IoT & Connectivity Tips

Containerization has been a cornerstone of modern software deployment, offering well-known benefits like portability, scalability, and consistency across environments. In the industrial IoT (IIoT) space, these advantages are particularly valuable, enabling organizations to manage complex systems with greater agility and efficiency. At PTC, we recognize that while containerization is not new, its application in IIoT continues to evolve, and our platforms—ThingWorx and Kepware—are designed to help you harness its full potential in practical, impactful ways. ThingWorx: Streamlining IIoT with Containerization ThingWorx has supported containerization for some time now allowing users to build ThingWorx Docker Container images and deploy applications with ease, whether on-premises, in the cloud, or in hybrid setups. This approach simplifies the deployment process, reduces configuration overhead, and ensures that your IIoT solutions can scale as your needs grow. For those already familiar with containerization, ThingWorx offers Dockerfiles allowing customers to build, run, and deploy, ThingWorx as Docker Containers for  development and production use cases. See our help center for already available information on this: https://support.ptc.com/help/thingworx/platform/r9.7/en/index.html#page/ThingWorx/Help/Installation/ThingWorxDockerGuide/thingworx_docker_landing_page.html     New Resource: Deploying ThingWorx on Kubernetes As container adoption matures, so does the need for robust orchestration tools. That’s why we’re excited to introduce a new best practices guide for deploying ThingWorx containers on Kubernetes, with a focus on Azure Kubernetes Service (AKS). This guide is designed to help you take the next step in managing your containerized applications at scale, offering information on: Setting up and managing Helm chart repositories. Preparing your Azure environment, including resource groups, virtual networks, and container registries. Creating and managing content repositories for Docker images. Deploying and configuring Azure Kubernetes Service (AKS) clusters. Implementing essential supporting components such as Monitoring Stacks, Certificate Managers, Ingress Controllers, Azure PostgreSQL Databases, and Storage Accounts to facilitate ThingWorx deployment. Detailed steps to deploy ThingWorx in various configurations, including standalone , high availability (HA) , and with eMessage Connector (eMC). Procedures for upgrading ThingWorx deployments   You can access this guide on our GitHub repository: ThingWorx Kubernetes Deployment (twx-k8s). Whether you’re scaling to support thousands of devices or simply looking for more efficient management of your IIoT infrastructure, this guide helps you with the best practices you need to succeed in your containerization efforts for ThingWorx.     Kepware Edge: Connectivity at the Source On the connectivity front, Kepware Edge brings the power of containerization directly to the edge of your operations. By packaging industrial-grade connectivity into a lightweight, container-friendly solution, Kepware Edge allows you to deploy secure, reliable data access right where your machines and devices are located. For more details on how Kepware Edge, check out our recent announcement: PTC Announces Kepware Edge and stay tuned for more updates on the availability of it.     Practical Tools for Your IIoT Journey Improving DevOps for applications built on ThingWorx is a key priority for us at PTC and containerization is a critical piece to it. We invite you to explore these resources and see how they can fit into your existing IIoT solution development workflows. Visit the ThingWorx Kubernetes guide on GitHub and let us know your feedback or any questions around containerization by posting on the IoT community.   Cheers, Ayush Tiwari Director Product Management, ThingWorx

Introduction In the dynamic landscape of IoT and industrial applications, development teams often face challenges such as limited visibility into application behavior, fragmented tooling, and time-consuming troubleshooting processes. To address these pain points, PTC has launched a DevOps initiative aimed at strengthening the ThingWorx low-code platform. This initiative delivers key enhancements in debugging, source control, monitoring, alerting, logging, and AI-driven development support. As ThingWorx continues to evolve, our commitment remains centered on improving the day-to-day experience for both developers and administrators. We've been listening closely to your feedback—this new project reflects our response, focusing on smoother DevOps integration and empowering users with deeper control and visibility into their applications. While many enterprises already rely on IT-recommended tools