IoT Tips

  Hi, everyone!   In previous tech tips, we’ve introduced 9.0’s biggest feature, active-active clustering, and covered some of the main architectural components. Today, I’ll cover some other architectural configurations and the flexibility that active-active clustering provides to meet your IoT deployment needs.   Deployment Flexibility With Active-Active Clustering, ThingWorx allows you to achieve the highest availability of your IIoT system while still retaining the high degree of deployment flexibility that ThingWorx is known for.   It’s important to emphasize flexibility not only in where you deploy ThingWorx, but also in how  you deploy it. Flexibility is embedded in the ThingWorx architecture to suit your deployment needs. Let’s look at two interesting options.   Cost-Efficient Deployment The first example is deploying ThingWorx in a cost-efficient architecture for smaller or cost-sensitive deployments. Instead of each component on its own separate VM or box, ThingWorx Connection Server, ThingWorx Foundation Server, ZooKeeper, and Ignite are all installed on the same box.   With three boxes in parallel, the system still achieves high availability while reducing deployment costs by minimizing the number of servers utilized. A minimum of three servers is needed to achieve an odd number of instances required by ZooKeeper while still providing redundancy.   In order to optimize for cost while still providing high availability, there are a few factors to consider with this deployment. In this configuration, Ignite is run within the same JVM as ThingWorx Foundation, rather than on a different server. While this does reduce the overall footprint, Ignite will consume additional memory, sharing the resources with the ThingWorx Foundation platform. Since ThingWorx Connection Server is run on the same VM as ThingWorx Foundation Server, this introduces socket limitations, which can restrict the maximum number of connected devices.     In short, the example above illustrates how, while being in an active-active clustered environment, you still retain the deployment flexibility to optimize for your deployment needs. In this scenario, the architecture is optimized for a leaner, more cost-effective deployment at the expense of numbers of connections and memory.   Now, let’s walk through some common use cases where ThingWorx is deployed on premise on VMs or baremetal to support use cases that require a balance of availability and scalability at an affordable cost. A few of these examples include: On-premise deployment of ThingWorx Foundation to support a dedicated factory production line on a plant floor to improve its connected manufacturing operations. VM based on-site deployment of ThingWorx Foundation to support IoT applications for a Smart Building scenario. Smart Ship deployments managing key ship operations where ThingWorx is deployed on a ship and sends data intermittently to private data centers running ThingWorx on shore through a satellite network leveraging ThingWorx federation technology. A failover-proof redundant setup required to capture key service metrics for medical equipment for predictive failures and maintenance where ThingWorx is deployed in hospital premises. OEM Deployment with Common Components The second example covers how active-active clustering architectural components can be shared across multiple clusters to reduce the cost and complexity of deployment. This can include scenarios where a large deployment spans multiple sites, geographies or end customers.   In this deployment, there are two ThingWorx clusters that share a common ZooKeeper cluster and database layer. Within each cluster, both the Connection Server and ThingWorx Foundation with Ignite running as embedded are deployed on a VM.   For the shared components, proper separation measures must be taken to ensure security. For ZooKeeper, separate namespaces and authentication from the clients are required. For the shared database layer, each cluster must have a unique schema, a separate shared file system and separate user credentials with database-level isolation. Please note that with a large shared database across tenants, rather than a dedicated database for each tenant of HA cluster, there is a risk of impacting performance and availability of other tenants due to issues caused by one of the shared ones.     This architecture is optimized for a larger deployment comprised of multiple ThingWorx clusters requiring separation between the clusters, while still allowing the provider to share a common infrastructure for cost reduction.   Again, let’s walk through another few common use cases, including: A ThingWorx OEM hosting multiple ThingWorx Foundation instances in their managed data center or public cloud to offer applications with further customization abilities to their end users. In this case, an OEM vendor can offer multiple ThingWorx clusters in active-active cluster mode with shared pieces of infrastructure across multiple tenants. A ThingWorx enterprise customer looking to build and host different ThingWorx-based applications in their IT data center where each application is powered by an individual active-active cluster satisfying specific digital transformation use cases across the enterprise value chain, including those related to engineering, product, sales, marketing, supply chain, partners, service and support. A ThingWorx factory customer looking to host multiple ThingWorx applications from their main regional factory IT data center to cater to the IoT needs of different factories located in surrounding geographic regions. In this case, a customer could dedicate one HA cluster to each factory to enable that factory/site to power multiple IoT applications efficiently.   These two configurations are some of the lesser known—yet equally powerful—deployments of this new architecture. Again, flexibility of our deployment architecture is one of the key superpowers of the ThingWorx platform. And, the active-active fun doesn’t stop there! Be on the lookout for an upcoming LiveWorx session titled Active-Active Clustering with ThingWorx 9.0  (Session ID: IP1117B), future tech tips like this one, and, of course, the GA release of ThingWorx 9.0 (targeted for June 2020) where you can take advantage of this new functionality!   Let us know what you think in the comments!   Stay connected, Kaya      

