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    Hi, everyone!   In previous tech tips, I’ve introduced the ThingWorx 9.0 active-active clustering feature and provided architectural details and configurations. If you haven’t already, I recommend you check them out to learn more about how active-active clustering enables higher availability for ThingWorx: 9.0 Sneak Peek: Active-Active Clustering for ThingWorx 9.0 Sneak Peek: ThingWorx Architecture for Active-Active Clustering 9.0 Sneak Peek: Flexible Deployments of Active-Active Clustering for ThingWorx “ThingWorx on Air” Ep. 08: FAQs: ThingWorx Active-Active Clustering for Higher Availability   Today, I’ll provide more details around the load balancer in the active-active clustering architecture, some of its requirements, and a few configuration examples. Ready? Here we go! Here are the top four FAQs around the load balancer that will help you maximize your use of active-active clustering.   What do you mean by load balancing? Load balancing is the process of distributing network traffic across multiple servers. An algorithm employed by the load balancer or a proxy, determines how the traffic is distrusted. Round robin, fastest response, and least established connections are some of the most common methods of load balancing and provide different benefits, but all fundamentally ensure no single server bears too much demand. By spreading the traffic, load balancing improves application responsiveness. It also increases availability of applications and websites for users. Modern applications cannot run without load balancers. In general load balancers can run as hardware appliances or as software-defined. Hardware appliances often run proprietary software optimized to run on custom processors. As traffic increases, the vendor simply adds more load balancing appliances to handle the volume. Software defined load balancers usually run on less-expensive, standard Intel x86 hardware. Installing the software in cloud environments like Azure VMs or AWS EC2 eliminates the need for a physical appliance.   Following the seven-layer Open System Interconnection (OSI) model, load balancing occurs between layers four to seven (L4-Transport, L5-Session, L6-Presentation and L7-Application), whereas network firewalls are at levels one to three (L1-Physical Wiring, L2-Data Link and L3-Network). Load balancers have a various capabilities, which include: L4 — directs traffic based on data from network and transport layer protocols, such as IP address and TCP port. L7 — adds content switching to load balancing. This allows routing decisions based on attributes like HTTP header, uniform resource identifier, SSL session ID and HTML form data. GSLB — Global Server Load Balancing extends L4 and L7 capabilities to servers in different geographic locations. More enterprises are seeking to deploy cloud-native applications in data centers and public clouds. This is leading to significant changes in the capability of load balancers. What is a load balancer’s role in the ThingWorx Active-Active Clustering setup? As is true of any load balancer, the load balancer required in the ThingWorx Foundation active-active clustering architecture is responsible for distributing incoming traffic across the nodes within the cluster.   In the Active-Active Clustering architecture for ThingWorx, the load balancer distributes the traffic using a round-robin method. Please note that there are a several algorithms that provide load balancing techniques and this article is a good read for further understanding of it. A round-robin method rotates servers by directing traffic to the first available server and then moves that server to the bottom of the queue.   In ThingWorx clustering setup, while both WebSocket and HTTP incoming traffic are handled in a round-robin manner, they are routed differently by the load balancer.   HTTP traffic is directly distributed amongst the ThingWorx Foundation Servers within the cluster. Sticky sessions are used for the HTTP sessions—sticky via cookie, so individual users are tied directly to a single server node and see all of their changes instantaneously.   WebSocket traffic is distributed across the and is balanced via source IP to ensure each request from a device goes through the same connection server. From the ThingWorx Connection Server, the device traffic is distributed amongst the underlying ThingWorx Foundation Servers, not requiring another load balancer between the ThingWorx Connection Servers and ThingWorx Foundation Servers.   Please note that the WebSocket traffic load does not necessarily get distributed evenly nor do the incoming requests due to stickiness. For example: 2 users connect HTTP, one sends 100 requests and the other sends 2. Since they are sticky, it is not distributed evenly. 2 devices connect to a ThingWorx Connection Server. 1 is a gateway for 100 other devices, all requests fthe gateway go to the same connection server. The Connection Server does a round-robin to the underlying Foundation Servers so that the load would be better distributed across, but the load balancer is sticky to a ThingWorx Connection Server.     Which load balancer can I choose for setting ThingWorx in an Active-Active Cluster mode? ThingWorx active-active clustering is pretty much load balancer agnostic, meaning if the load balancer of your choosing that you might be using in your IT center meets the requirements, it can be utilized within the active-active clustering architecture. The load balancer is required to support the following features: Based on Layer-7 architecture Supports HTTP and WebSocket traffic Ability to support sticky sessions for  traffic and/or IP based stickiness. IP based means all traffic from a specific IP will be routed to the same server (this can be a problem with gateway type scenarios). Sticky sessions are based on a cookie, sessions are routed to same server based on cookie. Different users same IP could route to different machines. Health checking on server endpoints. (optional) It can manage SSL termination and SSL internal endpoints. Supports Path based routing. This is the ability to route to specific backends based on the URL or part of the URL. By default, all routes should go to the platform servers, but the following routes should go to the connection server: /Thingworx/WS /Thingworx/WSTunnelServer /Thingworx/WSTunnelClient /Thingworx/VWS All servers should be setup to only be part of load balancing based on their health configuration.  When configuring health check frequency, they should be run at a rate based on the tolerance for bad requests to be processed. Thingworx Foundation has a /health and /ready endpoint.   