IoT & Connectivity Tips

Help the ThingWorx product team with some key strategic questions about developing apps in the cloud!   Let us know what you think here!   Stay connected, Kaya

Hi Community,   Although we have reference architectures and integration paths for connecting devices to ThingWorx through Azure IoT; no one has ever written anything about doing the same from one ThingWorx to another.  I thought I’d change that and put some ideas out there around how one might go about doing this.  Although this is not officially supported or recommended by PTC; I have consulted with a number of leading SMEs on the subject, which have participated in forming the basis of my thinking outlined here.   Components Required (in order of communication path): On-premise ThingWorx Platform Protocol Adapter Toolkit* (CXS) - MQTT Azure IoT Edge Azure IoT Hub ThingWorx Azure IoT Hub Connector (CXS) Azure Cloud-hosted ThingWorx Platform   PAT (2) with codec to encode MQTT messages publishes to on-premise IoT Edge MQTT endpoint which handles store-and-forward of messages to IoT Hub.  An Azure IoT device would exist for each Thing you wish to represent on the ThingWorx servers.  The Azure IoT Hub Connector would pick-up the incoming messages and pass them on to the cloud ThingWorx which would decode the MQTT payload and map to Thing property updates.   The only part that I presently don’t like about this approach is that you’ll need to decode the MQTT messages on the ThingWorx platform in the cloud when they are received from the IoT Hub, and this mechanism will need to also need to handle encoding and publishing back to the IoT Hub if C2D (Cloud-to-Device) messages are to be implemented (aka bi-directional).  This is required as ThingWorx only supports AlwaysOn as an application level protocol so some form of mapping needs to be done.   * Another approach would be to replace the PAT with a custom agent which implements both the ThingWorx Edge SDK and the Azure IoT device SDK   Regards,   Greg Eva

This post is part of the series Forced Root Cause Monitoring via Mashups and Modal Popups To not feel lost or out of context, it's recommended to read the main post first. Create the Main Mashup Create a new Mashup called "rcp_MashupMain" as Page and Responsive Save and switch to the Design tab Design Add a Layout with two Columns In the right Column add another Layout (vertical) with a Header and one Row Add a Grid to the Row Add a Panel to the Header Add a Panel into the Panel (we will use a Panel-In-Panel technique for a better design experience) Set "Width" to 200 Set "Height" to 50 Set "Horizontal Anchor" to "Center" Set "Vertical Anchor" to "Middle" Delete its current "Style" and add a new custom style - all values to default(this will create a transparent border around the panel) Add a Label to the inner Panel Set "Text" to "Historic data of what went wrong" Set "Alignment" to "Center Aligned" Set "Width" to 200 Set "Top" to 14 Add a Panel to the left Column Add a Navigation Widget to the Panel This will call the Popup Window when its Navigate service is invoked (by a Validator) Set "MashupName" to "rcp_MashupPopup" Set "TargetWindow" to "Modal Popup" Set "ShowCloseButton" to false Set "ModalPopupOpacity" to 0.8 (to make the background darker and give more visual focus to the popup) Set "FixedPopupWidth" to 500 Set "FixedPopupHeight" to 300 Set "PopupScrolling" to "Off" Set "Visible" to false, so it will not be shown to the user during runtime Add a Textbox to the Panel This will show the numeric value corresponding to the State selected in the modal popup This will just be used for displaying with no other functionality - so that we can verify the actual values chosen Set "Read Only" to true Set "Label" to "Selected Reason (numeric value)" Add a Checkbox to the Panel This will be used an input for the Validator to determine if an error state is present or not Set "Prompt" to "Set this box to 'true' to trigger the popup. Set the value via the Thing to simulate a service. Once the value is set, the trigger is set to 'false' as the popup has been dealt with. A new historic entry will be created." Set "Disabled" to true Set "Width" to 250 Add a Validator to the Panel This will determine if the checkbox (based on the trigger / error state) is true or false. If the checkbox switches to true then the validator will call the Navigate service on the Navigation Widget. Otherwise it will do nothing. Click on Configure Validator Add Parameter Name: "Input" Base Type: BOOLEAN Click Done Set "Expression" to "Input" (the Parameter we just created) Set "AutoEvaluate" to true Save the Mashup Data In the Data panel on the right hand side, click on Add entity Choose the "rcp_AlertThing" and select the following services GetProperties (execute when Mashup is loaded) SetProperties QueryPropertyHistory (execute when Mashup is loaded) clearTrigger Click Done and the services will appear in the Data panel Connections After configuring the UI elements and the Data Sources we now have to connect them to implement the logic we decided on earlier GetProperties service Drag and drop the trigger property to the Checkbox and bind it to State Set the Automatically update values when able to true SetProperties service From the Navigation Widget drag and drop the selectedState property and bind it to the SetProperties service selectedReason property From the Navigation Widget drag and drop the PopupClosed event and bind it to the SetProperties service From the SetProperties service drag and drop the ServiceInvokeCompleted event and bind it to the clearTrigger service From the SetProperties service drag and drop the ServiceInvokeCompleted event and bind it to the QueryPropertyHistory service QueryPropertyHistory service Drag and drop the Returned Data's All Data to the Grid and bind it to Data On the Grid click on Configure Grid Columns Switch the position of the timestamp and selectedReason fields with their drag and drop handles For the selectedReason Set the "Column Title" to "Reason for Outage" Switch to the Column Renderer & State Formatting tab Change the format from "0.00" to "0" (as we're only using Integer values anyway) Choose the State-based Formatting Set "Dependent Field" to "selectedReason" Set "State Definition" to "rcp_AlertStateDefinition" Click Done clearTrigger service There's nothing more to configure for this service As the properties will automatically be pushed via the GetProperties service, there's no special action required after the service invoke for the clearTrigger service has been completed Validator Widget Drag and drop the Validator's TRUE event to the Navigation Widget and bind it to the Navigate service Drag and drop the Checkbox State to the Validator and bind it to the Input parameter Navigation Widget Drag and drop the Navigation Widget's selectedState to the Textbox and bind it to the Text property Save the Mashup

