IoT Tips

Official name: DataStax Enterprise, sometimes referred as Cassandra. Note: DBA skills required, free self-paced training can be found here Training | DataStax The extension package can further be obtained through Technical Support. Thingworx 6.0 introduces DSE as a backend database scaling to much greater byte count, ad Neo4j performance limitations hit at 50Gbs. Some of the main reasons to consider DSE are: 1. Elastic scalability -- Alows to easily add capacity online to accommodate more customers and more data when needed. 2. Always on architecture -- Contains no single point of failure (as with traditional master/slave RDBMS's and other NoSQL solutions) resulting in continious availability for business-critical applications that can't afford to go down. 3. Fast linear-scale performance -- Enables sub-second response times with linear scalability (double the throughput with two nodes, quadruple it with four, and so on) to deliver response time speeds. 4. Flexible data storage -- Easily accommodates the full range of data formats - structured, semi-structured and unstructured -- that run through today's modern applications. 5. Easy data distribution -- Read and write to any node with all changes being automatically synchronized across a cluster, giving maximum flexibility to distribute data by replicating across multiple datacenters, cloud, and even mixed cloud/on-premise environments. Note: Windows+DSE is currently not fully supported. Connecting Thingworx: Prerequisite: fully configured DSE database. 1. Obtain the dse_persistancePackage 2. Import as an extension in Composer. 3. In composer, create a new persistence provider. 4. Select the imported package as Persistence Provider Package. 5. In Configuration tab:      - For Cassandra Cluster Host, enter the IP address set in cassandra.yaml or localhost if hosted locally      - Enter new of existing Cassandra Keyspace name      - Enter Solr Cluster URL      - Other fields can be left at default (*) 6. Go to Services and execute TestConnectivity service to ensure True response. 7. When creating new Stream, Value Stream, or a Data Table, set Persistence Provider to the one created in previous steps. Currently all reads and writes are done through Thingworx and all Thingworx data is encoded in DSE.  Opcenter still allows to see connectes streams, datatables, valuestreams. *SimpleStrategy can be used for a single data center, or NetworkTopologyStrategy is recommended for most deployments, because it is much easier to expand to multiple data centers when required by future expansion. Is there a limit of data per node? 1 TB is a reasonable limit on how much data a single node can handle, but in reality, a node is not at all limited by the size of the data, only the rate of operations. A node might have only 80 GB of data on it, but if it's continuously hit with random reads and doesn't have a lot of RAM, it might not even be able to handle that number of requests at a reasonable rate. Similarly, a node might have 10 TB of data, but if it's rarely read from, or there is a small portion of data that is hot (so it could be effectively cached), it will do just fine. If the replication factor is above 1 and there is no reads at consistency level ALL, other replicas will be able to respond quickly to read requests, so there won't be a large difference in latency seen from a client perspective.