  Hi everyone,   In anticipation of ThingWorx 9.0’s biggest feature, active-active clustering, we’d like to provide an architectural overview of a sample active-active configuration and its underlying components. If you haven’t already seen it, we invite you to read our previous Community tech tip, where we introduce the concept of active-active clustering for ThingWorx Foundation, which enables you to: significantly reduce unplanned downtime for your mission-critical services and apps support horizontal scalability of the ThingWorx Server where you can scale your services up and down based on your requirements easily run, package, deploy, and operate advanced apps and services with the help of intuitive browser-based navigation, interactive monitoring and debugging tools, and more deploy anywhere - public cloud, private datacenter, on-premise, hybrid, or even locally on your laptop with deep optimizations for Azure Now, before we go too deep, we’d like to let you know that you can continue to seamlessly upgrade from previous versions of ThingWorx releases to upcoming ThingWorx 9.0  releases. Previously, you could deploy ThingWorx Foundation in a “single server” mode, and, for a high availability in “active-passive cluster” mode (see here for details). In the ThingWorx 9.0 release and onwards, you’ll be able to continue to deploy ThingWorx Foundation in a “single server” mode and for high availability scenarios via our new “active-active cluster” mode. Please note that active-passive clustering configuration will no longer be supported in ThingWorx 9.0 or onwards.   Let’s start with a quick recap on how the ThingWorx Foundation 9.0 release would look like in single server deployment.   ThingWorx 9.0 Deployed in a "Single-Server" Architecture Below is a high-level diagram depicting the main architectural layers and components of ThingWorx Foundation deployed in a single server mode.   Deployment Components Below is a brief summary of all major architectural components and their purpose in the deployment architecture:   The Client Layer This layer is comprised of everything that connects with, sends data to, and receives content from the ThingWorx platform. It be broken down into two groups: Devices/Things: Things, devices, agents, and other assets. Users/Clients: People and the respective products (primarily web browsers) they use to access ThingWorx.   The Application Layer This layer is where ThingWorx Foundation and other applications deployed with ThingWorx Foundation reside, such as ThingWorx Analytics, ThingWorx Connection Server, ThingWorx Azure IoT Hub Connector and others. This layer provides connectivity to the client layer, performs authentication and authorization checks, ingests/processes/analyzes content, and reacts to conditions by sending alerts. For a specific ThingWorx Foundation deployment that needs basic device data ingestion, processing and storage, you can setup only ThingWorx Foundation server. In some cases, with large number of device connections, you may want to setup ThingWorx Connection Server with ThingWorx Foundation in a single server for further scalable connectivity. ThingWorx Foundation: ThingWorx Foundation is a java-based application that serves as a rapid, model-based application development platform. Shared File Storage: Shared Disk space to contain ThingWorx Storage repositories, store and archive log files accessed by all ThingWorx Foundation servers. A NAS file storage, AWS Elastic File System, or Azure Files and others could be used for this purpose.   The Data Layer ThingWorx Foundation includes several persistence provider implementations that enable you to choose a database option that best fits your use case. A persistence provider enables the connection to a data store and the ability to perform a CRUD operation on that data. See here for more information. Currently, there are two basic variations of persistence providers: Model Provider – Responsible for ThingWorx model metadata and system data. Data Provider – Responsible for runtime data ingested against the model elements, including streams, value streams, data tables, etc. ThingWorx supports H2 (in-memory Database), PostgreSQL, MS SQL Server and AzureSQL as both model and data providers, and InfluxDB as only a data provider. Please see here for model and data best practices.   ThingWorx 9.0 Deployed in an Active-Active Clustering Reference Architecture Below is a reference architecture diagram for ThingWorx 9.0 with multiple ThingWorx Foundation servers configured in an active-active cluster deployment. Please note that this is only one reference example of how ThingWorx 9.0 can be deployed in an active-active clustered environment. There could be other architectural configurations dependent upon the needs of the specific deployment. Deployment Components Once you have developed an understanding of the basic architectural components in a single server mode, below are the additional components required to run ThingWorx in active-active cluster mode.   The Client Layer This will be similar to what has been mentioned in the above single server configuration.   The Application Layer In this layer, if you’re familiar with ThingWorx active-passive cluster configuration, then you may be aware of most of the components used below—with the exception of a new component: Apache Ignite that provides Distributed Caching for the horizontally scalable ThingWorx Foundation servers. Load Balancer: A third-party device that receives network traffic and distributes requests among available servers. In active-active cluster configuration, the load balancer is used to direct WebSocket-based traffic to the ThingWorx Connection Servers while user requests (http/https) traffic is directly distributed to the ThingWorx Foundation servers. Users can continue to use a load balancer with ThingWorx 9.0 that they might already be using for their existing active-passive or single server deployments with ThingWorx 8.X or previous releases.  Some example load balancers include, but are not limited to: HAProxy, Azure Application Gateway, and AWS Application Load Balancer. ThingWorx Connection Services: These services handle all messages routing to and from devices, providing scalable connectivity to the ThingWorx Foundation Server. With the ThingWorx 9.0 release, ThingWorx Connection Services have been upgraded with many additional features to support active-active clustering of the ThingWorx Foundation servers, where now they route all WebSocket traffic in a round robin fashion to the connected ThingWorx Foundation servers. Depending upon the various use cases, one could use multiple ThingWorx Connection Services available, such as ThingWorx Connection Server, ThingWorx Azure IoT Hub Connector, and ThingWorx Protocol Adapter Toolkit. Please see here for further details. Please note that for ThingWorx 9.0 releases, ThingWorx Connection Server would be required in an active-active configuration to support all the WebSocket-based traffic routing, including egress of files and device messages from multiple ThingWorx Foundation servers back to the devices, and it would also serve as WebSocket communication from ThingWorx Mashup-based applications to ThingWorx Composer. ThingWorx Foundation: With ThingWorx 9.0 and onwards, you can set up ThingWorx Foundation servers in an N-active-active cluster model to provide higher availability to your applications and horizontally scale the Foundation server nodes up and down based on your scalability needs. Apache Zookeeper: Apache ZooKeeper is a centralized service for maintaining configuration information and naming as well as providing distributed synchronization and group services. It is a coordination service for distributed applications that enables synchronization across a cluster. Specific to ThingWorx, ZooKeeper is used for distributed locking, selecting a singleton server during the server initialization, service discovery for Apache Ignite, allowing it to find instances of ThingWorx Foundation servers. Apache Ignite: This offers a distributed cache for the active-active cluster setup. It is 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. In this configuration, Ignite is set up in a standalone cluster but can be run embedded within the ThingWorx Foundation. Running Ignite in a standalone cluster is more ideal for larger scale, as it supports higher vertical scale of memory in the deployment setup.   The Data Layer ThingWorx is largely database agnostic. You can continue to use officially supported persistence providers that you may already be using in your existing deployments based off of ThingWorx 8.X or previous releases. Please look out for an upcoming ThingWorx update as well as enhanced installation documents to help with your upgrade and migration questions with the general availability of ThingWorx 9.0. Please note that this diagram does not make the distinction between model and data providers; depending on your data ingestion needs, separate model and data providers can be used. As a reminder, all databases should be deployed in a high-availability configuration to help eliminate any single point of failure.   In closing, we can't wait to launch active-active clustering in 9.0 to help you: dramatically further reduce application downtime scale your deployments and more efficiently manage your apps, regardless of where they’re deployed   If you have any questions about active-active clustering or its architecture, please do not hesitate to reach out!   Stay connected! Kaya

  Hi, everyone!   We’re actively working towards the ThingWorx 9.0 release and we’re ready to provide a sneak peek into the biggest feature of 9.0: Active-Active Clustering for High Availability configuration.   You may be wondering: doesn’t ThingWorx already offer High Availability?   Yes, ThingWorx already supports a High Availability configuration. Previous versions of ThingWorx, such as ThingWorx 8.X version releases, support Active-Passive configuration, where 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.   So, how is ThingWorx Active-Active different?   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 all of the servers, instead of only one, 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.   Since all ThingWorx servers are active, they are processing in parallel and, as a result, the cluster can process more data than that of a single server or a cluster with an Active-Passive configuration. Simply put, multiple servers working together outperform a single server. This allows customers to scale their deployment by simply adding more ThingWorx servers to the cluster (horizontally scaling), which does not have the same limitations of scale that is achieved by increasing the performance of the server itself.   What does that mean for me? 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 - Now, 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.   Stay tuned! We’ll be posting more information on Active-Active Clustering—how it's achieved in ThingWorx, architectural component overviews, and what it means for your ThingWorx deployment!   In the meantime, we're running the Active-Active Clustering Beta Program. Interested in participating? Reach out to Ryan Servais (rservais@ptc.com) or Ayush Tiwari (atiwari@ptc.com) to learn more about participation!   Stay connected! Kaya