Pushbullet is a lightweight notifications platform and can be a way to explore Alerts and Subscriptions Basically create an an Alert on a property and Subscribe to that Alert Adding Alert to Property Humidity Adding Subscription The PTC-PushBulletHelper is just a generic Thing with a service called PushNotification var json = {     "body": Message,     "title":"Temperature fault",     "type":"note" }; var accessHeader = {     "Access-Token": "o.Hnm2DeiABcmbwuc7FSDmfWjfadiLXx2M" }; var params = {      proxyScheme: undefined /* STRING */,     headers: accessHeader /* JSON */,      ignoreSSLErrors: undefined /* BOOLEAN */,      useNTLM: undefined /* BOOLEAN */,      workstation: undefined /* STRING */,      useProxy: undefined /* BOOLEAN */,      withCookies: undefined /* BOOLEAN */,      proxyHost: undefined /* STRING */,      url: 'https://api.pushbullet.com/v2/pushes' /* STRING */,      content: json /* JSON */,      timeout: undefined /* NUMBER */,      proxyPort: undefined /* INTEGER */,      password: undefined /* STRING */,      domain: undefined /* STRING */,      username: undefined /* STRING */ }; // result: JSON var result = Resources["ContentLoaderFunctions"].PostJSON(params); You can test the Helper PushNotification service Next you can test the subscription

This post is part of the series Forced Root Cause Monitoring via Mashups and Modal Popups To not feel lost or out of context, it's recommended to read the main post first. Create a Popup Mashup Create a new Mashup called "rcp_MashupPopup" as Page and Static Save and switch to the Design tab Design Edit the Mashup Properties Set "Width" to 500 Set "Height" to 300 Add a new Label Set "Text" to "Something went wrong - what happend?" Set "Alignment" to "Center Aligned" Set "Width" to 230 Set "Top" to 55 Set "Left" to 130 Add a new Radio Button Set "Button States" to "rcp_AlertStateDefinition" Set "Top" to 145 Set "Left" to 25 Set "Width" to 450 Set "Height" to 100 In the Workspace tab, select the "Mashup" Click on Configure Mashup Parameters Add Parameter Name: "selectedState" BaseType: NUMBER Click Done Save the Mashup Connections Select the Radio Button Drag and drop its Selected Value property to the Mashup and bind it to the selectedState Mashup Parameter Drag and drop its SelectionChanged event to the Mashup and bind it to the CloseIfPopup service Save the Mashup

This post is part of the series Forced Root Cause Monitoring via Mashups and Modal Popups To not feel lost or out of context, it's recommended to read the main post first. Required Logic The following logic will help us realizing this particular use case: The trigger property on the AlertThing switches from false to true. The MashupMain will receive dynamic Property updates via the AlertThing.GetProperties service. It will validate the value of the trigger Property and if it's true the MashupMain will show the MashupPopup as a modal popup. A modal popup will be exclusively in the foreground, so the user cannot interact with anything else in the Mashup except the modal popup. In the modal popup the user chooses one of the pre-defined AlertStateDefinitions. When a State is selected, the popup will set the State as a Mashup Parameter, pass this to the MashupMain and the popup close itself. When the MashupPopup is closed, the MashupMain will read the Mashup Parameter The MashupMain will set the selectedReason in the AlertThing to the selected value. It will also reset the trigger property to false. This allows the property to be set to true again to trigger another forced popup. On any value change the AlertThing will store the selectedReason State in a ValueStream to capture historic information on which root causes were selected at which time. The ValueStream information will be displayed as a table in a GridWidget in the MashupMain once the new properties have been set.