The /Thingworx/ready endpoint should be used for the load balancer.  It will return a 200 when the server is ready to receive traffic.  Connection Server checks health requests on a specific port and will return 200 when healthy. What are some of the compatible load balancers that I can use? While you can use any load balancer that satisfies the above request and meets your IT standards, below are some of the third-party load balancers that provide the features that are required of the active-active clustering architecture: HAProxy - HAProxy is a free, open source software that provides a high availability load balancer and proxy server for TCP and HTTP-based applications that spreads requests across multiple servers. It is very powerful and supports monitoring capabilities out of the box. PTC tests the clustering architecture using HA Proxy and provides a reference document for the same through the ThingWorx Foundation help center docs. Please note that it runs only on Linux environments. For a quick reference example of how to set up an HAProxy load balancer, see our Help Center here. NGINX - NGINX is an HTTP and reverse proxy server, a mail proxy server, and a generic TCP/UDP proxy serve. NGINX provides proxy capabilities as well as web server options. Some features like sticky sessions, advanced monitoring are not available in the opensource version and require you upgrade to NGINX Plus.  If you’re a Windows shop or already use NGINX Plus in your IT, then you may choose this load balancer offering.  However, please note that PTC doesn’t provide any official configuration steps of setting it up through our Help Center documentation. For a quick reference example of how to set up an NGNIX load balancer, see our Help Center here. AWS Application Load Balancer - Application Load Balancer (ALB) is best suited for load balancing of HTTP and HTTPS traffic and provides advanced request routing targeted at the underlying ThingWorx applications. Operating at the individual request level (Layer 7), Application Load Balancer routes traffic to targets within Amazon Virtual Private Cloud (Amazon VPC) based on the content of the request. If you’re running ThingWorx deployments on AWS, then you may choose to use AWS-offered managed load balancing services. F5: F5 Networks through its BIG-IP Local Traffic Manager solution provides advance load balancing techniques such as a full proxy where you can inspect, manage, and report on application traffic entering and exiting your network with additional features around SSL and performance optimization. Load balancers are another area where ThingWorx allows for flexibility and extensibility by enabling you to use the load balancer of your choosing that you’re most comfortable with or that best suits your needs (provided it meets the criteria above). You can also configure SSL or TLS for HAProxy when using ThingWorx HA clustering for end-to-end security. I hope this tech tip helped you develop a deeper understanding of how active-active clustering leverages load balancers to further increase your performance and thus availability and machine uptime, among many others.   If you’re not already on 9.0 and using active-active clustering, be sure to upgrade!   Stay connected, Kaya  
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In ThingWorx Analytics, you have the possibility to use an external model for scoring. In this written tutorial, I would like to provide an overview of how you can use a model developed in Python, using the scikit-learn library in ThingWorx Analytics. The provided attachment contains an archive with the following files: iris_data.csv: A dataset for pattern recognition that has a categorical goal. You can click here to read more about this dataset TestRFToPmml.ipynb: A Jupyter notebook file with the source code for the Python model as well as the steps to export it to PMML RF_Iris.pmml: The PMML file with the model that you can directly upload in Analytics without going through the steps of training the model in Python The tutorial assumes you already have some knowledge of ThingWorx and ThingWorx Analytics. Also, if you plan to run the Python code and train the model yourself, you need to have Jupyter notebook installed (I used the one from the Anaconda distribution). For demonstration purposes, I have created a very simple random forest model in Python. To convert the model to PMML, I have used the sklearn2pmml library. Because ThingWorx Analytics supports PMML format 4.3, you need to install sklearn2pmml version 0.56.2 (the highest version that supports PMML 4.3). To read more about this library, please click here Furthermore, to use your model with the older version of the sklearn2pmml, I have installed scikit-learn version 0.23.2.  You will find the commands to install the two libraries in the first two cells of the notebook.   Code Walkthrough The first step is to import the required libraries (please note that pandas library is also required to transform the .csv to a Dataframe object):   import pandas from sklearn.ensemble import RandomForestClassifier from sklearn2pmml import sklearn2pmml from sklearn.model_selection import GridSearchCV from sklearn2pmml.pipeline import PMMLPipeline   After importing the required libraries, we convert the iris_data.csv to a pandas dataframe and then create the features (X) as well as the goal (Y) vectors:   iris_df = pandas.read_csv("iris_data.csv") iris_X = iris_df[iris_df.columns.difference(["class"])] iris_y = iris_df["class"]   To best tune the random forest, we will use the GridSearchCSV and cross-validation. We want to test what parameters have the best validation metrics and for this, we will use a utility function that will print the results:   def print_results(results): print('BEST PARAMS: {}\n'.format(results.best_params_)) means = results.cv_results_['mean_test_score'] stds = results.cv_results_['std_test_score'] for mean, std, params in zip(means, stds, results.cv_results_['params']): print('{} (+/-{}) for {}'.format(round(mean, 3), round(std * 2, 3), params))   We create the random forest model and train it with different numbers of estimators and maximum depth. We will then call the previous function to compare the results for the different parameters:   rf = RandomForestClassifier() parameters = { 'n_estimators': [5, 50, 250], 'max_depth': [2, 4, 8, 16, 32, None] } cv = GridSearchCV(rf, parameters, cv=5) cv.fit(iris_X, iris_y) print_results(cv)   To convert the model to a PMML file, we need to create a PMMLPipeline object, in which we pass the RandomForestClassifier with the tuning parameters we identified in the previous step (please note that in your case, the parameters can be different than in my example). You can check the sklearn2pmml  documentation  to see other examples for creating this PMMLPipeline object :   pipeline = PMMLPipeline([ ("classifier", RandomForestClassifier(max_depth=4,n_estimators=5)) ]) pipeline.fit(iris_X, iris_y)   Then we perform the export:   sklearn2pmml(pipeline, "RF_Iris.pmml", with_repr = True)   The model has now been exported as a PMML file in the same folder as the Jupyter Notebook file and we can upload it to ThingWorx Analytics.   