  Hello, everyone! Discover how we embed security throughout the entire lifecycle of the ThingWorx platform in our latest “ThingWorx on Air” episode!   Hear Walter walk through how the ThingWorx platform is secured from end to end. Walter breaks it down into three simple parts: secure design, secure coding practices and continuous security improvements via our maintenance releases.   Listen to Episode 07 to hear the steps we’re taking in each of these areas and how security is at the forefront of what we do.   Finally, Walter mentions the Secure Deployment Hub, our brand-new set of resources to help you securely deploy your ThingWorx apps. Check out my last tech tip to learn more.   As always, stay connected, Kaya

  Whether your ThingWorx instances are deployed on premise, in the cloud or a hybrid of the two, I’d like you to imagine: You have a super cool app. You want to deploy it securely. You’re not a security expert. What do you do? How do you know how to securely deploy your app? Where do you go for security best practices? Introducing the new ThingWox Secure Deployment Hub!   The ThingWorx Secure Deployment Hub is a new section of our support site that will introduce you to the ThingWorx security landscape and direct you to security resources pertaining to the Edge, the platform and beyond.   From permissions and provisioning, to subsystems and SSO, the hub is packed with our recommendations and best practices for you to deploy your app in a secure fashion.   Happy deploying! Kaya

  Happy New Year, everyone! New year, same mission. As we continue to improve ThingWorx, we remain committed to taking into account what you, our users, are saying. What are you using ThingWorx for? What do you want it to do? What additional tools are you looking for?   To hear from you directly, our PM team has created a quick survey to understand your identity management and SaaS strategies a little better.   Complete the survey below for a chance to win a free Solution Central t-shirt! Loading…   Thanks in advance! At the end of the survey, all respondents will receive a link to check out the latest in our ThingWorx 8.5 release. One lucky winner will receive the Solution Central t-shirt.   Thanks for sharing your info! We’ll be sure to study it as we continue to develop our robust IoT solutions platform.   Stay connected in the New Year! Kaya

  Whether you’re new to ThingWorx or you’re a seasoned user, understanding the Thing Model is key to accelerating your IoT development. Today, I’ll dive into what ThingShapes, ThingTemplates and Things are and how to use them to accelerate development.   Before I dive into the definitions of these concepts, let’s first consider the wide array of machines that exist out there in world. The variety is huge—there’s MRI machines, 3D printers, laser cutters, CNC machines, tractors, and so much more.   At their core, all MRI machines share similar properties and capabilities—they have a name, a physical location, a magnetic strength, a radio frequency current, and the ability to visually display what’s going on inside the human body. There are, however, different types of MRI machines, and, while they are fundamentally the same type of machine, there are notable differences as well. When creating our IoT app, it’s important that we have a way to model these differences so that we can cascade changes across entities and reduce development time.   Let’s walk through an example using MRI machines. Consider the various MRI machines that exist today; there’s the traditional closed MRI machine, the open MRI machine and the standing/sitting MRI machine.   To represent the fundamental properties (i.e., characteristics or readings) and services (i.e., functionality) of a generic MRI machine—name, location, magnetic strength, etc.—we’ll create a ThingTemplate. The ThingTemplate is the general definition/representation of the real-world physical thing (i.e. the MRI machine) that is being modeled. You can think of a ThingTemplate as a blueprint of what you’re modeling. A ThingTemplate defines what a Thing is; if you’re familiar with object-oriented programming, a ThingTemplate is similar to the concept of inheritance; it defines a “is a” relationship. Using our ThingTemplate, we’re able to create multiple instances of the template that inherit the properties and services from that template. If you have 100 MRI machines in a particular region, rather than updating each one separately, simply updating the template will allow you to propagate these changes.   Let’s say that, of our 100 MRI machines, 40 are traditional closed machines, 30 are open machines and 30 are standing/sitting machines. The traditional machines have a specific diameter of the opening where the patient goes in to lay down and the sitting/standing machine may have a particular height of the seat where the patient sits. Due to the nature of the machines having unique components/parts, the different types of machines have difference maintenance service.   To model each of these “add-on” properties, we’ll want to create a ThingShape. A ThingShape is a representation of particular properties or services that may optionally come in some versions of the machine but not others. The ThingShape is a single feature or piece of the physical thing that’s being modeled. You can think of a ThingShape as a reusable part, or a set of properties/services that comes with some versions, but not all. A ThingShape defines what a Thing has; if you’re familiar with object-oriented programming, a ThingShape is similar to the concept of composition; it defines a “has a” relationship. So, for our MRI example, we could create one ThingShape for the standing MRI and a second ThingShape for the closed MRI. The StandingMRIThingShape would have a property of “SeatHeight” and a service of “StandingMRIMaintenanceService.” The ClosedMRIThingShape would have a property of “opening diameter” and a service of “ClosedMRIMaintenanceService.” Just like a ThingTemplate, the properties and services that make up a ThingShape are also inherited by the instances that use that ThingShape.   Finally, Things. A Thing is simply an instance of a ThingTemplate with (optionally) ThingShapes added for additional unique properties/services.   Let’s say we want to model a single closed MRI machine. We’ll represent the machine as a Thing that inherits from Templates and Shapes. We’ll start with the MRIMachineThingTemplate so that we can create an MRI Machine Thing (i.e., instance).   Since this is a closed MRI machine and has the additional property of opening diameter, we’ll want to make sure we include that property. To do this, we’ll add the ClosedMRIThingShape.   Viola! We now have a digital twin of our closed MRI machine with all the base properties of an MRI machines from our MRIMachineThingTemplate and all the special add-ons of the closed version with our ClosedMRIMachineThingShape.   Here’s a visual recap of what we just modeled.   If you’re looking for even further guidance on how to model your data with the Thing Model, check out the Data Model Introduction guide on the Developer Portal to get started and the Design Your Data Model guide to learn even more.   Happy data modeling!   Stay connected, Kaya  