  Hello, IIoT Developers!   Today, I’m going to provide you an overview of a new SDK we’re offering for developers to build custom web content. It’s called our Visual SDK. We released 9.0 in June, so it’s time to start getting excited! In case you missed it, check out these other 9.0 posts on active-active clustering, Composer and Mashup Builder, and the 9.0 release overall.   In 8.4, we introduced a new visualization architecture and set of web components based on Polymer. We’ve continually updated and added new widgets and features with this architecture each release, including new Chart Components in 9.0. This SDK was previously available mostly as a style guidance, informing designers and developers what elements and behaviors were available in the new PTC web component-based widgets. You could use this SDK to style in CSS custom elements of the web components in a mashup-based application. You weren’t, in 8.4, really able to use this SDK yet to actually create your own Polymer web components and have them be as robust in the Mashup Builder in ThingWorx.   In 9.0, this SDK has been expanded so you not only have style and behavioral descriptions of PTC components, but you also have tutorials and utilities that let you create your own components and import them into the Mashup Builder. The possibilities are endless here for custom content, so let’s look at what’s inside.   The SDK guide has a quick outline of some pre-requisites you should know about as you enter custom web development with ThingWorx. Things like knowledge of Polymer 3, downloading common tools like NPM and Gulp CLI, Aurelia, etc. Much of this info is also included in markdown documents within the SDK files, but the SDK web content makes it easier to follow and search.   From there, the guide walks you through more setup of your SDK directories, NPM install of PTC components, and basics around dependencies, styling, and demo pages. Each PTC-developed web component is also available in the SDK pages as well with more information on what they offer and their basic designs. This is useful if you would like to reference the PTC components as imports into your own web component. This technique is very useful for re-use and upgrade safety when developing custom components on top of ThingWorx. Sample overview pages in the SDK for ptcs-chart The SDK also includes a getting started tutorial and a sample Polymer component and a widget called simple-el , which are helpful as you want to reference during development and familiarizing yourself with concepts. The component is functional and offers a theme dropdown so you can see how the theming engine and events work. Sample Polymer component included in the SDK called simple-elOnce you have created your web component, there is also a new utility called mub, which scans your component project and wraps it in a shell for the Mashup Builder. If you run the mub utility on your component, you’ll find it produces a zip file with the relevant design and runtime wrappers for the mashup environment already mapped to your component. You can also use it to define properties for your new component in the mashup environment, include custom code for defining the widgets at design and runtime behaviors, and to add icons, categories and other standard platform features. Running the mub utility on a web component project Once you have run the utility, you just import the artifact into a ThingWorx platform and it will be available for your application developers to use in their mashups as a widget. Again, how it appears in the design experience, what properties are exposed, how it responds to platform binding and theming events are all customizable in the SDK. Sample Polymer Component wrapped as a widget for use in a Mashup Once you get the hang of things with the sample code and understand the ins and outs, you can then use those same patterns to develop your own content! These are the same techniques that the PTC R&D team uses when they make each of the new widgets that you see in our product, like the 9.0 charts! Uber cool stuff!   Like what you see? Have a question? Drop us a line in the comments!   Stay connected! Kaya    

ThingWorx provides multiple ways to deliver your data to the server. You can choose from the C based EMS to your own C application that uses the C SDK as well as SDKs for many popular languages but what can you do if the device you want to collect data on is so small that it need a very lightweight data delivery method. Normally you would consider using the REST web service interface and writing your own custom client to post your data by there is an alternative, MQTT. MQTT is a lightweight protocol that can be used from an Arduino with an Ethernet Shield that can stream real time data directly to ThingWorx by installing the MQTT Marketplace Extension on your server. To learn more about how this kind of solution worked, I created this slide deck while building a hardware example: DeliveringArduinoDataToThingworx.pdf Hopefully, it can help others out who want to create this kind of solution as well.