to manage the application lifecycle and Day-2 operations, PTC is committed to complementing these investments by delivering additional capabilities and guidance tailored to the ThingWorx platform. Key features of the new devOps project initiative include real-time debugging and version control, the ability to roll back to previous versions, hot-fix deployments, and distributed team development through seamless integration with repositories like GitHub. Furthermore, streamlined application packaging and deployment significantly simplify the management of ThingWorx-based applications. These enhancements go beyond routine updates and reflect a meaningful evolution in how teams develop, troubleshoot, and optimize IoT applications in production environments.  Debugging : Preview in ThingWorx 10.0   The first major feature introduced under DevOps is the debugging capability, currently available in a private preview (alpha version). Debugging has long been a challenge in ThingWorx applications, where troubleshooting JavaScript code within the platform was often cumbersome and time-consuming. With the new JavaScript Debugger, developers can now debug their scripts directly within ThingWorx Composer, reducing the time spent identifying and fixing issues. This feature brings real-time issue resolution, allowing developers to pinpoint errors efficiently without needing external tools.   Security and seamless integration into the existing ThingWorx environment were critical design considerations for this feature. The debugging actions are logged securely for audit and compliance, ensuring that sensitive information remains protected. Furthermore, support for major browsers such as Chrome, Firefox, Edge, and Safari enhances the accessibility of this feature across different development environments. The debugging capability is expected to significantly improve developer productivity by offering better visibility into JavaScript execution and real-time error tracking, reducing the trial-and-error approach that developers previously relied upon. Here is a brief video offering a preview of upcoming features included in the ThingWorx 10.0 release, with general availability planned for the 10.1 release later this year.   Debugger Capability (Preview) Logging and Monitoring : Continuous improvement   In addition to the new debugging capabilities, we’ve delivered several enhancements focused on monitoring and alerting—specifically designed to support the needs of IT administrators responsible for maintaining the uptime and reliability of ThingWorx environments in the last major release. The integration of OpenTelemetry has transformed logging and performance monitoring, allowing better observability of system operations. This enhancement enables third-party integrations with monitoring tools such as Sumo Logic, Datadog, and Splunk, providing developers and administrators with deeper insights into system performance. These improvements have made ThingWorx more resilient and responsive, allowing teams to proactively detect and address issues before they impact operations. Mashup Builder : Continuous improvement   We have been continuously enhancing Mashup development capabilities, starting with the introduction of Read-Only Mashups in ThingWorx 9.6 and extending through to the latest improvements in recent releases. Also, a new Export Function replaces the legacy Data Export Widget, offering a more secure and efficient data export process. Binding Verification & Debugging introduces a powerful capability to detect and resolve broken bindings after mashup migrations, reducing errors and improving reliability. Improved UI Management features, such as widget highlighting and container zooming, make mashup creation and debugging more intuitive. Additionally, developers can now customize Tab Titles & Favicons, enabling better branding and a more polished user experience for ThingWorx applications. Mash up improvements in ThingWorx 9.7 The Road Ahead: AI-Powered Development and Version Control   The next phase of the DevOps initiative is set to deliver major advancements in source control and AI-driven development. One key enhancement is the addition of IDE-like features for source code management, enabling developers to better track, iterate, and roll back changes. Planned integrations with GitHub and other repositories will support seamless collaboration in distributed teams.   We welcome your feedback as you explore the new Debugger Feature Preview included in the ThingWorx 10.0 release. In parallel, we are actively working with customers and partners to enhance key capabilities such as source code version control and application lifecycle management within the ThingWorx platform. If you're interested in contributing to the future of low-code development, we encourage you to share your thoughts in the comments below—our team will be in touch to connect.   Vineet Khokhar Principal Product Manager, IoT Security Stay tuned for more updates as we approach the release of ThingWorx 10.0, and as always, in case of issues, feel free to reach out to <support.ptc.com>  