  Hello, everyone!   With the release of ThingWorx 8.5, we’ve incorporated a lot of new functionality into our manufacturing and service apps. To cover a few, I’ve included the list below. We created a manufacturing common layer extension to bundle all the PTC-offered IoT apps (Operator Advisor, Asset Advisor, Production KPIs and Controls Advisor) into one extension to enable you to use them even more quickly. We added a UI to Operator Advisor to strengthen your development of work instructions. We introduced new shift and crew data models and user interfaces to standardize how to track workers’ shifts and crew availability. We also introduced Flexible KPIs to help you more rapidly develop apps to calculate common metrics. We enhanced the Operator Advisor MPMLink connector to allow users to access navigation criteria for filtering parameters based on required criteria with support for standard processes. We incorporated multiple context supports for assets—like different business units, separating maintenance views from production views or segmenting sites by location—to allow segmentation based on role and responsibility, showing the power of ThingWorx networks and permissions.   Today, I’d like to highlight one of these areas in particular: flexible KPI calculations.   I spoke with one of product managers, Ward (who you may recognize from this post) to learn more about what this new feature does and the value it brings the business. Here’s what he said:   Kaya: Why did we create flexible KPIs? What was the challenge users were facing that led us to create them? Ward: While there is an industry standard for KPIs such as OEE, availability, productivity and quality, many customers choose to customize the calculations slightly and use their own specific versions in their decision-making process or production monitoring.    Kaya: What do the flexible KPIs do? Can you provide an example? Ward: KPIs can now be customized by ThingTemplate; this allows users to calculate KPIs differently for different “classes” of things. Imagine you have a group of CNC machines and a group of pumps. You want to calculate the availability of each group, but the availability calculation for the CNC machines may differ slightly from the same availability calculations for pumps. With our new flexible KPIs, you’re able to customize the availability calculation to make slight tweaks or changes based on differences in machines or devices. So, you can calculate the availability for both your CNC machines and for your pumps using your customized availability calculations. You can also create your own KPIs to calculate metrics like safety incidents or waste.   Kaya: Let’s dive a little deeper there. If I want to create a quality station for my robot with custom KPIs, how exactly would I do that? Ward: Let’s consider OEE. We have an OEE ThingShape applied to our ISA95 physical ThingTemplate. This shape has services to perform the OEE calculation. You’re able to customize the service on this template, so you have the flexibility to change the way you perform OEE calculations. Now, let’s say you want to add a new KPI like mean time between repair (MTBR). To do so, you would create a MTBR ThingShape and add it to the ThingTemplates where you want OEE calculated. Then, you would update the KPI manager service GetKPINames to add your ThingShape to the list of KPIs to be executed each iteration. The SCO apps will then execute your MTBR service along with the other KPIs.   Kaya: What are their use cases? How does they improve the business? Ward: Customers can have their cells roll up OEE based on the worse performing asset and have their operations roll up on a different criterion.  If the customer wants to use a modified OEE on a machine that includes the size of the crew operating it, they can now do so on that one machine, on classes of machines or on all machines.   Kaya: Wow. You were certainly busy with 8.5 with all these new features. Can you tell me what you’re most excited about for 9.0? Ward: I’m most looking forward to High Availability. The ability to have multiple servers in an active-active mode allows me to do more processing in ThingWorx and provide a level of reliability to my customers. (Look out for info on this exciting new functionality in the future!)   Ready to get started using the flexible KPIs yourself? Check out the ThingWorx Apps Customization Guide! While you’re at it, be sure to also check out the other new features in 8.5 listed above!   Reach out with any questions and stay connected! Kaya

 Image Source: https://www.thefire.org/resources/spotlight/     Designed a super cool mashup? Have an innovative IoT app? Are you really proud of how you solved an IoT challenge? Are you using ThingWorx for a unique use case?   If so, we want to hear from you! I’m looking for a few ThingWorx developers that are interested in sharing their work to be showcased on the Ask Kaya blog! (Don’t worry—we can hide your confidential info and only share what you allow us to.) We’d love to highlight what our developers are doing with ThingWorx out in the real world. If you’re interested, comment below or message me directly!   As always, stay connected.  

    We’re back with a ThingWorx 8.5 highlight! Today, we’ll cover brand-new functionality within ThingWorx Flow—the Azure Connector!   Imagine you’re on the regal shores of ThingWorx, trying to reach the plentiful utopia of Azure IoT services and capabilities. How do you get there? Through the new Azure Connector for ThingWorx Flow!   The Azure Connector for ThingWorx Flow is an OOTB connector that enables you to leverage the power and breadth of Azure services directly in ThingWorx applications with ThingWorx Flow. If you have intermittent needs for high-scale processing, for example, the Azure connector can help optimize costs based on when you require a mighty powerful liege and where you only pay for the necessary processing capacity when it is important. Azure Functions are also useful when you want to leverage some special code that was written in a language like Python that you’d like to easily leverage, such as to pre-process information collected from a device.   With the Azure connector, you’re able to: Support execution of logic apps to access a large number of OOTB systems connectors and customer investments in apps. Enable execution of Azure functions wherever elastic scale is needed to cost-effectively support use cases that have intermittent high-scale needs, such as executing an analysis of device sensors leading up to and following a key alert or incident. Enable use of Azure Cognitive Services to easily leverage a rich set of capabilities from simple text to voice or voice to text to computer vision in end-to-end IoT use cases. A few examples include the ability to: Convert the alert text to speech to deliver to an operator to take urgent action. Convert a verbal description of an assembly problem to a textual description in an automatically generated problem report. Use computer vision for a quality check to automatically pass or fail a part based on a visual image and confidence level. Here are a few of the many different services you can leverage with the Azure Connector in ThingWorx Flow: Anomaly Detector Bing Search Computer Vision Custom Vision Execute Function Execute Logic App Face Recognition LUIS Prediction QnA Prediction Speaker Recognition Speech Service Text Analytics Check out this demo video to see an example in action. In the video, you’ll see us: Create an Azure Function app. Create a ThingWorx Flow that triggers from an alert on a ThingWorx thing. Within the flow, you’ll see us consume the alert information and send it to the Azure Function app, and the Azure function app will process and return a response. (view in My Videos)   While simple, this demo shows the ability to connect ThingWorx and Azure together for an incredibly flexible and powerful distributed IoT system.   Finally, if you’re looking for assistance on how to use the new connector, see our Help Center here.   Stay connected and go with the (ThingWorx) Flow! Kaya        

  After months of development, hours of user interviews and countless coffees, ThingWorx Solution Central is here!   I posted a few weeks ago introducing the new cloud solution management portal, but just as a reminder, ThingWorx Solution Central is a brand-new set of cloud services offered to help you more efficiently manage and deploy your solutions—ow ow!   ThingWorx Solution Central automatically identifies and packages up your dependencies so you can slash your time to deploy. Once you develop your solution in ThingWorx (using the Projects feature), ThingWorx Solution Central will then automatically package up all the artifacts and dependencies required for your solution to run, and then you can publish your “package” up to the cloud, where it will be ready to be deployed to your specified environment(s).     Ready to get started? Request access to ThingWorx Solution Central here and you’ll be on your way to easier solution deployments in no time.   And if you happen to run into any trouble, see the ThingWorx Solution Central Help Center.   Happy deploying!   Stay connected, Kaya

   Who’s ready for exciting new functionality like smoother integration with Azure, rapid deployment capabilities, flexible KPIs and so much more?   Good news! Yesterday, we released ThingWorx 8.5—equipped with features like a new Azure connector for ThingWorx Flow, new software content management (SCM) capabilities with the Azure IoT Hub Connector, streamlined deployments with Solution Central, flexible KPI calculations with our PTC manufacturing and service apps—just to name a few. Check out the 8.5 release notes to discover all the highlights and goodness of our latest release and hear our CTO of IoT, Joe Biron (who you may recognize from previous Ask Kaya posts) and one of our product experience specialists, Sebastian Bergner, highlight new functionality and share demos in this exciting webcast (please note that we've had a little snafu with the link and the recording should be available later this week).   Play around with our new features by downloading ThingWorx 8.5, and let the good times roll.   Let us know what you think in the comments below and be on the lookout for future Ask Kaya posts highlighting new 8.5 functionality.   Stay connected, Kaya