Uploading and Exploring the PMML in Analytics To upload and use the model for scoring, there are two steps that you need to do: First, the PMML file needs to be uploaded to a ThingWorx File Repository Then, go to your Analytics Results thing (the name should be YourAnalyticsGateway_ResultsThing) and execute the service UploadModelFromRepository. Here you will need to specify the repository name and path for your PMML file, as well as a name for your model (and optionally a description)   If everything goes well, the result of the service will be an id. You can save this id to a separate file because you will use it later on. You can verify the status of this model and if it’s ready to use by executing the service GetDetails:   Assuming you want to use the PMML for scoring, but you were not the one to develop the model, maybe you don’t know what the expected inputs and the output of the model are. There are two services that can help you with this: QueryInputFields – to verify the fields expected as input parameters for a scoring job   QueryOutputFields – to verify the expected output of the model The resultType input parameter can be either MODELS or CLUSTERS, depending on the type of model,    Using the PMML for Scoring With all this information at hand, we are now ready to use this PMML for real-time scoring. In a Thing of your choice, define a service to test out the scoring for the PMML we have just uploaded. Create a new service with an infotable as the output (don’t add a datashape). The input data for scoring will be hardcoded in the service, but you can also add it as service input parameters and pass them via a Mashup or from another source. The script will be as follows:   // Values: INFOTABLE dataShape: "" let datasetRef = DataShapes["AnalyticsDatasetRef"].CreateValues(); // Values: INFOTABLE dataShape: "" let data = DataShapes["IrisData"].CreateValues(); data.AddRow({ sepal_length: 2.7, sepal_width: 3.1, petal_length: 2.1, petal_width: 0.4 }); datasetRef.AddRow({ data: data}); // predictiveScores: INFOTABLE dataShape: "" let result = Things["AnalyticsServer_PredictionThing"].RealtimeScore({ modelUri: "results:/models/" + "97471e07-137a-41bb-9f29-f43f107bf9ca", //replace with your own id datasetRef: datasetRef /* INFOTABLE */, });   Once you execute the service, the output should look like this (as we would have expected, according to the output fields in the PMML model):   As you have seen, it is easy to use a model built in Python in ThingWorx Analytics. Please note that you may use it only for scoring, and the model will not appear in Analytics Builder since you have created it on a different platform. If you have any questions about this brief written tutorial, let me know.
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Now that ThingWorx 9.3 is live, let’s take a closer look at some of our new features we released for Composer and Mashup Builder.   Referenced By Find where entities, code references, and project dependencies are used in your existing projects using the new “Referenced by” report feature. This feature is not automatically enabled because it is intended to be used during development, since it can call upon all of the entities in your project and can impact your load times in production. That being said, this is your friendly reminder to turn off this feature during production.     How to enable: Go to the relationship subsystem and tick the check box to enable during development.   How it works: The “Referenced By” feature finds any entity that is referenced in your ThingWorx environment based on the supplied search characteristics. You can run this “Referenced By” report in the Composer or via a ThingWorx service “GetWhereUsed”.  When you use the “Referenced By” feature on an entity, you can find all of the references in the system for that entity in Mashup bindings, service script references, thing property bindings, and more.     Grid Widget The new grid widget component, which was available for preview in ThingWorx 9.2, is now complete, so it’s time to get your grid on! We have improved styling and performance capabilities with this new widget, including greater support for inline editing, autocreation of columns based on infotables, and adding new footer areas. You can also configure the grid using the property editor in Mashup Builder, where previously we had plain text entry.   Style Migration The new Style Migration is a game changer. It allows you to retain the same look and feel of your Mashups as you upgrade from previous versions of ThingWorx to the newest web components and features available in 9.3. Improved from our previous migrator, this allows you to move to the latest platform version and capabilities without having to re-implement or redesign your applications and widgets.     How it works: When you upgrade to the latest version of ThingWorx, you will see a pop-up window appear if you have any legacy widgets or layouts in your Mashup. The window will have the option for you to apply one of three style themes to your Mashup: PTC Convergence Theme (the new ThingWorx Default theme), Legacy Styles Theme (the old ThingWorx theme, from version 8.0 and earlier), or Custom Theme (choose from custom themes you defined using the Theme Editor and Style Theme that will appear when custom theme is selected in the pop-up). Depending on how you already styled or would like to style your Mashups, select an option and click migrate. This migrator maintains previous coloring, spacing, and other design properties better than previous migrators. You, of course, have the option to not upgrade your Mashup, but we recommend that you migrate, especially where we have new widgets available to replace legacy versions. If there are any issues with your migration, you can always click “Undo” in the toolbar.   Things to Consider: This migration will work best with ThingWorx default styling, out of the box styling, and Mashups with widgets that we now have replacements for (these are marked legacy in the builder). Always make sure you review your Mashups to make sure bindings and properties remained. Note that custom CSS will not be migrated, and custom widgets developed outside the standard platform installation will remain the same on the new Mashup.   Other Bonus Features That’s not all we rolled out in ThingWorx 9.3. You will also see Composer enhancements for test execution on ThingTemplates and dynamic use of Master Mashups to allow for swapping out Masters at run time based on predefined conditions based on your users. Plus, we now have truncation support for the breadcrumb component and tabs component, which utilizes an ellipsis pattern for long  text for a more user-friendly application.  With enhancements to our charts, you can now show/hide legends and format axis in new ways. We also support localization for our new web component widgets, .   How has your experience been building solutions with the latest updates to Composer and Mashup Builder? How can we continue to build upon these enhancements? Let us know what you think.   Stay connected, Rachel