Leveraging ThingWorx for Unified Namespace with Sparkplug B Integration   Abstract   The industrial IoT (IIoT) landscape demands scalable, interoperable, and real-time data architectures to enable seamless communication across heterogeneous systems. Unified Namespace (UNS) has emerged as a new approach to organizing and contextualizing data in a centralized, hierarchical structure accessible to all devices and applications. This article explores how PTC’s ThingWorx, a leading IIoT platform, can serve as a robust foundation for operationalizing a UNS, with a specific focus on integrating MQTT-based Sparkplug B messaging. Building on the open-source SparkplugB-Edge-SDK provided by the ThingWorx Customer Success team, we demonstrate how ThingWorx can bridge edge devices, industrial systems, and enterprise applications within a UNS framework, delivering real-time visibility, scalability, and operational efficiency.   1. Introduction   1.1 The Need for Unified Namespace   In traditional industrial environments, data silos and protocol disparities hinder operational efficiency and decision-making. A Unified Namespace (UNS) addresses these challenges by providing a single, logical, and hierarchical data structure that serves as a "single source of truth" for all systems. While customers using ThingWorx have been implementing UNS without realizing it, recently when people say UNS, they also associate it with leveraging MQTT with it.  MQTT (Message Queuing Telemetry Transport) as a lightweight messaging protocol, with Sparkplug B enhancing it by adding a standardized topic structure and payload format helps enterprises with a starting point for implementing UNS.     1.2 ThingWorx: An IIoT Platform for Modern Architectures   PTC ThingWorx is a comprehensive IIoT platform designed to model, connect, and manage industrial assets while providing tools for data visualization, analytics, and integration. Its extensible architecture and support for standards like MQTT make it an ideal candidate for operationalizing a UNS. This paper builds on an example implementation, the SparkplugB-Edge-SDK, to illustrate how ThingWorx can operationalize a UNS in real-world scenarios.   2. Understanding Unified Namespace and Sparkplug B   2.1 Unified Namespace Overview   A UNS is a hierarchical naming convention that organizes all data—sensors, machines, processes, and enterprise systems—into a structured, globally accessible namespace. For example, a UNS topic might look like: FactoryA/Line1/Machine1/Sensor1/Voltage This structure ensures that data is self-describing, context-rich, and universally interpretable across the enterprise.   2.2 Sparkplug B: Enhancing MQTT for Industrial IoT   Sparkplug B is an open specification that builds on MQTT to provide a standardized framework for IIoT data exchange. Key features include: Topic Namespace: A predefined structure (e.g., spBv1.0/GroupID/MESSAGE_TYPE/NodeID/DeviceID) for consistent data addressing. State Management: Birth and death certificates to manage device connectivity. Efficient Payloads: Binary encoding via Google Protocol Buffers for compact, high-performance data transfer. Sparkplug B aligns naturally with UNS by enforcing a structured, interoperable data model suitable for industrial environments.   3. ThingWorx and Sparkplug B Integration   3.1 The SparkplugB-Edge-SDK   PTC offers several connectivity options with Kepware for industrial connectivity providing protocol transformation, and ThingWorx Edge SDKs for custom connectivity in developer friendly languages such as C-SDK, .NET SDK, and Java SDK to connect any asset with ThingWorx natively using WebSocket based AlwaysOn protocol. The SparkplugB-Edge-SDK (source and executable JAR available at https://github.com/thingworx-field-work/SparkplugB-Edge-SDK) is a Java-based component developed using ThingWorx Edge Java SDK. It integrates ThingWorx with Sparkplug B-enabled edge devices, enabling bidirectional communication over MQTT. Key components include: MQTT Client: Connects to an MQTT broker (e.g., Eclipse Mosquitto, HiveMQ) to publish and subscribe to Sparkplug B topics. ThingWorx Edge SDK Integration: Maps Sparkplug B data to ThingWorx entities (Things, Properties, Services). Configuration Flexibility: Supports customizable mappings between Sparkplug B metrics and ThingWorx data models. This SDK serves as a reference implementation for bridging edge devices with ThingWorx in a UNS context.   