  Hi everyone,   Today I’m here with a very exciting guest—Janie! Janie recently joined PTC after spending the last two years at a global professional services firm where she held many roles including that of a lead ThingWorx developer. While Janie did do some font-end development work and UI creation, the bulk of her time was spent on the backend writing services that enabled the application’s functionality. In this role, she not only wrote code herself, she also played a large part in the in-platform architectural decisions, determining the best way to utilize the platform in order to satisfy complex business requirements.   Throughout her last two years, she worked on various IIoT projects in the manufacturing industry developing a real-time asset health monitoring and OEE/production tracking application to monitor key metrics like downtime and output. For each customer engagement an assessment of IoT platforms was often undertaken in order to assess strengths and weaknesses based off-of the business requirements of the customer and while she spent time looking into a variety of platforms, ThingWorx always came out on top.   That said, her experience with ThingWorx showed her how much and how quickly that technology can can change the way a manufacturing company operates. She decided that instead of doing implementations of the technology, she wanted to have an impact on the technology itself and have a hand in the direction it goes and the way it continues to change the businesses we know today. This desire is what led her to product management and the role she currently holds at PTC today.   I recently sat down with Janie to hear how it has been moving from a developer on the platform to a PM for it to learn about her past ThingWorx experiences and how those will influence the work she does at PTC.     Here’s how our convo went.   Kaya: In your previous role as an IoT developer at another company, what made you choose ThingWorx over other IoT solution platforms? Janie: We chose ThingWorx over other IoT platforms due to its strong ability to connect such a wide variety of machines using ThingWorx Industrial Connectivity via Kepware, its industry-leading standing in the market and the fact that it did not require its users to have extensive development knowledge given its low-code environment, which enabled non-developers to be successful.   Kaya: Why do you think ThingWorx saved you time over other development platforms/products? Janie: There were three key ways the platform helped to save me time. First, I didn’t have to write code from scratch. For example, when needing to manipulate arrays or parse through uploaded csv files, there were pieces of code readily available for me to do so without having to know how to do it by myself. Second, due to the widgets ThingWorx already had available, I didn’t have to spend time making custom front-end UIs or widgets. And, thirdly, I saved a ton of time during the connectivity phase because connectivity to devices was supported OOTB through Kepware’s extensive suite of drivers available including some of the key ones we utilized such as Allen-Bradley Control Logix, Modbus, Siemens, and user configurable drivers.   Kaya: Along the lines of saving time, how would your experience with the platform have differed had you leveraged one of our manufacturing apps like Production KPIs? Janie: As I talked about previously, having access to a pre-built solution would have evidently saved a ton of development time and accelerated time to value. It also would have reduced the complexity of our completed app, which would have made it more scalable. While I understand the Manufacturing apps are not 100% ready-to-go out of the box but rather configurable stepping stones into a larger and mole holistic solution, if we could have had Production KPI’s as our development starting point, we would have had a more sound and already proven way of tackling Production and OEE tracking and could have added even more value on top of that.   Kaya: What were some of your favorite aspects about the platform? Janie: The code-snippets to get started were a big favorite, as were the OOTB widgets that allowed for quick visualization of important data. The OOTB industrial connectivity with seamless integration to ThingWorx was huge—we were able to connect multiple devices and stream information in real-time with little difficulty, which enabled us to derive even more value from the platform and really focus on becoming a fully smart and connected operation. Finally, the drag-and-drop UI was simple and intuitive.   Kaya: What do you think the top misconception is about IoT? Janie: I would say repeatability. Scaling an IoT solution across an enterprise is not as simple as it is often represented. I know we’re releasing a new functionality to help users more easily deploy their solutions, so I’m excited about that.   Kaya: So, now that you work as PM for the platform, what were a few things you wish you knew as a developer working on ThingWorx? Janie: Seeing everything we’re working on for the platform now is very exciting; I wish I could have been more aware of what’s on the roadmap so I knew what was coming as I was developing on the platform.   Kaya: On a similar note, now that you are working on the ThingWorx PM team, what items are you hoping to drive/change based on your experience? Janie: First, I’d like to drive stronger interaction with our system integrators (SIs) and partners by providing them insights into our roadmaps and allowing for them to provide feedback in a more seamless way. Next, I’d like to improve upon our essential platform developer capabilities, such as CI/CD, debugging, versioning, testing, etc. That said, Solution Central and PTC’s commitment to and integration with Microsoft products are very exciting roadmap features for me.   Kaya: I completely agree. Those are some great points. As I’m sure you’re aware, but our readers might not be aware of, we are working within the platform itself and a new feature, Solution Central, to provide more of that basic functionality so that, in addition to building blocks, low-code and a drag-and-drop UI, we can continue to help you accelerate your time to value.   Readers, I hope you enjoyed hearing from Janie! We’re excited to have her on the ThingWorx team and we look forward to making ThingWorx even stronger.   Let me know what you think in the comments below.   Stay connected, Kaya

    Raise your hand if you’re ready for seamless, rapid deployment of your ThingWorx applications with visibility into your various environments! It’s time to say goodbye to error-prone deployments with manual dependency tracking and hello to Solution Central!   Releasing this fall as part of 8.5, Solution Central is a brand-new cloud service coming to the ThingWorx platform to enable you to efficiently manage your ThingWorx applications across the enterprise.   With Solution Central, you’ll no longer be caught chasing missing dependencies (like ThingShapes, Mashups, templates or library extensions). Solution Central automatically identifies and packages up the dependencies required for your application. No more manual dependency madness!   Whether you’re managing many apps deployed to a few environments or a single app deployed to hundreds of environments, Solution Central allows you to accelerate your deployment through an intuitive UI or powerful APIs for automation.   Here’s how it works: Begin by creating your application in Composer with a project. Let Solution Central automatically package up all the artifacts and dependencies required for your application. Allow Solution Central to publish your solution package to the cloud. Deploy your application to your various environments (local servers, data centers, cloud systems) directly from Solution Central. It’s like your company has its own private app store. Here’s a sneak peek of the Solution Central UI! Keep an eye out for the release of ThingWorx 8.5 at the end of Sept 2019 and begin accelerating your app deployment! Check out the presentation and demo my fellow PM Chris Baldwin and I delivered at LiveWorx19—and be sure to attend LiveWorx20! To navigate to our session recording, search for “Introducing Solution Central: Your Gateway to Accelerated IIoT Value Across the Enterprise” here.   Sound interesting? Message me directly to discover how you can become part of the Solution Central Private Preview Program!   -Kaya  

  When it’s time to make pizza, most of us head to the fridge for our bag of dough; we don’t head for the flour and yeast to start from scratch. So, why would your ThingWorx apps be any different? Start with pre-built solutions like Asset Advisor to rapidly create health monitoring apps and dramatically reduce your development time.   We previously introduced Asset Advisor on Episode 04 of “ThingWorx on Air.” Today, we dive deeper into Asset Advisor with Greg Huet, Asset Advisor’s technical product manager (aka product owner). Listen to Ep. 06: Rapidly Build IIoT Apps for Service & Monitoring with Asset Advisor to hear Greg share our strategy of studying existing use cases and finding similarities that we can pre-build into solutions so that you don’t have to build them from scratch. Hear how you can use Asset Advisor out-of-the-box with tweaks for your company’s configurations or as an accelerated starting point where you can add as much customization as your use case desires—it’s like building a custom pizza, but starting with pre-made dough, rather than yeast and flour.   Greg also mentions the ThingWorx Application Development Guide. Be sure to check out my previous post, where Ward, one of the document creators, shares four of his top tips from the guide.   Now, sit back, relax and go enjoy some pizza while you listen to Episode 06.   As always, stay connected! Kaya

