:    Capability    Guide Build Application Development Tips & Tricks   Additional Resources   If you have questions, issues, or need additional information, refer to:    Resource         Link Community Developer Community Forum Help Center  Custom Widget Tips and Example    

Question: Is there a Security log entry added when a user is refused access to Composer? Answer:The Security log is mainly for user login and authentication items; since this is not authentication per se, we don't log any messages there. The Application log should have log entries noting any errors. Question:  Do the gauges and graphs now behave more reactive without reloads of massive data. just easy show "realtime" data? Answer: The Custom Charts we have on the Market place should alleviate some of that - depending on how the data refresh is set up, that should redraw. The changes we have done on the layout side won't have any impacts there, unless the browser window is resized. Question:Will we offer a library of "Design themes"?  Answer:We are working on adding prebuilt themes for a future release. Question: Does the new Mashup builder store Mashups in the same way? Are these new Mashups taking into account a runtime separated from the platform? Answer: It should be the same - the runtime instance is still separated. Question:What about inheritance with themes? Answer: The support inheritance - if you have a Contained Mashup without a Theme set, they should be inheriting the parent's Theme. Question: Is it posible to duplicate an expression / validator? are there plans to include the event router there? Answer: We don't have duplication support in the current release . Yes, we have plans to add more 'non-visual' widgets to the list, that includes Event Router and Status Message. Question: Is it planned to generate the preview images dynamically based on mashup contents? Answer: We are looking into dynamic updates for images - it might get expensive to generate images based on the volume of data that is bound to the widgets, so we're exploring different ways to resolve this. Question: Will these new BETA widgets be forward compatible? Answer:Correct, and we are working on adding more widgets! The property definitions within them shouldn't undergo any changes (as in properties won't get removed). We're always looking to enhance these further, so they might get additional features/ properties. Question: Any guide available for custom widget development? Answer: We are working on adding development guides for Web Components, and working with the respective SDKs.

This groovy script will return a list of DeviceGroups based off a given Asset's serialnumber. import com.axeda.drm.sdk.device.*; import com.axeda.drm.sdk.Context; Context sysContext = Context.create(); DeviceGroupFinder dgf = new DeviceGroupFinder(sysContext); DeviceFinder devFinder = new DeviceFinder(sysContext); devFinder.setSerialNumber("[your serialnumber here]"); Device myDevice= devFinder.find(); dgf.setDeviceId(myDevice.getId()); List<DeviceGroup> allGroups = dgf.findAll(); allGroups.each { group -> logger.debug(group.getName()); }

  Helloooooo ThingWorx users,   Ever wanted to see the coolest technology in action? Ever wished you could surround yourself with awesome ThingWorx developers? Maybe you’ve even wished you could meet the ThingWorx product management team!   If that’s the case, you’re in luck! Join me for LiveWorx 2019 from June 10 – 13 in Boston this summer to discover how you can make digital transformation a reality for your organization. See what all the hype’s about here!   I’ll be presenting a rockin’ session on some exciting new functionality coming in ThingWorx to help with enterprise-wide app deployment. See me present with Chris Baldwin on Tues, June 11, @ 1:15pm in our session titled Introducing Solution Central: Your Gateway to Accelerated IIoT Value Across the Enterprise!   For a sneak peek of what’s to come at LiveWorx, here are seven sensational sessions our developers can’t miss! (Note: Dates and times are subject to change.) It's Electric: HowCaterpillar Develops Compelling IIoT Apps That Resonate With Customers & Dealers Mon, June 10, @ 4:30 (45 min) ThingWorx and Microsoft Azure from A to Z Tues, June 11, @ 4:00pm (45 min) It’s All About The Apps: Introducing ThingWorxMashupBuilder 2.0 and More! Wed, June 12, @ 9:00am (45 min) Connecting Asset Advisor to Azure Wed, June 12, @ 3:00pm (45 min) ThingWorx for Scalability with InfluxDB and Beyond! Wed, June 12, @ 3:00pm (45 min) From Pilot to Production: Tips & Tricks for Vuforia Studio Thurs, June 13, @ 12:00pm (45 min)   Hope to see you all there and meet you in person!   Stay connected, Kaya

Why? Reduce or eliminate hardware costs Get database portability across on-premise and cloud compatible virtualization High speed and minimum downtime Optimize performance Three deployment options: Single: best for apps requiring resource guarantee at database level Elastic pool: SAAS apps with multiple databases achieving better cost efficiency Managed instance: best for modernization at scale MS SQL Improvements: Ingest millions of data items/day with imrpoved MS SQL 150% improvement  ingestion throughput with MS SQL persistence provider Optimized indexing to achieve better peformance for the same compute at the same price ThingWorx with Microsoft database solution: Azure SQL logical server (single instance and elastic pool) v12 Azure SQL managed server v12 MS SQL sever 2016 Azure PostgreSQL 9.6 and 10 Q: What is the rate as compared to PostgreSQL? A: We are in process launching new sizing guide that will be out in a few weeks. MS SQL is around 15-22K writes per sec. Comparable to Postgres.