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Background Getting a performance benchmark of your running application is an important thing to do when deploying and scaling up an application in production.  This not only helps focus in on performance issues quickly, but also allows for safely planning for scaling up and resource sizing based on real concrete data.   I recently created a tool and made a post about capturing and analysing ThingWorx utilisation statistics to do such an analysis, as well as identifying potential performance bottlenecks. Although they are rich and precise, utilisation statistics fall short in a number of areas however - specifically being able to count and time specific service executions, as well as identifying and sorting based on the host executing the service.   Tomcat Access Log Analysis As ThingWorx is a Tomcat web application, Tomcat logs details of the requests being made to the application server and ThingWorx REST API.  The default settings include the host (IP address), date/timestamp, and request URI; which can be decoded to reveal relevant details like the calling entities and service executions.   Adding 3 key additional variables (%s %B %D) to the server.xml access log value also gives us the HTTP response code, service execution time, and bytes returned from Tomcat.  This is super useful as we can now determine exact time of service executions, and run statistics on their execution totals and execution time.     Once you have an access log file looking like the one above, you can attempt to load it into the access_log sheet in the analysis Excel workbook that I created.  You do this by click on the access_log table, then selecting "Data > Get Data > Data Source Settings".  You'll then be prompted with the following or similar pop-up allowing you to navigate to your access_log file to select and then load.     It should be noted that you'll have to Refresh the table after selecting the new access_log.txt file so that it is read in and populates the table.  You can do this by right-clicking on the table and saying Refresh, or using the Data > Refresh button.   This workbook relies on a number of formulas to slice and dice the timestamp, and during my attempts at importing I had significant issues with this due to some of the ways that Excel does things automatically without any manual options.  You really need to make sure that the timestamps are imported and converted correctly, or something in the workbook will likely not work as intended.  One thing that I had to do was to add 1 second to round up 00:00:00 for the first entries as this was being imported as a date without the time part, and then the next lines imported as a date/time.   Depending on how many lines your file is, you'll likely also have to "Fill Down" the formulas on the right side of the sheet which may be empty in the table after importing your new data set.  I had the best results by selecting the cells in question on the last row, then going down to the bottom corner, pushing and holding Shift, clicking on the last cell bottom right, and then selecting Home > Fill > Down to pull the formulas down from the top.   Once the data is loaded, you'll be able to start poking around.  The filters and sorting by the named columns is really helpful as you can start out by doing things like removing a particular host, sorting by longest execution times, selecting execution times greater than 4 seconds, or only showing activity aimed at a particular entity or service.     You really need to make sure that the imported data worked fine and looks perfect, as the next steps will totally break if not.  With the data loaded, you can now go to the Summary Data table and right-click on one of the tables and select Refresh.  This is reload the data in into the pivot table and re-run their calculations.   Once the refresh is complete, you should see the table summary like shown here; there are Day, Hour, and Minute expand/collapse buttons.  You should also see the Day, Hour, Month fields showing in the Field Definitions on the right.  This is the part that is painful -- if the dates are in the wrong format and Excel is unable to auto-detect everything in the same way, then you will not get these automatically created fields.     With the data reloaded, and Pivot Tables re-built, you should be able to go over to the Dashboard sheet to start looking at and analysing the graphs.  This one is showing the Top 10 services organised into hourly buckets with cumulated service execution times.     I'm not going to go into all of the workbooks features, but you can also individually select a set of key services that you want to have a look at together across both the execution count and execution time dimensions.     Next you can see the coordinated view of both total service execution time over number or service executions.  This is helpful for looking for patterns where a service may be executing longer but being triggered the same amount of times, compared to both being executed and taking more time.  I've created a YouTube video (see bottom) which goes through using all of the features as well as providing other pointers to using it.     Getting into a finer level of detail, this "bonus" sheet provides a Pivot Table and Pivot Chart which allows for exploring minimum, maximum and average execution time for a specific service.  Comparing this with the utilisation subsystem metrics taken during the same period now provide much deeper insight as we can pinpoint there the peaks were, how long they lasted, and where the slow executions were in relation to other services being executed at that time (example: identifying many queries/data processing occurring simultaneously).     Without further ado, you can download and play with my ThingWorx Tomcat Access Log Analysis Excel Workbook, and check out the recorded demonstration and explanation for more details on loading and analysis use. [YouTube] ThingWorx Tomcat Access Logs - Service Performance Analysis