3.2 Architecture Overview   The proposed architecture integrates ThingWorx with a UNS as follows: Edge Layer: Devices publish data to an MQTT broker using Sparkplug B topics Broker Layer: An MQTT broker (e.g., Mosquitto) acts as the central hub, routing Sparkplug B messages. Application Layer: ThingWorx subscribes to the broker, ingests data, and maps it to its internal data model, exposing it via REST APIs, mashups, or analytics. This layered approach ensures scalability and decoupling of edge and enterprise systems.     4. Implementation Details   4.1 Setting Up the Environment   To implement a UNS with ThingWorx and Sparkplug B: Deploy an MQTT Broker: Install and configure an MQTT broker (e.g., Mosquitto) to handle Sparkplug B traffic. Configure the SparkplugB-Edge-SDK: Clone the repository: git clone <https://github.com/thingworx-field-work/SparkplugB-Edge-SDK.> Update configuration files (e.g., SparkplugBEdge.json) with MQTT broker details and ThingWorx connection credentials (URL, AppKey). Deploy the SDK on edge devices or gateways. Model in ThingWorx: Create Thing Templates and Things corresponding to edge devices. Define Properties to mirror Sparkplug B metrics (e.g., Voltage, Temperature, Pressure).   4.2 Mapping Sparkplug B to ThingWorx   The SDK maps Sparkplug B payloads to ThingWorx entities. For example: Sparkplug Topic: spBv1.0/FactoryA/DDATA/Node1/Device1/Voltage ThingWorx Entity: A Thing named FactoryA_Node1_Device1 with a Property Voltage. The SDK handles: Data Ingestion: Subscribes to Sparkplug B topics and updates ThingWorx Properties in real time. Event Handling: Processes Birth/Death messages to manage device state in ThingWorx.   4.3 Extending the UNS   ThingWorx’s extensibility allows the UNS to evolve: Services: Custom services can aggregate or transform data (e.g., calculating averages across a production line). Mashups: Visualize the UNS hierarchy using ThingWorx’s UI tools. Analytics: Integrate with ThingWorx Analytics to derive insights from UNS data.   5. Benefits of ThingWorx in a UNS   Scalability: ThingWorx’s distributed architecture supports thousands of edge devices within a UNS. Interoperability: Seamless integration with edge using Sparkplug B and with different systems using REST API OR OOTB connectors ensures compatibility with diverse industrial protocols and systems. Real-Time Visibility: Immediate data updates enable responsive decision-making. Extensibility: Developers can enhance the UNS with custom logic, integration, and visualizations.   6. Case Study: Manufacturing Line Monitoring   Consider a factory with multiple production lines. Using the SparkplugB-Edge-SDK: Edge sensors publish data to spBv1.0/FactoryA/DDATA/Line1/Machine1/ Voltage. The SDK relays this to ThingWorx, updating the Line1_Machine1 Thing’s Voltage Property. A ThingWorx mashup displays real-time Voltage (and properties like RPM, Torque/Current, Power Factor, etc.,) across all machines, organized by the UNS hierarchy. Alerts trigger if Voltage exceed thresholds, demonstrating actionable insights derived from the UNS. This setup provides a cohesive, scalable monitoring solution.   7. Challenges and Considerations   Network Reliability: MQTT requires a stable connection; ThingWorx’s data storage capabilities can mitigate disruptions. Data Volume: High-frequency updates may strain resources; optimize payload sizes and subscription rates. Security: Secure MQTT with TLS and enforce ThingWorx access controls to protect the UNS.   8. Conclusion   ThingWorx, offers a powerful platform for operationalizing a Unified Namespace in industrial IoT environments. By leveraging Sparkplug B’s standardized messaging and ThingWorx’s robust data management and visualization capabilities, organizations can achieve a scalable, interoperable, and real-time data architecture. This article provides a high-level blueprint for integrating these technologies, empowering industries to unlock the full potential of their data.   9. Road ahead   ThingWorx already ingests data over MQTT using the MQTT extension, this Sparkplug-edge SDK, Kepware, or via Azure IoT hub, but with IoT Streams capability introduced in ThingWorx v10.0, users will have the ability to send contextualized IoT data for further analysis and intelligence for end to end Industrial Data Management and UNS needs. PTC plans to provide more OOTB capabilities to ingest MQTT data coming into ThingWorx, contextualize it, and make that contextualize data rapidly available over MQTT to other resources at scale. Stay tuned!     As ThingWorx community members get further along their journey of implementing UNS using ThingWorx, please do not hesitate to provide us your feedback or ask questions in the ThingWorx IoT community.       Cheers, Ayush Tiwari Director Product Management, ThingWorx.  