Send data from MXChip development board to ThingWorx with Azure IoT hub   NOTE: Complete the following guides in sequential order. The estimated time to complete this learning path is 90 minutes.   1. Connect MXChip to Azure IoT 2, Create An Application Key 3. Connect Azure IoT Devices Part 1 Part 2 4. Create A Thing Shape

Solution Central and Azure Active Directory Written by: Tori Firewind, IoT EDC   As we’ve said in a previous post, Solution Central (SC) is a crucial part of any mature dev ops pipeline. In its latest version (3.1.0), it manages custom solutions even more easily due to the SC API. However, this comes with a few requirements that can be a little tricky.   One of the more complex configuration pieces for using this new API involves a cloud-hosted Active Directory (AD) application within Azure AD. In order to make use of the new API, your organization’s users must exist on an Azure AD tenant that is separate from the PTC tenant. Most PTC customers are placed on this PTC-owned tenant by default, so additional configuration may be required to set up the AD instance within Azure before the SC API can be used. The type of tenant has to be Azure, of course, as that is what PTC uses: a multi-tenancy Azure infrastructure for all authentication.   In this usage, “tenant” is a cloud-hosting, infrastructure term which essentially refers to an Azure VM hosting an Active Directory server, as well as managing the many AD components that would otherwise require a lot of oversight. Users within that AD server are grouped so that only those solutions published by their own organizations are visible within Solution Central. In this way, the term “tenant” can also refer to a partition of some kind of data; a Solution Central tenant includes the users, the solutions, and is sort of like a sub-tenant of the larger PTC infrastructure. PTC uses a global Solution Central tenant for deployment of its own solutions, like DPM (Digital Performance Management), which is therefore available to every user in the PTC Azure AD tenant or a tenant which has been connected using the tutorial below.   There are good reasons to want to use your own Azure AD integrated into Solution Central that do not involve using the SC API. For one thing, it allows for direct control over the users that have access; otherwise, a ticket to PTC support is necessary every time a user needs access granted or removed. The tutorial below is a great reference for anyone using Solution Central, with steps 1-4 offering an easy guide for integrating your own Azure AD and simplifying your user management.   To use the SC API, however, there are additional steps required to create an application for retrieving an oauth token. This application needs the “solution-publisher” role or else bad request/forbidden errors will pop up. This role is automatically available in your Azure AD tenant once it is linked to the PTC AD tenant, but it does have to be manually assigned to the application, whose sole function is to request this access token for authenticating requests against the SC server.   The Azure application you need to create is essentially a plugin with permission to publish solutions against the SC API. It functions a little like a “login” in database terminology, serving the function of authenticating to an endpoint (in this case not tied to a user or any kind of identity). This application must be able to request an access token successfully and return that to the scripts which call upon it in order to perform the project creation and publication requests. The tutorial below steps you through how to create this application and request all of your solutions via the SC API.   Tutorial: Create Azure AD Application to Access SC via API Create a new tenant in Azure AD for users who will have access to the SC API Create a ticket with PTC to provide the tenant ID and begin the onboarding process Once that process completes, you will receive an email with a custom link to login to the Solution Central portal for your organization, where only your solutions exist Users will then need to be added as “Custom Global Administrators” on the SC enterprise application within Azure Portal to grant them access to login to Solution Central in a browser In order for us to be able to use the SC API, however, more work needs to be done; an application to request an oauth token for requests must be created in Azure Portal Navigate to “App Registrations” from the Azure AD page in Azure Portal and then click “New registration” Enter the application name (ours is called “gradle-plugin-tokenfetcher” in the examples shown here), and select the “single tenant” radio button Enter a URL for redirect URI and for “Select a platform” select “Web” Click “Register”, and wait for the application created notification Now we need to add permissions to see Solution Central Open the app from under “App registrations” and select the “API permissions” tab Click “Add a permission” and in the pop-up window that appears, select the “APIs my organization uses” tab, which should have PTC Solution Central listed, if this tenant has been linked to the PTC tenant per step 2 above Select “Application Permissions” and then check the “solution-publisher” role Click “Add permissions” The application now has access to Solution Central as a publisher, able to send solution publications over the API and not just via the Platform interface   The application is ready now, so we can create a request to test that it has access to SC Using Windows Powershell or something similar, create a script to make a couple of cURL requests against first the Azure AD and then the Solution Central API (attached as well): The tenant ID and the directory ID are the same value (listed on the tenant under “Overview”), and the client ID and application ID are the same as well (listed on the application, shown here), so don’t be confused by terminology The client app secret is the “Value” provided by the system when a new client secret is created under “Certificates & Secrets” (remember to copy this as soon as it is made and before clicking away, as after that, it will no longer be visible): The Solution Central app ID can be found under “App registrations”, listed within the details for the “solution-publisher” role: This access token request piece must be done before every request to the SC API, so this secret should be kept in some kind of password management tool (or a global environment variable in GitLab) so that it isn’t found anywhere in the source code If the script pings the SC API successfully, then a list of solutions will be returned

Hey Community Members – I have exciting news to share! Last week, PTC announced that ThingWorx was recognized as a frontrunner IIOT Platform in four leading analyst research reports on the industrial software market.   In alphabetical order, the reports PTC/ThingWorx was named in were: ABI Research’s Smart Manufacturing Platforms Competitive Ranking The Forrester Wave™: Industrial IoT Software Platforms, Q3 2021 The Gartner® Magic QuadrantTM for Industrial IoT Platforms IDC MarketScape for Industrial IoT Platforms and Applications for Manufacturing Not only is PTC the only company included in all four reports, but it also placed as a leader in all four, which hopefully makes you feel confident in your choice to use ThingWorx. The research criteria the analyst firms use to make selections is unique to each firm, but to us, all of them measure the value ThingWorx can bring to an industrial business.   What value does ThingWorx bring to you?   Stay connected, Rachel               Gartner, Magic Quadrant for Industrial IoT Platforms, Alfonso Velosa, Ted Friedman, Katell Thielemann, Emil Berthelsen, Peter Havart-Simkin, Eric Goodness, Matthew Flatley, Lloyd Jones, Kevin Quinn, 18 October 2021 Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. Gartner and Magic Quadrant are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved. (this will be soon updated in our Policy as well)