Overview A global leader in chemical processing and industrial manufacturing, with a strong international footprint and multiple production sites worldwide, set out to transform its production ecosystem by adopting Industrial IoT (IIoT). The objective was to unify fragmented factory data, enable real-time analytics, and drive operational efficiency through AI-powered insights. Based on detailed use case documentation and architectural workshop findings, this reference architecture outlines a robust, scalable solution designed to integrate factory systems, deliver AI-supported insights in real time, and empower teams through self-service applications.   The solution leverages PTC’s ThingWorx suite—along with Microsoft Azure services and complementary technologies—to address key challenges in production, quality, and efficiency across engineering, manufacturing, and operations. About Beyond the Pilot series Use Case   A. Engineering – Process Optimization & Quality Control   Problem: Resolving Data Integration & Visibility Challenges   Customer’s engineering teams struggled with fragmented data across various factory systems, limiting their ability to analyze process performance and optimize production parameters. Without a unified data platform, engineers could not effectively compare historical and real-time machine center lining values, making it difficult to maintain consistent production quality.   Solution: Unified Data Integration & Advanced Process Analytics   The reference architecture establishes a central, cloud-based data platform that aggregates and correlates machine data from various sources in real time. By integrating OPC Aggregators and Kepware with Azure IoT Hub, factory data is ingested, processed, and made accessible via ThingWorx applications. Engineers can now visualize mechanical and digital process values, set dynamic thresholds, and receive alerts when deviations occur—ensuring precise process control and quality optimization.   Role of PTC Products:   PTC Kepware: Standardizes and integrates machine data from disparate factory systems, ensuring a seamless flow of real-time process variables. ThingWorx Platform: Provides a robust dashboard for analyzing centerlining data, visualizing production trends, and enabling data-driven decision-making. ThingWorx Digital Performance Management (DPM): Automates the identification of process inefficiencies, allowing engineers to fine-tune machine settings dynamically.   B. Manufacturing – Scrap Reduction & Production Efficiency   Problem: Enhancing Scalability and Reducing Operational Inefficiencies   Customer faced challenges in scaling its IIoT solution as new sensors and data sources were introduced. Traditional systems struggled with the increased volume of factory data, leading to slow system response times and ineffective real-time analytics. Additionally, manual process adjustments resulted in inconsistencies, contributing to increased scrap rates and wasted materials.   Solution: Cloud-Scalable Infrastructure with Real-Time Process Optimization   To address these issues, the architecture leverages Azure IoT Hub, Azure Data Explorer (ADX), and Influx DB to handle massive data streams and provide low-latency analytics. This ensures that production trends, environmental conditions, and machine parameters are continuously monitored and optimized in real time. Advanced machine learning models predict process inefficiencies, enabling operators to make automatic adjustments to reduce scrap and optimize yield.   Role of PTC Products:   ThingWorx Platform: Acts as the central command hub, enabling real-time decision-making based on factory data trends. ThingWorx Digital Performance Management (DPM): Uses historical data to provide AI-supported recommendations for reducing material waste and improving overall equipment effectiveness (OEE). PTC Kepware: Ensures reliable, high-speed data acquisition from sensors, production lines, and environmental monitoring systems, feeding critical information into ThingWorx for optimization.   C. Driving Digital Transformation & Quality Optimization   Problem: Lack of Digital Process Automation & AI-Powered Decision Making   Customer’s previous factory systems relied on manual reporting and fixed thresholds for process control, limiting the ability to detect and respond to process inefficiencies in real time. Operators needed a system that could provide intelligent, self-service applications with AI-driven recommendations for optimal production performance.   Solution: AI-Driven Automation & Dynamic Quality Control   The IIoT architecture integrates AI-powered predictive analytics to analyze deviations in real-time and suggest automatic machine adjustments. Real-time applications, customizable process recipes, and dynamic alerting systems empower production teams with actionable insights. By embedding self-service applications in ThingWorx, engineers and operators can fine-tune process settings and receive automated recommendations for improving quality and efficiency.   Role of PTC Products:   ThingWorx Platform: Serves as the central analytics hub, delivering AI-powered insights for continuous process improvement. ThingWorx DPM: Uses machine learning to correlate scrap rates with process variables, recommending changes that minimize waste and enhance quality. PTC Kepware: Captures real-time process data, ensuring that AI models receive accurate inputs for predictive analysis.   Customer’s digital transformation journey is now backed by a robust, PTC-powered IIoT ecosystem that delivers continuous improvement, higher production efficiency, and proactive maintenance capabilities—ultimately driving the future of smart manufacturing. Technical Architecture and Implementation Details   This section combines detailed technical descriptions with the overall reference architecture. It describes the core components, integration points, and implementation strategies that deliver a robust IIoT solution for the customer.   A. Architecture Overview Diagram       High-level architecture diagram for the final solution B. Detailed Technical Components     Component Role Key Features OPC Aggregators & Kepware Stream and bridge machine data from production, DEV, and QA environments to Azure IoT Hub for real-time processing in ThingWorx. Scalable ingestion; latency monitoring; secure device connectivity; segregated closed environments for DEV/QA. Azure IoT Hub Ingests and secures machine telemetry data for analytics. Centralized data ingestion; integration with Azure services. ThingWorx on VMs Hosts the core IIoT application that processes data, provides end-user applications, and manages workflows. High performance; disaster recovery via VM snapshots; enhanced security through Azure AD integration and SSL support. Managed PostgreSQL Provides high availability for persistent application data through replication and failover. Data redundancy; managed service benefits; automated backup and recovery. Azure Data Explorer / Influx DB Handles advanced analytics, timeseries visualization, and predictive insights for telemetry data. Real-time analytics; anomaly detection; cost-effective long-term storage. Monitoring & Logging Tools Ensure comprehensive observability and prompt incident response across all components. Real-time applications monitoring; alerting; centralized log aggregation. RESTful APIs Enable seamless integration with ERP systems, legacy data sources, and other IoT devices. Secure data exchange; standardized connectivity protocols.     C. User Personas   The success of this solution relies on a well-defined team of technical experts responsible for deployment and ongoing management:     Persona Key Responsibilities Plant Manager Oversee overall factory performance and use data insights for strategic decision-making Drive process improvements and efficiency Digital Transformation Lead Analyzes and prioritizes valuable use-cases for the business Implement IIoT solutions across factory operations and scale AI-driven automation and data analytics Ensure long-term digital innovation and adoption Operations Manager Oversee production lines and ensure efficiency and optimize machine settings based on real-time insights Troubleshoot and resolve process issues quickly Quality Assurance Engineer Monitor production quality in real time and ensure compliance with quality standards Reduce scrap and rework by addressing deviations early Maintenance Engineer Monitor equipment health and respond to alerts and perform predictive maintenance to prevent failures Minimize downtime through proactive repairs Software Engineer Develop and maintain IIoT backend and frontend systems and ensure seamless data integration and API connectivity Optimize system performance and scalability Cloud Architect Design and manage IIoT cloud infrastructure and ensure scalable and secure cloud deployments Optimize data storage and processing in the cloud Security Analyst Implement and monitor security measures for IIoT systems and conduct risk assessments and threat analysis Ensure compliance with cybersecurity standards DevOps Engineer Manage CI/CD pipelines for IIoT applications and automate deployments and infrastructure management Optimize system performance and reliability     NOTE : Although these personas were required, the needs were fulfilled by a team of only 4–5 developers effectively playing multiple roles. Outcome   Optimized Production Efficiency By unifying machine telemetry, process parameters, and historical trends, customer empowers engineers with real-time insights. AI-driven recommendations and automated adjustments replace trial-and-error, enabling precise, dynamic optimizations. Bottlenecks and inefficiencies are identified instantly, allowing rapid corrective actions for peak performance.   Reduced Waste & Enhanced Quality Real-time process optimization and automated quality control significantly reduce material waste and variability. The system detects deviations at the source, enabling instant adjustments and ensuring consistent product quality, minimizing scrap, rework, and compliance risks.   Seamless Data Visibility & Collaboration A centralized dashboard provides real-time access to critical metrics, eliminating fragmented reports and delays. Engineers and operators can compare production data across sites, standardize best practices, and drive continuous improvements across the network.   Future-Ready Innovation Beyond immediate gains, this IIoT transformation lays the foundation for scalable sensor integration, AI-driven automation, and advanced predictive analytics. It’s not just a solution for today—it’s a long-term framework for sustained digital innovation in smart manufacturing. This reference architecture is not just about solving today’s challenges—it establishes a long-term, adaptive framework that will continue to evolve, enabling our customer to remain at the forefront of smart manufacturing and industrial digitalization. Additional Information   This section provides further insights into the project implementation and future strategic direction.   Parameter Description Example/Notes Time to First Go-Live Estimated duration from project initiation to initial production deployment. Approximately 16 weeks Partner Involvement Key strategic and technical partners collaborating on the deployment. Microsoft, Ansys, and Deloitte were supporting the digital transformation initiative centered around ThingWorx. Customer Roadmap Future enhancements planned by customer, such as AI-based predictive analytics and further automation. An expansion to incorporate AI and advanced machine learning–driven insights is planned       Vineet Khokhar Principal Product Manager, IoT Security   Disclaimer: These reference architectures will be based on real-world implementation; however, specific customer details and proprietary information will be omitted or generalized to maintain confidentiality.   Stay tuned for more updates, and as always, in case of issues, feel free to reach out to <support.ptc.com>  