  Hello, IIoT Developers!   9.0 is out—let’s dive right into what’s new with Composer and Mashup Builder. (If you haven’t already checked out what’s new in 9.0 with active-active clustering, be sure to check out this tech tip.) We have a lot of new functionality that we can’t wait for you to start using, so without further ado, let’s begin!   Mashup Builder   In 9.0, we continue to make great advancements to our Mashup Builder and visualization toolset. We’re all about productive developers building the coolest IIoT apps! Mashup in 9.0 with new Line Chart widgets!   Undo/Redo   Ever spent a good half hour arranging a layout, making some data bindings, adding some styles, and once you view the Mashup, you decide you aren’t quite happy with your last few tweaks? The panic sets in when you forget exactly what you changed, and you don’t want to lose all of your edits. What is a developer to do? In older versions of ThingWorx, you might cancel without saving your edits or you might try to surgically get back to a good state. Either way, you were not a happy developer.   ThingWorx 9.0 will make you happy again. All actions in the Mashup are now tracked by an undo/redo buffer. Buttons are now available in the toolbar to help you revert actions. An action history drop-down is also available if you want to undo or redo a few jumps at once. Sometimes, it’s the little things!   Undo and Redo actions now available in the Mashup Builder.   Mobile Settings   For a few releases now, we’ve been upgrading our visualization toolset and examining ways we can be better for desktop and mobile experiences. It starts with our latest layout engine/editor introduced in 8.4 and with new Polymer-based, responsiveness “designed-in” web components introduced in 8.4, 8.5, and 9.0. For the more adventurous folks out there, you can also use Custom CSS to do media queries and influence your layouts based on the viewport settings. There are also custom resolutions and screen orientations available in the Mashup Builder toolbar itself so you can view your content in design mode with each of those targets in mind.   In 9.0, we now have introduced a new Mobile Settings configuration editor on the Mashup. This allows you to define for mobile browsers your scaling and width as well as your height and zoom settings. There are even iOS-specific settings for shortcuts and the status bar.  Mobile Settings Editor and iPhone view of a 9.0 Mashup.   New Configure Bindings Dialog   The heart of any application is the data, and how it is leveraged in the UI. For Mashups, there many good ways to do that with our drag-and-drop functionality or our Bindings panel. But in 9.0, we have completely revamped the Configure Bindings Dialog. You’ll quickly notice when you open the new dialog that it has a more usable interface with more screen real estate to explore services, properties, sources and targets. There is now a good separation between the Widgets, Data and Function sources, which makes things easier to locate and build. You’ll also see, if you’ve made bindings already, the complete map of bindings for your context. New search enhancements and target bindings chip-based filters are also now added.   New Configure Bindings Dialog Another cool feature is that the bindings graph in the dialog will also show you any circular references you may have inadvertently created. If you can see in the diagram below, the red circle icon with a number 1 inside of it—this is almost always a bug, so we may as well tell you about it! New Circular references checking! New Web Components   If you look at almost any IIoT application, you’re almost sure to see a chart. IIoT decisions are always centered around looking at telemetry and KPIs at specific moments of time, events, history, and future projections. ThingWorx has new charts in 9.0 for Line, Bar, and Schedule. They look sharp, they are powerful, and are a true upgrade over the former ThingWorx charts.   Here are some highlights. All are based on D3 framework and follow the PTC Design System. The Line chart also supports sub types of Run, Step, Area, Streamgraph and Scatter plot. The Bar chart also supports a column-based view. The Schedule chart is a great way to visualize downtime events, production orders, machine states, or device alarms. All charts feature responsive layout, advanced performance and data sampling, tooltips, multiple series support, multiple orientations for legends and axis labels, and plenty of styling and data configurations. They also all have great zooming capability for larger data sets including horizontal and vertical pan, drag/lasso zoom, interval controls, range zoom and zoom slider controls. Line Charts with filters, zoom sliders, and markers   Bar Charts with zoom sliders, horizontal and vertical orientations, and configurable legends   Schedule Chart with drilldown and hover tooltips Other Coolness   The team was busy with these highlighted features, but there is so much more in 9.0! For Mashup, we also added: Improved tooltip and icon hover support for all web component-based widgets Accessibility improvements for keyboard navigation and focus New category filters for widget property configuration editors New data tools panel New context menu options New theming options for layout containers Composer For application development outside of the Mashup area, you’ll also notice some new changes in the Composer tool. One of our favorites is the new navigation panels. If you’ve been with ThingWorx for a few releases, you’ve seen many redesigns and updates to the Composer interface. We are constantly evaluating and testing this interface’s design with users to make it a highly productive and intuitive environment. You’ll now see much more horizontal real estate in the Composer because we’ve moved the top header bar into a new left-hand navigation. We’ve also improved the grid resizing in the entity and other list views in the interface to work better with larger result sets. New Composer Layout with updated left-hand navigation One more bonus feature to highlight! We now have quick copy buttons in common places in the interface where you might want to copy entity names or application keys. Just click and that text is in your clipboard. Very handy for searching or making bindings!   Quick copy buttons on entity names     As you can see, plenty of awesome new features and upgrades in the ThingWorx 9.0 application development tools. We also have a brand-new visual SDK available in the 9.0 release so that you can make your own widgets with Polymer and import them into the Mashup Builder. Stay tuned for another Ask Kaya tech tip soon on the SDK.   Like what you see? Have a question? Drop us a line in the comments!   Stay Connected! Kaya  