    April 22, 2025   Hello ThingWorx community members! We are excited to announce the preview release of ThingWorx 10.0, the latest evolution of our IIoT platform for all your Industrial Data Management needs. This release focuses on delivering a powerful, secure, and intelligent foundation for industrial innovation, empowering businesses to achieve more with their IoT solutions. Powerful & Secure: A New Standard in IoT Platforms ThingWorx 10.0 sets a new benchmark for scalability and security in IoT with features like IOT Streams to enhance enterprise industrial data acccess and reliability, caching improvements to increase server scale and response times, and security updates for TLS, Tomcat, Java, and others to ensure top-tier performance and protection. These advancements make ThingWorx 10.0 the most mature and secure platform yet, giving businesses the confidence to scale their IoT deployments while safeguarding their data.   Industrial Solutions: Ready to Drive Performance ThingWorx 10.0 enhances our industrial solutions, advancing connected worker, manufacturing efficiency, and quality use cases. Windchill Navigate View Work Instructions, a powerful, feature-rich app, launches with ThingWorx 10.0. Built on ThingWorx and integrated with Windchill PLM, this task-based solution delivers real-time work instructions, enhancing enterprise collaboration and boosting worker productivity with seamless, intuitive guidance. Alongside Connected Work Cell (CWC), both applications strengthen the connected worker experience in manufacturing with real-time instructions and data. Additionally, enhancements to Real-Time Production Performance Monitoring (RTPPM), and Digital Performance Management (DPM), improve manufacturing performance by optimizing workflows, enhancing service quality, and providing operators with clear, data-driven insights. Data Insights: Unlocking Intelligence from Edge to Cloud ThingWorx 10.0 empowers businesses to harness data-driven intelligence like never before. With advanced analytics and integration with third-party generative AI tools, the platform enables seamless management of industrial data from edge to cloud. Unlock actionable insights and make smarter decisions to stay ahead in a competitive landscape. Get started today The preview release of ThingWorx 10.0 is now available for evaluation. Discover how a powerful, secure, and intelligent IoT platform can transform your industrial operations. Please reach out to your account reps or customer success team to get preview access for this release. Alternatively, drop a comment on this post or submit a Tech Support ticket, and we’ll get in touch with you to discuss onboarding to the ThingWorx 10.0 Private Preview Program.   Lastly watch out this space as we roll out additional details about ThingWorx 10.0 release and other announcements!   Cheers! Ayush Tiwari Director Product Management ThingWorx, a PTC Technology.

Improvements in Monitoring and Diagnostics The Outcome of the Diagnostics Forum of Yesterday By Tori Firewind, Principal Cloud Architect Introduction Many moons ago, a forum of dedicated diagnostic enthusiasts gathered together throughout several round-table discussions to produce a list of diagnostic daydreams, groom and refine that list, and then use it to produce realistic, yet awesome diagnostics requirements. Three different organizations, eight teams in total across PTC were involved, and dozens of real-world, customer experiences were considered throughout these conferences. In the end, a large diagnostics feature was designed and passed already prioritized, from the front lines directly into the backlog in the first ever collaborative effort to do Dev Ops as a process at PTC.   The fruits of this labor are now available in the latest version, ThingWorx 9.7! These features include the largely anticipated acceleration-based monitoring, custom persistence provider monitoring, and the ability to turn off metrics as needed, as well as additional open telemetry integrations and capabilities. This article will spotlight some of these new features and direct you to the 9.7 Help Center pages for more information. The Platform is smarter and Dev Ops easier than ever before, with the latest and greatest in monitoring found right here in ThingWorx 9.7.   Acceleration-Based Monitoring This is an extremely cool new feature in ThingWorx where the Platform monitors itself for runaway queues, those which indicate a system malfunction in the event or value stream queues for instance. If the acceleration is high enough for that queue, the Platform will automatically generate stack traces. This ensures the diagnostic data is already on the disc if and when the issue progresses to an outage.   No more do diagnostic SMEs have to sit and wait for a problem to occur again before they start investigating! Now they can download the stack traces that the Platform already stored on the disc.   Of course, it’s really important to get this feature configured right. If thread dumps are taken too often, those associated with the root cause may be purged before a tech can look more closely; only 10 thread dumps at a time are stored on the disc to prevent it growing out of proportion. On the other hand, if it does not take thread dumps often enough or in response to the right kinds of acceleration readings, then the root cause may altogether not be captured.   