Applicable Releases: ThingWorx Platform 7.0 to 8.4   Description:   A practical example of how to build a data model in ThingWorx following a pre-defined design Following topics are covered: Review existing Design Plan Build all required entities in ThingWorx Composer Test the model and review scalability and reusability         The session was recorded using the old ThingWorx Composer, but the concepts are still applicable Related Success Service - Principles of Thingworx Modeling Related Service - Design your Thingworx Model

This post is part of the series Forced Root Cause Monitoring via Mashups and Modal Popups To not feel lost or out of context, it's recommended to read the main post first. Testing the Mashups Open the rcp_MashupMain in a new browser window For this test I find it easier to have the rcp_AlertThing and the Mashup in two windows side-by-side to each other The Mashup should be completely empty right now Nothing in the historic table (Grid) The Selected Reason is blank The Checkbox is false In the rcp_AlertThing switch the trigger to false The following will now happen The new value will be automatically pushed to Mashup The checkbox will switch to true The validator now throws the TRUE Event, as the condition is met and the trigger is indeed true The TRUE Event will invoke the Navigation Widget's Navigate service and the modal popup will be opened The user now only has the option to select one of the three states offered by the Radio Button selector, everything else will be greyed out After choosing any option, the SelectionChanged Event will be fired and trigger setting the selectedState as well as closing the popup The PopupClosed Event in our MashupMain will then be fired and populate the selectedState parameter into the textbox (just for display) and will also call the SetProperties service on our Thing, updating the selectedReason with the selectedState parameter value Once the property is set and persisted into the ValueStream via the SetProperties' ServiceInvokeCompleted Event, we clear the trigger (back to false) and update the Grid with the new data In the AlertThing, refresh the properties to actually see the trigger false and the selectedReason to whatever the user selected Note: When there is a trigger state and the trigger is set to true the popup will always be shown, even if the user refreshes the UI or the browser window. This is to avoid cheating the system by not entering a root cause for the current issue. As the popup is purely depending on the trigger flag, only clearing the flag can unblock this state. The current logic does not consider to close the popup when the flag is cleared - this could however be implemented using the Validator's FALSE Event and adding additional logic

This article https://support.ptc.com/appserver/cs/view/solution.jsp?n=CS264270 and the blog post provide information on the technical changes in Thingworx 8.0, New Technical Changes in ThingWorx 8.0.0 Here are some common questions and answers in regards to the change. Is there any way that one could lose access to the Appkey keystore? (restore a backup, etc) Yes, it is possible to  lose the key store. If one for some reason simply deletes it or renames it, the existing application keys would no longer be able to be decrypted - thus unusable. Is there a way to back up the appkey store and any necessary secrets such that it can be recovered then? Yes, but this would be handled at the file system, not inside of ThingWorx. We do have some best practices documented for managing the keystore. For developers who configure Edge applications and Connectors to connect to the platform, where do they copy the app key from? Are they copyring the encrypted version of the app key? They would do the same as before. We are not encrypting the app key in the UI, only on disk. Is there any way to get a summary of appkeys that are being used via URL? We do have some requirements for highlighting "repeat offenders". In 8.0, one can query the logs to find those app keys. We don't log the app key id, only the app key name.