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Distributed Timer and Scheduler Execution in a ThingWorx High Availability (HA) Cluster Written by Desheng Xu and edited by Mike Jasperson    Overview Starting with the 9.0 release, ThingWorx supports an “active-active” high availability (or HA) configuration, with multiple nodes providing redundancy in the event of hardware failures as well as horizontal scalability for workloads that can be distributed across the cluster.   In this architecture, one of the ThingWorx nodes is elected as the “singleton” (or lead) node of the cluster.  This node is responsible for managing the execution of all events triggered by timers or schedulers – they are not distributed across the cluster.   This design has proved challenging for some implementations as it presents a potential for a ThingWorx application to generate imbalanced workload if complex timers and schedulers are needed.   However, your ThingWorx applications can overcome this limitation, and still use timers and schedulers to trigger workloads that will distribute across the cluster.  This article will demonstrate both how to reproduce this imbalanced workload scenario, and the approach you can take to overcome it.   Demonstration Setup   For purposes of this demonstration, a two-node ThingWorx cluster was used, similar to the deployment diagram below:   Demonstrating Event Workload on the Singleton Node   Imagine this simple scenario: You have a list of vendors, and you need to process some logic for one of them at random every few seconds.   First, we will create a timer in ThingWorx to trigger an event – in this example, every 5 seconds.     Next, we will create a helper utility that has a task that will randomly select one of the vendors and process some logic for it – in this case, we will simply log the selected vendor in the ThingWorx ScriptLog.     Finally, we will subscribe to the timer event, and call the helper utility:     Now with that code in place, let's check where these services are being executed in the ScriptLog.     Look at the PlatformID column in the log… notice that that the Timer and the helper utility are always running on the same node – in this case Platform2, which is the current singleton node in the cluster.   As the complexity of your helper utility increases, you can imagine how workload will become unbalanced, with the singleton node handling the bulk of this timer-driven workload in addition to the other workloads being spread across the cluster.   This workload can be distributed across multiple cluster nodes, but a little more effort is needed to make it happen.   Timers that Distribute Tasks Across Multiple ThingWorx HA Cluster Nodes   This time let’s update our subscription code – using the PostJSON service from the ContentLoader entity to send the service requests to the cluster entry point instead of running them locally.       const headers = { "Content-Type": "application/json", "Accept": "application/json", "appKey": "INSERT-YOUR-APPKEY-HERE" }; const url = "https://testcluster.edc.ptc.io/Thingworx/Things/DistributeTaskDemo_HelperThing/services/TimerBackend_Service"; let result = Resources["ContentLoaderFunctions"].PostJSON({ proxyScheme: undefined /* STRING */, headers: headers /* JSON */, ignoreSSLErrors: undefined /* BOOLEAN */, useNTLM: undefined /* BOOLEAN */, workstation: undefined /* STRING */, useProxy: undefined /* BOOLEAN */, withCookies: undefined /* BOOLEAN */, proxyHost: undefined /* STRING */, url: url /* STRING */, content: {} /* JSON */, timeout: undefined /* NUMBER */, proxyPort: undefined /* INTEGER */, password: undefined /* STRING */, domain: undefined /* STRING */, username: undefined /* STRING */ });   Note that the URL used in this example - https://testcluster.edc.ptc.io/Thingworx - is the entry point of the ThingWorx cluster.  Replace this value to match with your cluster’s entry point if you want to duplicate this in your own cluster.   Now, let's check the result again.   Notice that the helper utility TimerBackend_Service is now running on both cluster nodes, Platform1 and Platform2.   Is this Magic?  No!  What is Happening Here?   The timer or scheduler itself is still being executed on the singleton node, but now instead of the triggering the helper utility locally, the PostJSON service call from the subscription is being routed back to the cluster entry point – the load balancer.  As a result, the request is routed (usually round-robin) to any available cluster nodes that are behind the load balancer and reporting as healthy.   Usually, the load balancer will be configured to have a cookie-based affinity - the load balancer will route the request to the node that has the same cookie value as the request.  Since this PostJSON service call is a RESTful call, any cookie value associated with the response will not be attached to the next request.  As a result, the cookie-based affinity will not impact the round-robin routing in this case.   Considerations to Use this Approach   Authentication: As illustrated in the demo, make sure to use an Application Key with an appropriate user assigned in the header. You could alternatively use username/password or a token to authenticate the request, but this could be less ideal from a security perspective.   App Deployment: The hostname in the URL must match the hostname of the cluster entry point.  As the URL of your implementation is now part of your code, if deploy this code from one ThingWorx instance to another, you would need to modify the hostname/port/protocol in the URL.   Consider creating a variable in the helper utility which holds the hostname/port/protocol value, making it easier to modify during deployment.   Firewall Rules: If your load balancer has firewall rules which limit the traffic to specific known IP addresses, you will need to determine which IP addresses will be used when a service is invoked from each of the ThingWorx cluster nodes, and then configure the load balancer to allow the traffic from each of these public IP address.   Alternatively, you could configure an internal IP address endpoint for the load balancer and use the local /etc/hosts name resolution of each ThingWorx node to point to the internal load balancer IP, or register this internal IP in an internal DNS as the cluster entry point.