Thingworx Analytics is offered through the User interface called Analytics Builder with some pre-configured functionality. However, should you want to create your own jobs and mashups, all features from Analytics Builder and some more are available through the Thingworx Services.  Running most functionality requires that you provide some data to run the Analytics Services. This is where the datasetRef parameter is required.        Data uploaded through Analytics Builder Any dataset uploaded through builder will require have a datasetUri as shown in the image above and format will be parquet (all small letters) datasetUri can be obtained from the list of datasets in builder Passing data as an in-body Dataset If data isn't uploaded through Analytics Builder, data can be supplied as an Infotable in the data parameter of the datasetRef. Metadata will also need to be supplied if a new dataset is being created (create Job of the AnalyticsServer_DataThing) If this data is being supplied for a scoring job, as long as the column names match up to what the model is expecting, TWX Analytics will inference them appropriately. The filter parameter is for parquet datasets already uploaded into TWXA and will take an ANSI SQL statement format to add conditions to reduce number of rows. Exclusions is an single column infotable list of the columns you wish to remove from the job you are trying to submit Example: If you want Profiles to only run on 5 out of 10 columns, you would give a list of 5 columns that you don't want to include in this exclusions infotable. Data may also be supplied as a csv file in the file repo in some cases, in which case you would give the dataseturi parameter the location of the file on the TWX File repo (of the format thingworx://UseCaseFileRepo/tempdata.csv) and the format which would be csv

Race to the finish line of IoT app development with ThingWorx Edge!     Hi everyone,   Today’s post comes fully packed with an intro to our ThingWorx Edge strategy. Learn how to connect your machine data to ThingWorx, how our SDKs work, why you’d want to use them and how you can deploy agents.   To learn more about the Edge with ThingWorx, I spoke with Shravan. When Shravan’s not following Formula 1, learning about the latest trends in AI or playing cricket, he’s leading our development teams as the PM for the Edge. Check out what he had to say:   Kaya: How can I connect my machine data to ThingWorx through a protocol that the platform does not natively support?  Shravan: If you’re looking to connect your machine data to ThingWorx through a proprietary protocol and you require a 1:1 connection with the platform, we have two paths you can take. You can either: Utilize PTC’s Edge MicroServer (EMS) out-of-the-box solution. This is a stand-alone application that you can configure to send property updates, files, etc. to your instance of the ThingWorx Platform. It’s almost like a little mailman. Or, if you want to build connectivity into your own Edge devices, you can take advantage of PTC’s Edge Software Development Kits (SDKs). We offer three SDKs—C, .NET and Java—to enable you to build connectivity into your own custom application.   Kaya: And how can I connect my machine data to ThingWorx if my protocol is known? Shravan: Alternatively, if you’re a customer that communicates over a known protocol, then we’d recommend using our ThingWorx Industrial Connectivity product, also known as KEPServerEX or ThingWorx Kepware Edge.   For more background, I’ll go into a little more depth: KEPServerEX works in a Windows environment. It leverages OPC and IT-centric communication protocols (SNMP, ODBC and web services). It has more than 150+ drivers that help to establish stable and secure communication channels to devices, PLCs, Gateways, etc. ThingWorx Kepware Edge, launched during LiveWorx 2019, provides the most valuable features of KEPServerEX to be deployed in Linux-based gateways, starting with three key drivers: Modbus Ethernet, Allen-Bradley ControlLogix Ethernet and Siemens TCP/IP.   Kaya: Okay, great. Let’s cover SDKs first. In one sentence, can you explain how our SDKs work?   Shravan: The SDKs provide services for establishing a secure WebSocket connection (AlwaysON) to the ThingWorx Platform so that you can perform functions such as property updates, file transfers, tunneling, software content management (SCM), etc.   Kaya: At a high level, why do SDKs leverage AlwaysON? Shravan: Typically, transferring data to a server in IoT would require leveraging either REST web services, which has high connection overhead, works over HTTP or using MQTT, which requires a server and additional open ports.   So, an ideal connection should have three key features as a minimum: Stays continuously on. Is always ready to receive data and execute commands. Should also use existing open ports on firewall.   ThingWorx Edge SDKs provide this ideal connection though “Always On” protocol, which is based on WebSockets.   Kaya: What are the top three things a developer can do with the SDKs?  Shravan: Here are my top three. Thing property updates: Events can subscribe to changes in property values and in aspects of properties. File transfer: Browse remote directories and files on an instance of ThingWorx platform and enable bidirectional file transfer between an edge device and an instance of the platform. Tunneling: Allows users to establish secure, firewall-friendly application tunnels for applications that use TCP, such as VNC or SSH.   Kaya: How can you deploy SDK-based agents to devices? Shravan: You can deploy the agent in two main ways. One where the agent lives adjacent to the control and monitoring application of the machine and the other where the agent is directly integrated to the control and monitoring app of the machine.   Kaya: Anything else you want to mention?  Shravan: The Edge SDKs support a framework for adding additional functionality to the SDKs. This is known as the Edge Extension Framework. This allows additional functionality to be provided as installable services, which allows them to be extended in a manageable way while keeping the core SDK as compact and efficient as possible. Software Content Management (SCM) was the first commercially available Edge Extension.   - - -   This concludes the first installment of our series on Edge. Be on the lookout for deeper dives into KEPServerEX, SDKs, ThingWorx Kepware Edge and AlwaysOn.   Reach out if you have any questions.   Stay connected, Kaya                     P.S. For everyone who’s followed me for the past year, I’d just like to extend a huge thanks, as “Ask Kaya” has just turned one! It’s been a great first year and I’m excited for year two!