I got this excellent question and I thought it worthwhile to put my answer here as well.   There are two ways to segregate information between clients. By default we use a ‘software’ approach to segregation by using Organizations. This allows you to designate a Client to an Organization/Organizational nodes and give those nodes ‘visibility’ to specific entities within the software. This will mean that ‘through software logic’ users can only see what they’ve been given visibility to see. This mainly applies to all the client’s equipment (Thingworx Things). They can only see their own equipment. This would also apply to a specific set of their data which is ValueStream data because that can only be retrieved from the perspective of a Thingworx Thing   Blog/Wiki/DataTable/Streams can store data across clients and do not utilize visibility on a row basis, in this case appropriate queries would need to be created to allow retrieval for only a specific client. In this case we use a construct for security that utilizes what we call the ‘system user’ and wrapper routines that work of the CurrentUser context, this allows you to create enforced validated queries against the data that will allow a user to only retrieve their specific data.   In regards to the data itself, if you need to, you can provide actual ‘physical’ segregation by using multiple persistence provider and mapping Blog/Wiki/DataTable/Streams/ValueStreams to different persistence providers. Persistence providers are basically additional database schemas (in one and the same database or different database) of the Thingworx data storage schema, allowing you to completely separate the location of where data is stored between clients. Note that just creating unique Blog/Wiki/DataTable/Streams/ValueStreams per client and using visibility is still only a logical / software way of providing segregation because the data will be stored in one and the same database schema also known as the Thingworx data persistence provider.

This post is part of the series Forced Root Cause Monitoring via Mashups and Modal Popups To not feel lost or out of context, it's recommended to read the main post first. Before we start Create a new Project called "RootCausePopups" and save it. In the New Composer set the Project Context (top left box) to the "RootCausePopups" project. This will automatically add all of our new Entities into our project. Otherwise we would have to add each Entity manually on creation.

  What Is “Beyond the Pilot” and Why it matters?   Beyond the Pilot is a reference architecture series that highlights how real-world manufacturing challenges are addressed at enterprise scale across engineering, manufacturing, and service lines of business.   These stories reflect solutions built using — but not limited to — industrial IoT (IIoT), AI, and cloud technologies. Each entry captures how a specific use case — ranging from quality optimization to predictive maintenance — was solved using a combination of proven tools and repeatable design patterns.   Our goal is simple: To provide a blueprint for repeatable success, enabling technical leaders, architects, and operations teams to move from isolated wins to sustained value — securely, scalably, and strategically. Because technology doesn’t create impact in the lab — it creates impact when it’s scaled across the enterprise. Because innovation is only as powerful as its ability to sustain value across engineering, manufacturing, and service. Because manufacturers everywhere face the same question: How do we take what works in a pilot and make it work at scale? That’s exactly what this series will explore.     What You’ll Find in This Series   Each blog will highlight: The Context – The real-world problem we set out to solve The Architecture – The design patterns and integrations that made it possible The Execution – How we turned a concept into a production-ready system The Outcome – Tangible business results, from efficiency gains to cost savings The Lessons Learned – Best practices and insights you can reuse in your own journey   What’s Next   Upcoming posts will dive into: Manufacturing efficiency gains through connected operations Secure, cloud-native deployments that balance scale with compliance How digital twins are reshaping design, operations, and customer experience And much more…   Each story will link back here as the anchor introduction to this series. So stay tuned — and join us as we explore what it really takes to go beyond the pilot. Because that’s where innovation becomes transformation. Vineet Khokhar Principal Product Manager, IoT Security   Disclaimer: These reference architectures will be based on real-world implementation; however, specific customer details and proprietary information will be omitted or generalized to maintain confidentiality.   Stay tuned for more updates, and as always, in case of issues, feel free to reach out to <support.ptc.com>  

This post is part of the series Forced Root Cause Monitoring via Mashups and Modal Popups To not feel lost or out of context, it's recommended to read the main post first. Create Entities AlertStateDefinition Create a new StateDefinition called "rcp_AlertStateDefinition" In the State Information tab, select Apply State: Numeric from the list on the right hand side Create a new State: Less than or equal to "1" Display Name: "Something good" Style: a new custom style with text color #f5b83d (orange) Create a new State: Less than or equal to "2" Display Name: "Something bad" Style: a new custom style with text color #f55c3d (red) Create a new State: Less than or equal to "3" Display Name: "Something ugly" Style: a new custom style with text color #ad1f1f (red) with a Font Bold Edit the "Default" State Set the Style: a new custom style with text color #36ad1f (green) We will not use this style, but in case we need a default configuration it will blend into the color schema Save the StateDefinition ValueStream Create a new ValueStream called "rcp_ValueStream" (choose a default ValueStream, not a RemoteValueStream) Save the ValueStream AlertThing Create a new Thing called "rcp_AlertThing" Based on a Generic Thing Base Thing Template Using the rcp_ValueStream Value Stream In the Properties and Alerts tab create the following Properties Name: "trigger" Base Type: BOOLEAN With a Default Value of "false" Check the "Persistent" checkbox Name: "selectedReason" BaseType: NUMBER Check the "Persistent" checkbox Check the "Logged" checkbox Advanced Settings: Data Change Type: ALWAYS In the Services tab create a new Service Name: "clearTrigger" No Inputs and no Outputs Service code me.trigger = false; When this service is executed, it will set the trigger Property to false Click Done to complete the Service creation Save the Thing

This post is part of the series Forced Root Cause Monitoring via Mashups and Modal Popups To not feel lost or out of context, it's recommended to read the main post first. Required Entities In this simplified example we'll just use a Thing to set a status triggering the popup. This Thing will have two properties and one service: Properties trigger (Boolean) - to indicate if an error status is present or not, if so - trigger the popup selectedReason (Number) - to indicate the selected reason / root cause chosen in the modal popup Service clearTrigger - to reset the trigger to "false" once a reason has been selected The selectedReason will be logged into a ValueStream. In addition to the Thing and the ValueStream we will need a StateDefinition to pre-define potential root causes to be displayed in the popup. We will use three states to be used in a traffic-light fashion to indicate the severity of the issue in a custom color schema. To display the monitoring Mashup and the popup we will need two Mashups.