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In a recent post, I gave an overview of the types of Building Blocks that are available with the ThingWorx Platform. As a reminder, Building Blocks are a collection of entities packaged together for modular software development. They are intended to be reusable, repeatable, and scalable, and they are the fastest way to either build your own solution or customize a pre-made PTC solution, like ThingWorx Digital Performance Management. There are four types of Building Blocks we will talk about for the development of IIoT applications and solutions on the ThingWorx platform: Connectors, Domain Models, Business Logic, and UI. In this post, we are going to do a deep dive on Connectors, which improve application performance and the transfer of data from disparate devices and systems.   What does a Connector look like in ThingWorx? All ThingWorx Building Blocks follow the same naming convention of CompanyName.BuildingBlockName, so any PTC-created Connectors will appear as PTC.Connector. Connectors in ThingWorx are external integrations that can come in through an industrial system, like an MES that could be connected to with ThingWorx Kepware, or business system, like a CRM that could be connected to via ThingWorx Flow or REST APIs. It could also be a connection to an external database. These are your data connections, so their structure will be somewhat dependent upon your database and assets.   What does a Connector look like in use in a PTC Solution? If we use the example of Digital Performance Management (DPM), one of the connectors we use is a Database Manager(ptc.DBConnection.Manager). It pulls information from the database that is being used from the implementation of DPM. If you think of Building Blocks like bricks, Connectors are the foundation. In this case, the Database Manager sits at the bottom layer of bricks to connect the asset data to the next layer of bricks (Domain Models, which I will cover in the next post) and allows you to pull any information you need.   How can you use a Connector in your solutions? As mentioned above, a Connector is the foundation building block for most solutions. It is what aggregates and transfers your solution-related data into the ThingWorx platform for use. The Connectors we currently have available on the ThingWorx platform will “talk” to your database and the other building blocks you use in your solutions, so for your own solutions, a Connector will be the entry point of your data into your solution.   How can you adapt a Connector for your own solutions? Because all PTC building blocks are built with JavaScript in the ThingWorx Mashup Builder, you can leverage existing Connectors on the ThingWorx platform and extend these same Connectors for your unique use case or build your own. You can view the code we used to create Connectors, so if they don’t pull data into your solution the way you want it to flow, you can override the Connector’s functions with your own capabilities.   The ThingWorx PM team is here to listen to your thoughts and feedback, so tell us: What questions do you have about Connectors and how they can improve your experience building solutions in the ThingWorx platform? Or, if you are waiting for the full deep dive into Building Blocks, keep an eye out for our next post on Domain Models, where we will cover the next “layer up” of the types of Building Blocks for use in ThingWorx.   Stay Connected, Rachel  
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The long-awaited manufacturing solution,  ThingWorx Digital Performance Management (DPM), has arrived! Announced at PTC’s  Manufacturing Live event, DPM provides key use cases around overall equipment effectiveness and real-time performance monitoring, while delivering insights with analytics and automated bottleneck identification tools. DPM gives customers clear insight into where and what to fix to drive efficiencies. Composed of modular building blocks with a foundation on the ThingWorx platform, DPM is easily configurable and customizable for closed-loop problem solving that drives productivity.   Let’s take a deeper look into what DPM is and how you can implement it to ensure your investment in the ThingWorx platform and digital transformation delivers business impact.   Monitor in real-time with Production Dashboard The Production Dashboard allows for automated or manual data entry of reason codes with a simple interface for limited disruption. Rather than providing front-line workers with the typical, difficult to understand, percentage based KPIs, Production Dashboard standardizes all losses, so operators can proactively resolve issues during production. You can configure this dashboard to collect granular data and allow opportunities for continuous improvement in process tracking.     Focus with Bottleneck Analysis Bottleneck analysis automatically identifies bottlenecks across the manufacturing process. Identifying bottlenecks can help you prioritize the highest-impact opportunities in the business process. This saves you having to manually identify and analyze potential issues and frees you up to work on other projects.   Prioritize with Time Loss Waterfall and Analyze with Loss Reason Pareto Monitor and analyze performance with data visualizations that help you pinpoint root causes and suggest improvements. Bring together your siloed data into one system and create a standard for how performance is measured and reported.   Improve with Action Tracker Action Tracker allows you to create continuous improvement actions tied to real production losses, to ensure your actions are having positive impact and return.  Create a digital workspace for teams to collaborate and learn from each other. Plus, you can track the improvements delivered through each individual action, so you can drill down and create transparency of work being done.   Confirm value delivered with Scorecard (Available in Later Versions) With the Scorecard feature, you can leverage a standard scorecard for enterprise wide KPIs to summarize factory health and compare similar factory operations. Use the scorecard to create trending and reporting that can be filtered based on the audience you are presenting data to. The scorecard gives you a consistent view that measures performance across the network and drives visibility and accountability across your business.   How do you plan to leverage DPM or the building blocks that make it up? We’d love to hear your thoughts on the first manufacturing solution from PTC.   Stay connected, Rachel   