For this reason, there are several parameters to use to configure this feature, one being the acceleration increase percentage, considered very significant and a potential sign of trouble within the queue. This value is a flat percentage calculated at the time of measurement: queue count / total size of the queue. This number is checked frequently, as configured by another parameter, the acceleration calculation frequency. If the queue size exceeds the queue capacity occupied percentage at the same time the increase percentage is above the threshold, then the Platform records a stack trace on the disc. This ensures the diagnostic data will be present even after a restart, from early on when the problem began.   Another key parameter is the number of acceleration occurrences to wait before turning the thread captures on, which allows for a great specificity of when to collect the diagnostic data. Even if the acceleration is met once, well maybe that means nothing; perhaps it is normal for the queue to accelerate quickly at times. However, let’s say it does it 5 times within 30 seconds or a minute, or maybe the acceleration is elevated for some time, and we are approaching a data loss scenario. A rule based around the first scenario will capture close to the root cause, while the second might serve to collect what events didn’t make it into the queue before the restart.   Once the thread dumps are taken, there is a configurable cool off period in which no new stack traces will be recorded. This can allow the stack traces to be taken repeatedly at set intervals for persistent issues, and also reduces the overall activity of recording stack traces to ensure only the most useful ones remain on the disc.   One of five queues can be monitored in this way: Persistent Property Queue Event Processing Queue Stream Processing Queue Value Stream Processing Queue Connections Pool Processing Queue An example of setting all of these values can be found along with more information in the Help Center.   Custom Persistence Provider Monitoring There is now the capacity to see what the Platform is doing when interacting with your own custom persistence providers, or those used by the various ThingWorx applications like Navigate or DPM. At the monitoring endpoint, all persistence providers will now be listed at /Metrics, tagged by their name and database type:     # HELP thingworx_ThingworxPersistenceProvider_ConnectionPool_BusyConnections Current count of busy connections to the underlying database # TYPE thingworx_ThingworxPersistenceProvider_ConnectionPool_BusyConnections gauge thingworx_ThingworxPersistenceProvider_ConnectionPool_BusyConnections{category="DPMpersistenceProvider.ConnectionPool",databaseType="Microsoft SQL Server",otel_scope_name="com.thingworx",persistenceProviderEntityName="DPMpersistenceProvider",platformid="",prefix="Platform.Core.PersistenceProvider"} 0.0 thingworx_ThingworxPersistenceProvider_ConnectionPool_BusyConnections{category="ThingworxPersistenceProvider.ConnectionPool",databaseType="PostgreSQL",otel_scope_name="com.thingworx",persistenceProviderEntityName="ThingworxPersistenceProvider",platformid="",prefix="Platform.Core.PersistenceProvider"} 0.0     For more information about which parts of the persistence providers are monitored, see the Help Center.   Disable Metrics Now there is the potential to turn off some metrics if they become problematic or threaten to destabilize the entire environment. For example, the Audit Subsystem has a history of causing such issues for many, since the database tables grow very large and counting the rows can begin to take time. Turning these metrics off is now something easily done in the next maintenance window.   Simply add some code to your platform-settings.json file and restart the server, and whatever metrics specified will no longer be captured or appear at the metrics endpoints:     "MetricsSettings": { "DisabledMetricsList": [ "<metrics name 1>", "<metrics name 2>", "<metrics name 3>" ] }     Please note that there are several caveats and a warning to those who would turn off default monitoring features: ensure critical metrics are not unintentionally turned off and remember that this feature is intended for administrators who know the system well and need the ability to fine-tune its monitoring to ensure performance. Read more about this feature and its caveats in the Help Center.   Open Telemetry OpenTelemetry support was introduced in 9.6 and expanded in ThingWorx 9.7 to facilitate the recording of high volume monitoring metrics. It handles large-scale metrics and provides a more robust observability and capability for both diagnostic and predictive analysis. Find the new endpoint at /MetricsHC, with the old metrics still available as before. You can also use this metrics library to create your own custom metrics in a ThingWorx Extension, really expanding the metrics capability of the Platform. More information on how to make use of OpenTelemetry for monitoring can be found in the Help Center.   Conclusion ThingWorx does Dev Ops now better than ever, with features like these coming straight from real-world experiences and going right into the development workflow. Already, 4 additional monitoring features have been thought up and added to the mix, and improvements are coming soon! With more feedback on how to better to Dev Ops in ThingWorx, feel free to reach out.