In this post I show how to use Federation in ThingWorx to execute services on a different ThingWorx platform instance. In the use case below I set up one ThingWorx instance in the Factory and another instance in the Cloud, whereby the latter is executing a service which is actually running on the former.   Please find the document in attachment.   HTH, Alessio Marchetti  

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.

    Step 4: Create and Implement State Definitions   A state definition is a collection of style definitions, along with rules for when to apply each style definition. The rule plus the style definition is a state.   In the HelloWorldPlayground Mashup, if the Gauge Widget goes to 10 and the Increment the Count button is clicked once again, the Gauge starts back at 0. This value change is displayed in the Line Chart when it is refreshed. Nevertheless, it would be helpful to have a way to show a user that they’re encroaching 10 and will have to restart, such as the Gauge changing colors in the section. This and many other uses is where State Definitions become useful and go hand and hand with Style Definitions.     Create Style Definition to Represent State Change   First, let’s create Style Definitions to represent the changes in the count. The default Style Definition for a Gauge is the DefaultGaugeFaceStyle Style Definition. We can simply duplicate and update the new Style Definition for our own purposes.   Filter and click the checkbox next to the DefaultGaugeFaceStyle Style Definition. Click Duplicate.   Name the Style Definition UpdatedGaugeFaceStyle. Click Style Information.   Set the Display String property as AlarmingCount. Change the Background Color to light red (color code #D60000 is used in this example).   Change the Secondary Background Color to a darker red (color code #960A0A is used in this example). The inside line of the Gauge Widget is very thin. As an additional exercise, update the Line Thickness property and/or Line Color to see the effect.     Configure State Definition   Now let’s create a State Definition that will use both the default Gauge Style Definition and the one we just created.   In the ThingWorx Composer, click the + New at the top of the screen.   Select State Definitions in the dropdown.   Set the Project (ie, PTCDefaultProject). Name the State Definition GaugeCount. Click States Information.   Set the Apply States dropdown to Numeric.   Set the following values for the default state: Property Value Operator Less than (<) Value 10 Display Name Under 10 Style DefaultGaugeFaceStyle 8. Click the Add State button to create the other states to match the below image:   9. Click Save.   You’ve now created a State Definition. If the value is below 10, the default Gauge format will be applied. Once the value reaches 10, notice the state-based changes you defined are displayed in the appearance of the Gauge.     Implement State Definition in Mashup   Update HelloWorldPlayground Mashup to incorporate the State-based formatting.   Select the Gauge Widget in the Workspace pane and click the ValueFormatter property.   Select the State-based Formatting radio button. Choose Count_Property for the Dependent Field drop-down and select the GaugeCount State Definition that we just created.   Click Done and Save the Mashup. Click View Mashup. If you used the color schemes mentioned, your new HelloWorldPlayground Mashup should look like this.   Click the Increment the Count button to see the state changes. The Gauge now displays a visual indication for when the count is approaching 10.     Enhance State Definition   To further enhance the user experience, you could add another color that warns the user in advance before the threshold is reached. For this example, we will update our State Definition and create a Style Definition that uses the color yellow.   Duplicate the UpdatedGaugeFaceStyle Style Definition.   Name the Style Definition UpdatedGaugeFaceStyle2. Click Style Information.   Set the Display String property to AlarmingYellowCount. Set the Background Color property to yellow (color code #F9EF6B is used in this example).    Set the Secondary Background Color property to a darker yellow (color code #D2CD0E is used in this example). Open the States Information tab of the GaugeCount State Definition. Update the State Definition to fit the image below and utilize the Style Definition we just created: Click Save and View Mashup to see the updated runtime appearance of the application.       Step 5: Implementing Event-Based State Changes   The State and Style Definition you just implemented enables the Gauge to show users when the data property value is approaching the defined threshold. To increase the effectiveness of your application, you can define Event Handling processes that alert the user. In this section we will explain two ways to handle the Event when the count is nearing the threshold value. One, with a Service that gets called whenever the Button Widget is clicked, and the other by using Expression Widgets.   Using a Service to Handle Events In this part of the exercise, we will configure the Mashup so that once the Count hits 9, we will display a more drastically changed Gauge.   Adding Data Service   The below sections are based on the HelloWorldPlayground Mashup.   Select the Gauge Widget in the Workspace pane. Click the Copy button in the toolbar.   Select the Container in the Workspace pane. Click the Paste button in the toolbar. If you Gauge Widgets will not go on top of one another, set the Z-index value of the new Gauge to a smaller number and set the Container Layout Position to static.   Click the green Add Service button in the Data tab next to Things_Hello_World_Thing1 to add two services from you Things_Hello_World_Thing1 Entity. NOTE: You just copied and pasted a Widget inside of a Mashup. While the Mashup retains the same property configurations and style definitions, the pasted Gauge will not have the same connections as the original Widget. You still need to define the inputs/outputs. For this new Gauge, we will only need to connect to the GetPropertyValues service. 6. Add the UnderWarningValue and WarningValueReached Services with the Execute on Load checked for both. 7. Click Done.   Binding Data and Event   With the original Gauge selected, scroll to the Visible property value. Drag and drop the UnderWarningValue service result to the Visible property.   With the new Gauge selected, scroll to the Visible property value. Drag and drop the WarningValueReached service result to the Visible property.   Select the Button Widget in the Workspace pane. Drag and drop the Clicked Event to the UnderWarningValue and WarningValueReached services.   This will ensure the other Services are run whenever the Increment the Count button is clicked.   The UnderWarningValue service will return true if the Count property is under 9. The WarningValueReached service will return true if the Count property is equal to or above 9. The result sent to the original Gauge controls whether the Gauge is visible to users or not.   You could choose to implement a pop-up, alert, or another visual indicator to the UI that would inform your application users. 7. Select the new Gauge in the Mashup or Explorer pane. 8. Clear the GaugeFaceStyle Style Definition and replace it with the DefaultChartStyle11.   9. Click Save and View Mashup to see the changes. Using Expression Widgets to Handle Events   Expression Widgets are a great asset to handle information being passed around inside of a Mashup and also events occurring within a Mashup. In this scenario, we will use the Count property value to create changes in the UI.   Setup Expression Widget   In the Functions Tab in the bottom right. Add a new function.   Set the Function Type to Expression and name it HighCount.   Click Next Click Add Parameter and add a Count (Number) parameter. Set the Expression property to output = Count >= 9;.   Check the Auto Evaluate and Fire on First Value checkboxes. Click Done.     Bind and Evaluate Event   In the Functions Tab in the bottom right, click the bind button of our new Function.   Click the dropdown by the Count input parameter. Click Add Source.   Select Data, then the Count_Property from the GetPropertyValues service.   Redo the past steps for a second Function. Name this function GaugeVisibility with a parameter of type Boolean with the name Visibility. Update the second Expression Widget’s Expression property to output = Visibility != true;. Ensure the checkboxes are checked and bind to the output of our last Function.   Connect the output of this Function to the second Gauge. Click Save and View Mashup.   NOTE: Move the Gauges from on top of one another if necessary to set values and parameters. The first Expression will show the newest Gauge Widget when Count hits 9. The other Expression Widget will show the original Gauge based on the evaluation of the first Expression Widget results.   Click the Increment the Count button to see how the display changes in the Mashup at runtime.   Step 6: Next Steps   The next guide in the Customize UI and Display Options to Deploy Applications learning path is Object-Oriented UI Design Tips.    Additional Resources   If you have questions, issues, or need additional information, refer to:   Resource Link Community Developer Community Forum Support Style & Themes Help Center  