  It’s here! It’s happening! ThingWorx 9.0 released today!   Unleash the Power of Now and leverage exciting new features like: Improved performance and higher availability via active-active clustering Faster, more streamlined development with: New widgets like line, bar & schedule charts Undo & redo functionality in Mashup Builder (look out for an upcoming Ask Kaya tech tip) New Mashup mobile settings Simpler management of entities and applications: Improved auditing scale & usability Ability to group entities via Thing Groups Ability to deploy apps built prior to 8.5 with Solution Central And more—like: Confidence model training Delegated authorization for Flow [Navigate] Component-based app development for custom production use apps (upgrade-safe) And even more—the list goes on and on. Check out the full list of new functionality in the 9.0 release notes and discover our What’s New page.   Access 9.0 under “ThingWorx Foundation” on the PTC Downloads Page and unleash its power today! As you get started, check out the ThingWorx Help Center for guidance.   Enjoy 9.0 and let us know what you think below! Kaya

This is a slide deck I created while learning how to post data from an Arduino to ThingWorx using MQTT protocol.

A while back, when I was learning about the ThingWorx platform, I could not find any good description of how InfoTables worked so I reverse engineered everything I could about them from a javascript perspective and wrote a short paper that I think is still of use today so I posted a copy here. It discusses what role InfoTables have as a ThingWorx primitive for passing data to and from ThingWorx and some of the lesser known capabilities that the data structure itself has built in. Here is a link to it Getting to Know InfoTables.pdf .

  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      

  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

Time series prediction uses a model to predict future values based on previously observed values. Time series data differs somewhat from non-time series data in both the formatting of the data and the training of predictive models. This article will highlight several important considerations when dealing with time series data. Preparing Time Series Data: The data must contain exactly one field with Op Type “TEMPORAL” and one field with Op Type “ENTITY_ID”, which defines the identifier for an entity, such as a machine serial number. The ENTITY_ID field should remain the same as long as there are no missing timestamps and it is within the same asset but should be different for different assets or asset runs in order to accurately assign history during model training and scoring.     The TEMPORAL field is a numeric field indicating the order of the data rows for a specific entity . One should also ensure that data is formatted such that the timestamps are equally spaced (for example, one data point every minute) and that no gaps exist in the sequence of numbers.   If there are gaps in the time series data, it is recommended to restart the series after the gap as a new entity. Alternatively, if the gap is small enough (few data points), linear interpolation based on the gap endpoint values within the same entity is generally acceptable.   Model Creation in Time Series: When creating a timeseries model in Analytics Builder, you will be asked to specify a lookback size and lookahead parameter. The lookback size determines how many historical datapoints (including the current row) will be used in the model. The lookahead indicates how many time steps ahead to predict.  If the value of the goal variable is not known at time of scoring, unchecking Use Goal History will use the goal column during training but not its history during scoring.   Time Series models can also be created in Services using the Training Thing. The lookback size and lookahead parameter are specified in the CreateJob service. The virtualSensor field is used to indicate if the model should be trained to predict values for a field that will not be available during scoring. For example, one can train a time series model to predict Volume using evolving Temperature and Pressure, based on sensor data for these three variables over a period of time. However, the Volume sensor may be removed from further assets in order to reduce costs, and the predictive model can be used instead.   Two important considerations: ThingWorx Analytics will expand historical data in the time series into new columns. This process creates new features using the values of the previous time steps. Additionally, low order derivatives, together with average and standard deviation features are computed over small contiguous subgroups of the historical data.   The expansion process can make the dataset exceptionally wide, so time series training is generally significantly slower compared to training with no history on the same dataset. This gets exacerbated when lookback size = 0 (auto-windowing, a process where the system is trying to find the optimal lookback). If there are columns that are not changing or change infrequently (such as a device serial number or zip code of the device’s location), these should be marked as Static when importing the data. Any columns labeled Static will not be expanded to create new features. Care also needs to be taken to exclude any features that are known to not be relevant to the prediction. Using a large lookback can eliminate how many examples / entities the model has available to train. For example, if a lookback of 8 is used, then any entities that have less than 8 examples will not be used in training. For the same reason, scoring for time series produces less results than the number of rows provided as input: if 10 rows are provided and lookback is 6, then only 5 predictions will be produced.