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To simplify the development of IIoT applications and solutions on the ThingWorx platform, we introduce the concept of Building Blocks. The intent of Building Blocks is to ease the creation of your own solutions and customization of PTC’s solutions. These Building Blocks are domain specific business logic pre-made for reusability, which means you won’t need to build from scratch on ThingWorx and can accelerate your time to value. What do we mean by Building Blocks? Building Blocks are premade components that enable modular software development. They are reusable, replaceable packages of functionality that can be connected into an architecture framework. Building Blocks allow for quicker development and customization of solutions and applications. What are the different types of Building Blocks?   Connectors  Leverage the same connectors we use for PTC solutions for better overall application performance and seamless transfer of data from disparate devices and systems. Identify the devices and systems you would like to monitor and let the connector do the rest.   Domain Models  Incorporate behavior and data from your devices and systems into a conceptual model of the domain, which is prepackaged based on common use cases. You can also leverage our out of the box models to connect and build dependencies between domains.   Business Logic  Encode real-world business rules that determine how data can be created, stored, and changed. Create KPIs for your devices and systems with these rules and create alerts based on your unique parameters.   UI  Construct widgets to view or analyze key data points in a graphical user interface that you can customize and leverage to extend functionality. Created with manufacturing and service use cases in mind, UI are predesigned to make it easy to view and understand data.   Building Blocks build upon the ThingWorx platform and are the base of all of PTC’s current and future solutions. We will continue to discuss Building Blocks in future posts, but in the meantime: How will you leverage building blocks in your own solutions? Is there more you want to know?   Stay connected, Rachel  
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Back in 2018 an interesting capability was added to ThingWorx Foundation allowing you to enable statistical calculation of service and subscription execution.   We typically advise customers to approach this with caution for production systems as the additional overhead can be more than you want to add to the work the platform needs to handle.  This said, these statistics is used consciously can be extremely helpful during development, testing, and troubleshooting to help ascertain which entities are executing what services and where potential system bottlenecks or areas deserving performance optimization may lie.   Although I've used the Utilization Subsystem services for statistics for some time now, I've always found that the Composer table view is not sufficient for a deeper multi-dimensional analysis.  Today I took a first step in remedying this by getting these metrics into Excel and I wanted to share it with the community as it can be quite helpful in giving developers and architects another view into their ThingWorx applications and to take and compare benchmarks to ensure that the operational and scaling is happening as was expected when the application was put into production.   Utilization Subsystem Statistics You can enable and configure statistics calculation from the Subsystem Configuration tab.  The help documentation does a good job of explaining this so I won't mention it here.  Base guidance is not to use Persisted statistics, nor percentile calculation as both have significant performance impacts.  Aggregate statistics are less resource intensive as there are less counters so this would be more appropriate for a production environment.  Specific entity statistics require greater resources and this will scale up as well with the number of provisioned entities that you have (ie: 1,000 machines versus 10,000 machines) whereas aggregate statistics will remain more constant as you scale up your deployment and its load.   Utilization Subsystem Services In the subsystem Services tab, you can select "UtilizationSubsystem" from the filter drop down and you will see all of the relevant services to retrieve and reset the statistics.     Here I'm using the GetEntityStatistics service to get entity statistics for Services and Subscriptions.     Giving us something like this.      Using Postman to Save the Results to File I have used Postman to do the same REST API call and to format the results as HTML and to save these results to file so that they can be imported into Excel.   You need to call '/Thingworx/Subsystems/UtilizationSubsystem/Services/GetEntityStatistics' as a POST request with the Content-Type and Accept headers set to 'application/xml'.  Of course you also need to add an appropriately permissioned and secured AppKey to the headers in order to authenticate and get service execution authorization.     You'll note the Export Results > Save to a file menu over on the right to get your results saved.   Importing the HTML Results into Excel As simple as I would like to hope that getting a standard web formatted file into Excel should be, it didn't turn out to be as easy as I would have hoped and so I have to switch over to Windows to take advantage of Power Query.   From the Data ribbon, select Get Data > From File > From XML.  Then find and select the HTML file saved in the previous step.     Once it has loaded the file and done some preparation, you'll need to select the GetEntityStatistics table in the results on the left.  This should display all of the statistics in a preview table on the right.     Once the query completed, you should have a table showing your statistical data ready for... well... slicing and dicing.     The good news is that I did the hard part for you, so you can just download the attached spreadsheet and update the dataset with your fresh data to have everything parsed out into separate columns for you.     