    Use Thing Shapes to create groups of related Properties   Guide Concept   Save time and effort by modeling a solution in ThingWorx using Thing Shapes to group Properties. A logical group of Properties can be applied to Things and Thing Templates.     You'll learn how to   Create a Thing Shape Add Properties to a Thing Shape   NOTE: This guide's content aligns with ThingWorx 9.3. The estimated time to complete this guide is 30 minutes       Step 1: Create Thing Shape   In this section you will create a Thing Shape for sensor properties of a MXChip development board.   Thing Shapes are components that contain Properties and Services. In Java programming terms, they are similar to an interface.   Start on the Browse folder icon of ThingWorx Composer. Under the Modeling section of the left-hand navigation panel hover over Thing Shapes, then click the + button.   Type ThermostatShape in the Name field.   If Project is not already set, click the + in the Project text box and select the PTCDefaultProject. Click Save.     Step 2: Add Properties to Thing Shape   Click Properties and Alerts tab at the top of your Thing Shape.   Click + Add. Enter the Property name in the Name field as shown in the table below. Name Base     Type           Persistent?       Logged? humidity NUMBER   X messageId STRING X   temperature NUMBER   X Select the appropriate Base Type from the drop-down menu.   Check Persistent and/or Logged according to the table. NOTE: When Persistent is selected, the property value will be retained during a system restart. Properties that are not persisted will be reset to the default during a system restart. When Logged is selected, every property value change will be automatically logged to a specified Value Stream. Click Check +. TIP: When adding multiple properties at once, click Done and Add after each, once you've entered a Name, selected a Base Type and any other criteria. If adding a single property, click Done. Repeat steps 4 through 6 for each of the properties in the rows of the table. Click the done Check. You'll see that these Properties have been created for the ThermostatShape.   Click Save.     Step 3: Next Steps   Congratulations! You've successfully completed the Create A Thing Shape, and learned how to: Create a new Thing Shape Add Properties to the Thing Shape   This is the last guide in the Azure MXChip Development Kit Learning Path.  If you wish to return to the Learning Path, click the link.   Learn More   The following resources continue your learning experience:  Resource       Link Build Data Model Introduction Experience Object-Oriented UI Design Tips   Additional Resources   If you have questions, issues, or need additional information, refer to:  Resource       Link Community Developer Community Forum Support Thing Shape Support Help Center      