ThingWorx 8.5 Sizing Guide Sizing is a very important part of the application design process, answering such questions as: how much hardware is required? What specifications does this hardware need to handle the expected load? And therefore, what is the overall cost of setting up and maintaining the ThingWorx environment? Properly sizing the environment before development begins ensures that there are no unexpected costs or limitations to application functionality later on down the road.   "Hardware sizing is driven by many factors - some more easily calculated than others", as stated in the new ThingWorx 8.5 Sizing Guide. "Measures like data streaming frequency (the data ingestion component) and HTTP request volume (the data visualization component) are easily calculated... However, sizing considerations for the data processing component of the application can depend largely on business use cases and application design." Enterprise-Ready applications have the capacity to handle all aspects of an IoT application, from data ingestion and processing to data visualization, as detailed in the friendly infographic above, which many will recognize from LiveWorx. Inside the ThingWorx 8.5 Sizing Guide,  there are formulas designed to help size the more analytical aspects of the application, as well as descriptions of other factors and how they (conceptually) play a role in sizing.    There are also two application design examples which step the reader through the calculations, the comparisons, and the selections of hardware for each use case. New in this version, these examples have been simulated in the real world to prove that the theory behind these calculations is sound, and to demonstrate the full process of designing, sizing, and testing an application.  One of the examples (shown here) sizes a Connected Product Solution, something which has many, many remote things in the field, each writing to the Platform at a slower rate, for consumption by a large number of general users, who don't access the same mashups many times nor refresh their view very often. The second example is much more complex, modeling an industrial use-case, where there are many different kinds of users each accessing the mashups many times, fewer things, and more variations in the types of properties each thing possesses. These examples are designed to help anyone with any use case step through the sizing of their application properly.   Please check out the new ThingWorx 8.5 Sizing Guide, especially because each version of ThingWorx is different and must be sized accordingly. Comments and questions about the guide are very welcome right here on this thread!

The RabbitMQ Management plugin provides a web-based interface into the inner workings of the messaging bus behind ThingWorx Flow. It is installed by the Flow installers but is an HTTP service by default and is a totally different web server than the NGINX used to front-end ThingWorx Flow. This will describe how to integrate it into the NGINX on your ThingWorx Flow server. This is necessitated by some recent browser behavior changes that make it very hard to get to the http port once you've used an https service on the same machine from the same browser.   First - let's find the user name and password for the RabbitMQ Management plugin. On a Linux server, the file /etc/rabbitmq/definitions.json will hold the name and password for the plugin's UI:         "users": [{                 "name": "flowuser",                 "password": "1780edc6b8628ace2ace72465cdc7b048c88",                 "tags": "administrator"         }],   On a Windows server, the definitions.json file can be found under [flow install location]\modules\RabbitMQ.   Of course, access to these directories should be limited.   Second - let's integrate the plugin into NGINX The best way to integrate the plugin into Flow is to let NGINX reverse proxy to the other http server running the UI for the plugin, which is exactly what happens for Thingworx itself. That way, only NGINX has to be configured for https and no other ports need to be opened to allow access to the plugin.   You need to find the file vhost-flow.conf on your system. On Linux, this will be /etc/nginx/conf.d/vhost-flow.conf. On Windows, it will be at C:\Program Files\nginx-[version]\conf\conf.d\vhost-flow.conf by default. Add the following fragment after the last location xxx {…} segment in the file:       # deal with the rabbitMQ admin tool     location ~* /rabbitmq/api/(.*?)/(.*) {         proxy_pass http://127.0.0.1:15672/api/$1/%2F/$2?$query_string;         proxy_buffering                    off;         proxy_set_header Host              $http_host;         proxy_set_header X-Real-IP         $remote_addr;         proxy_set_header X-Forwarded-For   $proxy_add_x_forwarded_for;         proxy_set_header X-Forwarded-Proto $scheme;     }       location /rabbitmq {         rewrite ^/rabbitmq$ /rabbitmq/ permanent;      }       location ~* /rabbitmq/(.*) {         rewrite ^/rabbitmq/(.*)$ /$1 break;         proxy_pass http://127.0.0.1:15672;         proxy_buffering                    off;         proxy_set_header Host              $http_host;         proxy_set_header X-Real-IP         $remote_addr;         proxy_set_header X-Forwarded-For   $proxy_add_x_forwarded_for;         proxy_set_header X-Forwarded-Proto $scheme;     }   This makes the request for /rabbitmq get pushed over to the web server at port 15672 on the Flow server.   Test the updated config file with (nginx may not exist in your normal path): nginx -t   Restart the NGINX service: Linux (one of these will work depending upon your Linux version): systemctl restart nginx service nginx restart Windows: Net stop ThingWorxOrchestrationNginx Net start ThingWorxOrchestrationNginx -or- use the Services app to restart the service   Thanks to https://groups.google.com/forum/#!topic/rabbitmq-users/l_IxtiXeZC8 for the needed config changes.   You can now use https://yourserver/rabbitmq to get to the login page for the management plugin. Login with the user and password from the definitions.json file on your system and you can now monitor the behavior of your RabbitMQ environment.