  Hi everyone,   In case you’re looking for more reasons to appreciate the power of Azure, today we’re answering 10 frequently asked questions around how and why to use Azure SQL with ThingWorx.   You likely already know that we support multiple persistence providers, like Azure SQL, InfluxDB, H2, MSSQL and PostgreSQL, for you to store and persist your ThingWorx data. Here’s an up-close-and-personal look into why we recommend Azure SQL.   1. What is Azure SQL?         Azure SQL is a relational database hosted in the Azure cloud and is a fully managed Platform as a Service (PaaS) Database Engine. Azure SQL Database engine is based on the Enterprise Edition of SQL Server. The Azure platform fully manages every Azure SQL Database with a high percentage of data availability and guarantees no data loss. Azure SQL Database comes with built-in high availability, disaster recovery, and upgrade for the database. Refer to Microsoft's Azure SQL Database - Platform as a Service documentation for more information on Azure SQL Database and its features.   2. What are the top 3 reasons to use Azure SQL with ThingWorx?   Ease of Use and Management: Azure SQL greatly reduces the need to manage database resources for ThingWorx. It helps to reduce your total cost of ownership for managing database resources for ThingWorx by managing virtual machines, operating system, database software, upgrades, high availability, and backups for you, so you can focus on building your IoT solution. It provides unmatched scale and high availability for compute and storage without sacrificing performance. With Azure SQL, you can scale your application on demand with up to 99.95% availability.   Hybrid Deployments: ThingWorx supports multiple persistence providers to store IoT data for different use cases. Please refer to the ThingWorx Model and Data Best Practices Guide to learn more. If you’re already using Microsoft SQL Server with ThingWorx on premise, then you can use Azure SQL for your cloud deployments of ThingWorx-based IIoT solutions in hybrid scenarios. This allows you to reduce development time—develop once and deploy anywhere through a common programming surface area across Azure SQL (on cloud) and SQL Server (on premise). You can leverage ThingWorx federation to run ThingWorx in different deployment topologies.   If needed, you can also accelerate your on-premise SQL Server migrations without changing the application code by leveraging Managed Instance. Use the Azure Hybrid Benefit Savings Calculator to calculate your TCO. Enjoy additional deployment flexibility with Single Database for SQL applications created in the cloud or Elastic Pool for multi-tenant applications.   Security and Compliance: Azure SQL Database meets the most stringent compliance standards with built-in auditing and information protection technology. With its availability in different regions, its best suited for Government cloud and sovereign cloud. Please see this link to check for the latest update on Azure product availability by region. You can also get multi-layered security provided by Microsoft across physical datacenters, infrastructure, and operations and will always have the latest SQL Server capabilities in the cloud, with no patching or upgrading. It also offers protection to your databases from malicious acts with fine-grained access controls, Always Encrypted technology, and advanced threat protection capabilities.   3. How do I configure ThingWorx for Azure SQL? From ThingWorx Foundation platform version 8.4 release onwards, ThingWorx provides you an option to choose Azure SQL as a persistence provider to store your value stream, stream, and data table data. This Help Center provides all the details and steps to help you set up Azure SQL with ThingWorx.    You can run ThingWorx with Azure SQL either by downloading the ThingWorx Azure SQL .WAR file or by running it as containerized ThingWorx Docker images by downloading ThingWorx Dockerfiles. For reference, see the below image to help you download ThingWorx 8.4 artifacts.   Here’s a video demonstrating how to install ThingWorx. (view in My Videos)   Here’s a second video that walks you through configuring ThingWorx with Azure SQL. (view in My Videos)   4. Which versions of Azure SQL does ThingWorx support? Consult the latest system requirements guide here to learn which versions of Azure SQL ThingWorx supports.   5. What database deployment options do I have? In Azure, you can have your SQL Server workloads running in a hosted infrastructure (IaaS) or running as a hosted service (PaaS). Within PaaS, you have multiple deployment options and service tiers within each deployment option, such as Single Database, Elastic Pool sets, and managed Instance. ThingWorx supports all the deployment options to setup Azure SQL as a persistence provider. You can refer to this link on Azure SQL Database versus SQL Server to help you choose an option that works best for your business needs.   6. Why would I want to use an PaaS database? Service tools and built-in features enable a more streamlined and automated means of controlling and operating your database. The need for constant manual control and tweaking of information, recovery tools, compliance and updates is now configured and built into Azure SQL for a more hands-off approach to your storage database. Here is a table to inform you on how Azure SQL PaaS helps.   7. Which features are new to Azure SQL 2019? Azure SQL now offers Always Encrypted data transfer through TLS and auto-failover for managed instance deployment to enable transparent and coordinated failover of multiple databases. Azure SQL also offers a data migration assistant, which detects compatibility issues that can impact functionality when upgrading your database. For more information on features and functionality, see Microsoft SQL documentation or Azure SQL’s latest release notes.   8. Is there any guidance available to help me migrate to Azure SQL? Yes! Microsoft’s Database Migration Service enables seamless migration to Managed Instance with downtime measured in minutes. The process is highly automated and risk-free while streamlining the transition of SQL Server and on-Microsoft database systems such as Oracle to Azure SQL Database. You can learn more about upgrading to Azure SQL here.   9. What purchasing models are available to me?   vCore based (recommended) - For customers that prioritize flexibility and control, this model offers scaling of compute, storage, and I/O resources independently to optimize price based on need. The customer chooses the hardware and service tier based on high-availability design, storage type, fault-isolation methods, and I/O ranges.   DTU based - Three distinct available tiers are differentiated based directly upon compute, memory, and I/O resources. This model bundles the measures together for customers who want pre-configured or simplified resource options. You can refer to more pricing and purchase options here.   10. What should I do if I need technical support? If you select Azure SQL as your persistence provider, then all support requests related to configuring Azure SQL can be logged through PTC Technical Support at https://support.ptc.com or by calling 1-800-477-6435.   You may also want to use the PTC Community to learn and collaborate with the growing PTC developer community. For all other requests related to database management, troubleshooting, monitoring, and administration, we encourage you to reach out to Microsoft directly.   Let me know what you think in the comments below.   Stay connected, Kaya

In the summer heat, keep your operators cool with Operator Advisor. Sit by the pool and relax to the tunes of Episode 05 of “ThingWorx on Air.”     High five! We’re back with Episode 05 of “ThingWorx on Air,” our developer-focused IoT podcast.   In today’s episode Jordan Chaisson, a super talented product manager, joins me to share even more about Operator Advisor (OA). You may remember that we introduced OA in our very first episode of “ThingWorx on Air”. Today, we dive deeper into its business value and reveal what’s on its roadmap. Plus, hear the coolest use case she’s seen yet with Operator Advisor!   OA is an accelerator application built on the ThingWorx platform that enables manufacturing operators through digital work instructions and a comprehensive user experience to receive the right data at the right time to minimize scrap and maximize efficiency.   Looking for more? Check out the Operator Advisor Guide or discover where to download Operator Advisor today.   Reach out with any questions, and, as always, stay connected!   -  Kaya