Abstract This article explores an approach on how to optimize ThingWorx thread usage during service execution. It addresses common scenario where the Event Processor executor thread pool can become saturated, which can lead to queuing and slow responsiveness to users. This article is a proposal for configuring and optimizing services, with an example. Please, use the post comments to provide feedback or suggestions. All used capabilities are 100% ThingWorx OOTB. In the following, the acronym SETO (Service execution thread optimization) will be used to refer to entities and their capabilities.   Introduction During the execution of a service, events trigger a subscription that runs in a new thread. In addition to the best practices for timers and schedulers, SETO uses this mechanism to parallelize the execution of a service across subdivisions of a population of Things. When using ThingWorx, clients often encounter issues related to the regular execution of services such as "get data" or "update KPIs".  These services, when executed frequently, can lead to several challenges: Single thread processing: Processing occurs only in one thread, might lead to long execution time. Thread Pool Saturation: When too many services are executed simultaneously, the thread pool can become saturated, slowing down the entire system. Queue Overflows: Thread pool saturation can lead to queue overflows, where new tasks cannot be processed in time. Task Loss: Overflows can result in the loss of important tasks, affecting service reliability. Unresponsive Server: Due to overload, the server can become unresponsive, impacting user experience and operational continuity. Data processing requirements often lead to decreasing execution time without the required consideration towards impact on stability and availability of the other required services.  This post provides explanations and examples of how to think differently about how to execute data processing quickly and reliably while also focusing on the systems stability and reliability.   Why Use Service Execution Thread Optimization? To address these issues, Service Execution Thread Optimization (SETO) is essential. It allows for effective management of resource saturation and its consequences. SETO enables you to control the percent or number of used threads and the safety inter-execution delay.   Selective Execution Management Prioritized processing involves sorting tasks from oldest to newest, focusing on older tasks to prevent them from falling too far behind. However, it is crucial not to limit execution to only old tasks but to find a balance to process all eligible tasks. If all things don’t execute the service before the inter-execution delay, SETO skips them. These remaining things will be prioritized for the next timer event. Selectively orchestrating work execution allows designing your data processing workflow so that it is coherent with your various use cases functional requirements as well as being tuned for performance and your provisioned resources. This example covers functional requirements which require data to be processed within a 1-hour period, and hence sorts the processing by oldest first, and allows for skipping execution windows if the system is busy at that time. Your application of this approach may leverage a more complex approach suited to your needs that could add sensitive assets that should be processed with more urgency depending on the type or location of an asset.  This is where multiple copies of the SETO entity would adapt according to your use cases, selection criteria, work sorting, timing, thread usage configurations, etc.   Applicability and Ease of Use SETO has been designed to avoid touching the existing model as much as possible. The only prerequisite is to have a Datetime property on each Thing to track the last execution of the service, one property per service.   How to use it? Configuration of Allocated Threads Per Service 1. Create an Thing from the PTCSC.SETO.WorkProcessManager_TT ThingTemplate. 2. Configure the AllocatedThreadsPerService Table:   TS or TT: The entity type that carries the service. Accepted values are “TT” for ThingTemplate and “TS” for ThingShape TS or TT name: The name of the entity that carries the service. Service name: The name of the service you want to streamline the execution. Safety timeout: A security time value that defines a hard stop before the next timer trigger, in seconds. Minimum of 5 seconds. Example: If my timer is set to 3 minutes and my safety timeout is set to 10, the service won’t be executed on remaining things at 2 minutes and 50 seconds. The safety timeout must be less than the timer update rate. Last update property name: The name of the datetime property on things used to store the last service execution timestamp. Update older than: The minimum number of minutes since the last update before the service is triggered on an object. If set to 0, all things will be taken in account anytime. Percent available thread: The percentage of available thread to use. Value constrained from 0 to 99. This value is truncated to select a round number. Example: 13 threads available, 60% requested → 13*0,6=7,8, so 7 threads will be used. Use number of threads: Way to the select the requested number of threads. TRUE, use percent of available threads / FALSE, use the number of threads value column. Number of threads: Maximum number of threads allowed to run in parallel to process the list of things. This number should be set to leave at least a few threads free. SETO let at least on thread free, so the number of request threads might be lower or equal to zero. The remaining thread might be used by other execution outside SETO. 3. Creating a Subscription in the new Thing.   Create a Subscription to link the Timer to the Service to execute.   Result example The following example demonstrates how logging is seamlessly integrated into SETO during the execution optimization process. Logging is part of the ServiceExecution_SUB subscription in PTCSC.SETO.WorkProcessManager_TT ThingTemplate.   Important Notes Appropriate entity selection, sorting, scheduling algorithms will depend on the specific use cases and workload. SETO uses QueryImplementingThingsOptimized for better performance, so indexing is encouraged. Processing needs to address resulting status and potentially needed retries as a part of the scheduling algorithm.  You'll want to add use case specific logic which ensures the entities with failing processing are only attempted a couple of times and that their error state is notified and addressed by a system administrator. Ex: just sorting by oldest last execution time will cause anomalous non-working entities to surface to the top and taking priority over all other processing (this is an anti-pattern to avoid, requiring a circuit breaker) SETO can only trigger Services without input parameters.  You could evolve the concept to leverage passing Service parameters through JSON property event data. In this article, a Timer is used to trigger a regular event. As best practice, it is better to use a Scheduler (regular as a Timer) Indeed, when server starts, all timers will start. Scheduler trigger depends on current datetime and not on sever startup.   Conclusion and provided file By optimizing Service execution, businesses can improve the performance and reliability of their applications built on the ThingWorx Platform. Proper configuration helps prevent common issues and ensures smooth service execution. Find attached to this article the SETO entities valid from version 9.3.   I've just put resource here as more generic as it is not only the thread pool that would become saturated in the given context.  It could be many other aspects downstream which are tightly coupled like the database.     NB: thanks to Greg EVA for sharing knowledge and review. 

  Step 8: Troubleshooting   Issue                                       Resolution CSS does not seem to be applied to the Mashup. Verify your CSS is included in the runtime TWX CSS. Clear Browser cache if your CSS is not merged to the combined TWX CSS. (under debug mode: Hold refresh button->Clear Cache). TWX fails to import the extension. If the extension is already installed, but you made recent changes, you need to bump the Version number in the metadata.xml. Recent CSS changes are ignored. Clear browser cache if your CSS file has changed recently.     Step 9: Next Steps   Congratulations! You've successfully completed the Add Style to Your UI with CSS guide, and learned how to:   Create custom CSS classes using the integrated CSS editor Bind CSS classes to a Mashup and to individual Widgets Use Media queries to dynamically apply styling   Learn More   We recommend the following resources to continue your learning experience:    Capability     Guide Build Application Development Tips & Tricks Experience ThingWorx Application Development Reference   Additional Resources   If you have questions, issues, or need additional information, refer to:  Resource       Link Community Developer Community Forum Support Help Center