Background: In very rare situations, it is possible that the Firewall-Friendly Agent process may stop running. If the Agent is not running, no machine monitoring or communication with the Cloud Server is possible. Recommendation: WatchDog is a little known yet very helpful feature available with Firewall-Friendly Agents. This program lets you monitor whether an Agent is running; if it’s not running, WatchDog can restart that Agent if needed. If the Agent process fails, WatchDog can bring it back up! WatchDog can also be configured to watch other processes. You can configure WatchDog to run as a service (for Windows) or daemon (for Linux). You will register the Watchdog to run as a service.  The Watchdog configuration file will specify the process(es) to be monitored and what to do when one exits. The options are to attempt to restart the process or to restart the system. Note: Watchdog detects only if a watched process exits. It will not detect or report on processes that may be “hanging”. Need more information? For information about configuring and using WatchDog, see the Agent User’s Guide for your Agent: either Axeda® Platform Axeda® Gateway User’s Guide (PDF) or Axeda® Platform Axeda® Connector User’s Guide (PDF).

Having trouble remembering how to get into Flow? How about make /Flow the URL?   Since the Flow environment uses NGINX to front-end the various components that make up Flow, there is a very sophisticated set of rewrites and proxy_pass directives in the NGINX configuration. All you have to do is add another 'location' fragment to the vhost-flow.conf file that will push /Flow over to /Thingworx/Composer/apps/flow:       location /Flow {       rewrite ^/Flow$ $proxy_scheme://$server_host/Thingworx/Composer/apps/flow permanent;     }   On Linux, the file should be at /etc/nginx/conf.d/vhost-flow.conf   On Windows, the file should be at c:\Program Files\nginx-[version]\conf\conf.d\vhost-flow.conf   Test the updated config file with (nginx may not exist in your normal path): nginx -t   Restart the NGINX service: Linux (one of these will work depending upon your Linux version): systemctl restart nginx service nginx restart Windows: Net stop ThingWorxOrchestrationNginx Net start ThingWorxOrchestrationNginx -or- use the Services app to restart the service   From this point forward https://yourserver/Flow will take you to ThingWorx Flow's home page.

I'm getting up to speed on all the great new stuff in 8.5, and have found that since the JavaScript engine was upgraded to Rhino 1.7.11, there's some awesome new JavaScript ES6 functionality available. I have tested arrow functions, filter, map, and reduce. Compose does not look like it is supported.   If you're not familiar with this functionality, I highly recommend reading up on them. Filter, map, and reduce are incredibly useful for working with arrays. They can save you a lot of annoying logic.   Here's some resources that I've found helpful for learning: JavaScript Functional Programming - map, filter and reduce Arrow Functions: Fat and Concise Syntax in Javascript If you really want to dive into ES6, Wes Bos has incredible tutorial sessions that are worth every penny: Wes Bos: ES6 for Everyone!   Have you played around with ES6 functionality in ThingWorx 8.5 yet?

<p>We live in a connected world where we can (want!) to receive instant updates and notifications. ThingWorx leverages the power of Web 2.0 and its Always-On technology to deliver that, but our friendly SMS providers have also provided an easy and powerful way that can be used to deliver SMS notifications right to your phone. Email to Text!</p><div>Set up a 'notification' Thing using our MailServer Template, set up your outgoing e-mail server and you are now ready to invoke the 'SendMessage' service on a given event. All you need now is the email address of your SMS number, which you can find by following this link: <a href="http://sms411.net/how-to-send-email-to-a-phone/" target="_blank"><span style="font-size:8.5pt;line-height:115%;font-family:&quot;Arial&quot;,&quot;sans-serif&quot;">List of e-Mail to SMS  addresses</span></a></div><p class="MsoNormal"><o:p></o:p></p><div><p class="MsoNormal"><o:p></o:p></p></div><p></p>

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!