  Energy. Innovation. Passion. That’s how I would describe LiveWorx19 in three words.   From beginning to end, LiveWorx truly was a one-of-a-kind digital transformation event. Whether it was the top-notch demos, the delicious lunch from food trucks, or the unique integration of our products with our partners’ technologies, everywhere I turned, inspiration and excitement were booming.   Here are my top three highlights:   1. Delivering a breakout session Chris Baldwin and I shared exciting new functionality that we’re releasing in ThingWorx to simplify and accelerate deployment of applications across your enterprise. We introduced Solution Central, a new portal in the cloud for application management and deployment (more info to come in a future post, but in the meantime, reach out with any questions).   2. Assisting with Xtropolis, our Demo Floor Speaking directly with you and hearing how you’re using ThingWorx to transform industries like medical devices, beer brewing or furniture manufacturing was pretty impressive. It was also quite rewarding and inspiring to hear your clever questions about your unique IoT use cases while being surrounded by folks performing service on a giant John Deere tractor, attendees having virtual rides on a Polaris vehicle and a team of brewers using ThingWorx and Vuforia to brew some tasty Trillium beer.   3. Participating in Usability Tests Thank you to everyone who participated in the UX Lab. Hearing your direct feedback in usability tests on what you like and what you want to see changed or added to the product helps make it feel like you are right there with us designing ThingWorx—because, well, you are. We take the feedback you share at LiveWorx right back to the office and begin iterating. So, quick shoutout to everyone who participated—thanks for your feedback.     If you weren’t able to attend LiveWorx, check out our CEO, Jim Heppelmann, deliver the opening keynote above and hear him discuss how PTC is interweaving AR, IoT, generative design, PLM and AI to create a digital thread that transforms industrial enterprises across the globe.     After hearing about our overall strategy, you’re looking for more details on our product roadmap, watch the above roadmap session delivered by our EVP of Products, Kathleen Mitford.   One of the most rewarding parts of the show for me was meeting some of you—ThingWorx developers and Ask Kaya readers—in person!   Stay connected, Kaya   P.S. If you want to hear what others thought of LiveWorx, check out what Forbes, Automation World or Diginomica had to say.   P.P.S. If you had as much fun as I did or you’re looking to attend for the first time, tickets for LiveWorx 2020 are already available—check them out here!

  DevOps. It’s not just a buzzword. It’s a true development methodology that can make all the difference in your application quality and release time. Today, I’ll walk you through how you can continuously integrate and deploy your ThingWorx applications to achieve CI/CD objectives as part of a DevOps-focused culture. At the end, I’ll provide you a sneak peek of what you can expect in a future release (hint: we’re working on some awesome new CI/CD functionality). Overview of ThingWorx DevOps and Common Tools I’ll start by providing an overview of the DevOps cycle, and then I’ll provide more details around each step of the cycle. Before we can start, you’ll need to define your high-level architecture and functional requirements as part of the “Plan” phase.   Now, let’s build your ThingWorx app. Ready? Here we go!   Code As with any software platform, developers can start working in any number of areas of the IoT application—from edge, to visualization, rules authoring to data modelling. For the purpose of this article, we’ll start with the UI, but much of the same steps can be applied in any order. Also, we’ll just call out high level steps of development, but for more info on building out each aspect of your application, please visit developer.thingworx.com.   In ThingWorx Composer, build out your user interface with Mashups. Starting with UI can help you think about the types of data you want to collect from devices and systems and how you want to solve your unique requirements for the business. Starting at this point can also help you show live POCs and functional mockups to stakeholders. Once you’ve built some starter screens and a skeleton of app navigation, you can start adding in data through configuration in Composer by creating your Things, Templates, properties and services. [Optional] We offer 65 out-of-the-box widgets for the UI in the ThingWorx platform. There are times when you have specific visualization requirements for your application and the out-of-the-box widgets don’t quite satisfy them. We have a path for that, through our custom widget extensions. If you choose to develop your own widget extensions, you can do so through other IDEs like Eclipse or WebStorm. Custom development and extensions are not just for UI. We also allow you to define Thing entities and their custom services in Java. If you are developing extensions in this way, we’d recommend you do so using Eclipse to code and Gradle to build and drive tests. For instructions on how to create your own extension, see “Creating Customized ThingWorx Widgets” on page 42 of the ThingWorx Application Development Guide posted on Ask Kaya. With a good start on the data model, business logic and UI, some quick testing and validation is in order. You’ll probably also want to save all of this work also to share with colleagues or move to other integration environments. Capture all of your entity and code artifacts (Mashups, style definitions, Thing shapes, Thing templates, JavaScript, etc.) by using the “Export to Source Control” feature from ThingWorx Composer to write entities to the file system. You can use Git or other source systems to monitor the file system and push to the remote repository of your choice (e.g. GitHub, Bitbucket, etc.). Again, if you are developing extensions outside of Composer, you’ll want to source control those items, too, from Eclipse or the file system directly. Build [Optional] You can build an application package as an extension with all entities and code from Eclipse using the ThingWorx Eclipse plugin. When you build the project, it will create an extension zip file. Again, more info in the Application Development Guide. Make your life easy by using tools like Gradle or Maven. ThingWorx is very similar to other Java development systems, so Gradle and Maven track your dependencies and create a package with all of the referenced extensions you may be using and put them into one single zip file package. Once you have a package built, you can import it into test or integration environments. For added automation, create repeatable tasks like a job in Jenkins so that every time your code is changed in the source repository (e.g. Git), it triggers a job to increment the version, build the project and create the package deliverables. Consider also configuring the Jenkins jobs to push artifacts to a central repository like Artifactory. Test Once your code has been built, we can’t forget about testing! Automation is king for DevOps! For ThingWorx apps, you should still design a test strategy for your application, and then define and create your tests. These can run in your local developer environment, as well as be triggered via build tasks/changes in the source repository. Tools like JUnit for your entities and Java-backed services or Selenium for testing the Mashup UIs can be used. You can create separate jobs in Jenkins along with the build to run the integration and unit tests against an instance of ThingWorx that has the latest artifacts deployed into it. You can also do static code analysis using tools like PMD to find bugs, check style issues or identify inefficient code paths. To round out your app also with performance and load testing, JMeter is one tool that you can leverage. Release Releasing is the culmination of the team’s great work! If the test results pass and the builds are green, you are good to go, and it’s time to establish your release build. Make sure that you consider a versioning scheme for your application and its artifacts. Semantic versioning is a pattern that can be implemented for your ThingWorx application. Correct versioning of ThingWorx packages affects your upgrade plans and is a signal to your users on the intent and content of the release. Again, see the Application Development Guide. Once a release milestone is met, you can create a source branch in Git for that milestone, which will have all the changes encompassed in that release. Configure a Jenkins job to create builds from that milestone branch for maintenance purposes. Deploy + Operate + Monitor   If you’ve tested and released your application, it’s time for production and real users! Using the build and testing infrastructure you’ve set up earlier in the development process, you can also deploy your release builds to your target staging and production ThingWorx environments with Jenkins jobs, Artifactory and automated steps. Finally, as with anything, it is important to measure success and monitor performance via KPIs, trends and logs. You can also extract application insights and recommendations from the PTC System Monitor (PSM) tool, which uses Dynatrace; here is a guide on how to install and deploy PSM.  There are many different paths through the platform and options for developers to match your local team processes and tools—this was simply a quick overview. Congrats! You’re now equipped to build ThingWorx apps while leveraging software best practices and incorporating a DevOps culture!   What can I expect in a future release of ThingWorx? Coming in a near-term release of ThingWorx, we’ll make it easier for you to continuously integrate and deploy your ThingWorx applications. How? Through new functionality that bolsters our packaging concepts, new cloud services to assist in deployment to environments and an error-proof way to integrate applications with an automated dependency awareness.   Stay tuned for more info about this exciting new deployment and application management functionality targeted for Fall 2019!   Reach out with any questions and stay connected.   -Kaya