  The IoT Enterprise Deployment Center’s goal is to create and share knowledge around the best practices for architecting, designing, and deploying successful, enterprise-scale Thingworx IoT Solutions.    To accomplish this goal, the EDC team takes a “real world” approach, using simulated IoT assets and users to benchmark the capabilities of different Thingworx deployment configurations. First, each implementation is pushed to its limit in an effort to establish real-world baselines, metrics which can be used to help customers determine which architecture choices will work for their custom needs. Then, each implementation is pushed beyond its limits, providing useful insight into where and why things fail, and illuminating potential implementation changes which could push the boundaries further.   Through the simulations testing to come, the EDC will be publishing the resulting benchmarks for all to see! These benchmarks will include details on implementation goals and performance metrics for different stages of deployment. Additionally, best-practice articles which illustrate how to deploy the different architectural components (those referenced within the benchmarks) will also be posted, highlighting the optimal approach to integrating everything into the Thingworx platform.   Stay tuned to see more about just how versatile the ThingWorx Platform can be! We look forward to discussing these findings as they are published right here on the PTC Community. 

  The scenario: Your company has settled on Azure as a cloud platform and you are currently using Azure IoT Edge as your connectivity strategy. You need a quick way to build IoT applications with your Azure devices. You’re looking for industry-proven and time-saving features like Mashup visualization, built-in connectivity to enterprise systems (like SAP or Oracle) with ThingWorx Flow, secure and scalable file transfer to your Azure-connected devices and the ability to create augmented reality (AR) experiences with Vuforia Studio. All of these options are available to you thanks to the ThingWorx-Azure IoT Hub Connector; it’s like the ice cream truck driving by on a hot summer day.   (If you’re wondering why we selected Azure as our preferred infrastructure, check out my previous interview with Neal, a Worldwide ThingWorx Center of Excellence Principal Lead here at PTC.)   I sat down with Ankit, a ThingWorx Product Manager, this week to learn more about the ThingWorx-Azure IoT Hub Connector. When Ankit’s not learning new hobbies like how to surf, snowboard or bike, he’s supporting our Microsoft partnership by enhancing and implementing ThingWorx-Azure functionality. Here’s how our conversation went:   Kaya: What is the Azure IoT Hub? Ankit: The Azure IoT Hub acts as a central message router for bi-directional communication between the cloud (and your ThingWorx applications) and your connected devices. The Azure IoT Hub securely connects, monitors and manages billions of devices. It is an open and flexible cloud platform as a service that supports open-source SDKs and multiple protocols. With ThingWorx, we enable you to authenticate user access per device to ensure your IoT solutions remain secure.   Kaya: I understand your team has created the ThingWorx-Azure IoT Hub Connector. Can you explain what it is and what it does? Ankit: The Azure IoT Hub Connector is an extension that is imported into ThingWorx for a developer to connect the Azure IoT Hub to ThingWorx. This helps ThingWorx to leverage the security and scalability of Azure while retaining the ThingWorx domain expertise to provide fast time to value.   The Connector is built on the ThingWorx Connection Server core. What it essentially does is convert JSON objects from Azure IoT Hub into ThingWorx property types (and vice versa) so that the digital twin data of an Azure device can be native to ThingWorx.   Since the Connector is built on the ThingWorx Connection Server, it is horizontally scalable and leverages features such as health check, metrics (message count and size, property writes) and logging.   Kaya: What was the challenge developers were facing that led us to create the Azure IoT Hub Connector? Ankit: There was no easy way for a developer to use ThingWorx to represent an Azure IoT device. Users weren’t easily able to take advantage of ThingWorx services and functionality on their Azure IoT devices, which were inherently connected to the Azure IoT Hub. Similarly, ThingWorx users were not able to take advantage of Azure services in a “configure-not-code” fashion in ThingWorx.   Kaya: How does the Connector solve this problem to enable you to integrate the two platforms and device models for a better combined solution? Ankit: Once you have an Azure device represented as a “Thing” in ThingWorx, you can use all the features and capabilities of ThingWorx Composer, Mashup Builder, etc. to build applications using the data from that Azure device.   Kaya: That’s pretty great. Ankit: Thanks, agreed. In the next version of the Connector, we’ll integrate more closely with Azure, such that our developers can leverage Azure services as well via ThingWorx, instead of building those services from scratch on Azure all on their own. For example, developers will be able to send software content, like firmware updates, to an Azure device without writing any code on Azure. All of this can be done on ThingWorx using Azure components like Azure IoT Edge Runtime.   Kaya: Awesome. In the meantime, what are the top two or three things a developer can do with the Azure IoT Hub Connector today? Ankit: Today, developers can take advantage of ingress and egress processing as well as file transfer. I’ll explain what these mean. Ingress Processing: Azure IoT devices (i.e. devices that are running Azure SDKs) send messages to the Azure IoT Hub. These messages are typically values of device properties (e.g. temperature). The Azure IoT Hub Connector “listens” for these messages, translates them and passes them to the ThingWorx platform. Egress Processing: Egress messages are messages that arrive from ThingWorx and are pushed to the Azure IoT Hub; an example might be pushing property updates to an Azure IoT device. File Transfer: The Azure IoT Hub Connector supports transferring files between Azure IoT devices and an Azure storage container (i.e. Blob store). An Azure storage container is represented by a ‘FileRepository’ Thing within ThingWorx. This enables developers to transfer files from an Azure storage container to ThingWorx and vice versa.   Kaya: What are two exciting features planned for a future release of the Connector? Ankit: Two exciting features planned for July include software content management (or SCM) and compatibility with ThingWorx Asset Advisor. Software Content Management (SCM): In our next release, we plan to have support for SCM from ThingWorx to an Azure IoT Edge device (an Azure IoT device with IoT Edge Runtime) via Azure IoT Hub. SCM allows users to transfer a variety of content like configuration settings, operating system patches and software updates and/or patches to a software agent on your Azure devices. SCM also allows you to manage your remote assets and keep them patched, secure and up-to-date with the latest features without having to dispatch a technician. This helps to reduce cost and complexity of software distribution and installation. Compatibility with ThingWorx Asset Advisor: Also planned for our next release, you will be able to readily manage Azure IoT devices directly through Asset Advisor to see key device alerts and warnings. This makes it even easier for you to leverage Asset Advisor to rapidly enable remote monitoring of your Azure devices.   Kaya: Exciting stuff. For our readers not familiar with Asset Advisor, check out this episode of my “ThingWorx on Air” podcast to understand what Asset Advisor is and how it works. Okay, next question. Do you have an example of a customer using Azure IoT Hub? Ankit: Absolutely. Colfax, an industrial manufacturing company, is using Azure IoT Hub to improve the efficiency of its IoT efforts across the enterprise. You should check out our case study on Colfax if you haven’t seen it yet.   Kaya: Where should I as a developer go if I want to learn more about the Azure IoT Hub Connector or Azure in general? Ankit: Depending on what you’re looking for, I’d recommend you check out the Help Center for technical guidance or the ThingWorx Azure IoT Hub Connector Release Notes, v. 2.0.0 for release updates.   Kaya: Finally, where can I go to download the ThingWorx Azure IoT Hub? Ankit: You can download it from the PTC Marketplace. Enjoy! Readers, let me know what you think about the Azure IoT Hub Connector in the comments below and reach out with any questions. While we’re excited to deliver what we have planned, our release content may change. In the meantime, for updates, tips and tricks and relevant info, stay connected!

  You’ve seen him before. You’ve heard him before. Fans around the globe can’t get enough of him. He’s…   ...Joe Biron—our CTO of IoT!   Hear Joe share his thoughts on the future of the industrial IoT with ThingWorx in Episode 03 of our “ThingWorx on Air” podcast!   Any questions? Just Ask Kaya.   Stay connected!