Now you can use the column filters to search for entity or service patterns or to select specific entities or attributes that you want to analyze.  You'll need to later clear the column filters to get your whole dataset back.     Updating the Spreadsheet with Fresh Data In order to make this data and its analysis more relevant, I went back and reset all of the statistics and took a new sample which was exactly one hour long.  This way I would get correct recent min/max execution time values as well as having a better understanding of just how many executions / triggers are happening in a one hour period for my benchmark.   Once I got the new HTML file save, I went into Excel's Data ribbon, selected a cell in the data table area, and clicked "Queries & Connections" which brought up the pane on the right which shows my original query.     Hovering over this query, I'm prompted with some stuff and I chose "Edit".     Then I clicked on the tiny little gear to the right of "Source" over on the pane on the right side.     Finally I was able to select the new file and Power Query opened it up for me.     I just needed to click "Close & Load" to save and refresh the query providing data to the table.     The only thing at this point is that I didn't have my nice little sparklines as my regional decimal character is not a period - so I selected the time columns and did a "Replace All" from '.' to ',' to turn them into numbers instead of text.     Et Voila!   There you have it - ready to sort, filter, search and review to help you better understand which parts of your application may be overly resource hungry, or even to spot faulty equipment that may be communicating and triggering workflows far more often than it should.   Specific vs General Depending on the type of analysis that you're doing you might find that the aggregate statistics are a better option.  As they'll be far, far less that the entity specific statistics they'll do a better job of giving you a holistic view of the types of things that are happening with your ThingWorx applications execution.   The entity specific data set that I'm showing here would be a better choice for troubleshooting and diagnostics to try to understand why certain customers/assets/machines are behaving strangely as we can specifically drill into these stats.  Keep in mind however that you should then compare these findings with the general baseline to see how this particular asset is behaving compared to the whole fleet.   As a size guideline - I did an entity specific version of this file for a customer with 1,000 machines and the Excel spreadsheet was 7Mb compared to the 30kb of the one attached here and just opening it and saving it was tough for Excel (likely due to all of my nested formulas).  Just keep this in mind as you use this feature as there is memory overhead meaning also garbage collection and associated CPU usage for such.
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Is your team operating an effective DevOps pipeline? DevOps is an important part of a mature, enterprise ready application, but the process isn’t simple.   This expert session will focus on how a full DevOps pipeline looks like and how PTC can help to build a seamless pipeline. Join us for our upcoming Expert Session to learn how to create a Docker image, integrate Azure with Docker and Git, and set up a seamless DevOps pipeline.   When? Thursday, September 30th 2021 | 11 AM EST Host: Tori FIrewind, Senior Engineer in PTC IOT Enterprise Deployment Center Registration link: https://www.ptc.com/en/resources/iiot/webcast/devops-pipeline-thingworx 
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  ThingWorx 9.2 is here! Deploy an entire solution and all its dependencies in one click with Solution Central’s one-click deploy, garner deeper analytic insight with our new waterfall charts, and manage and authenticate users more seamlessly with an Azure Active Directory integration. Discover these features and more in my 9.2 preview post here!   Review our release notes here and be sure to upgrade to 9.2!   Stay connected, Kaya
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We will host a live Expert Session: "5 Common Mistakes for Developing Scalable IoT Applications" on June 22nd, 11h00 EST.   Please find below the description of the expert session and the registration link.   Expert Session: 5 Common Mistakes for Developing Scalable IoT Applications Date and Time: June 22nd, 11h00 EST Duration: 1 hour Host: Tori Firewind, Mike Jasperson and Prachi Rath - Enterprise Deployment Center Registration Here: https://www.ptc.com/en/resources/iiot/webcast/5-common-dev-mistakes-for-scalable-iot-applications    Description: To build scalable applications, it’s necessary to identify the common mistakes made and ensure to avoid them at the early stages of development.   In this expert session, the PTC Enterprise Deployment Team will elaborate on why scalability is important and how one can avoid the common development pitfalls in IoT.    Existing Recorded sessions can be found on support portal using the keyword ‘Expert Sessions’. You can also suggest topics for upcoming sessions using this small form.   Here are some recorded sessions that might be of your interest. You can find recordings for the full library of webinars using the keyword ‘Expert Sessions’ in PTC support portal search Thingworx Active Active Clustering This session will cover the main aspects of the High Availability Clustering feature launched with the ThingWorx 9.0 release.   Recoding Link Upgrade to Thingworx 9 – How to Plan / Evaluate Impacts This session highlights the key points you should evaluate to properly plan your upgrade to Thingworx 9. Recording Link Top 5 items to check for Thingworx Performance Troubleshooting How to troubleshoot performance issues in a Thingworx Environment? Here we cover the top 5 investigation steps that will help you understand the source of your environment issues and allow better communication with PTC Technical Support     Recording Link
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  Hi, everyone!     Today, we’re launching an exciting new series called “PTC Community Spotlights.” Each post in the series explores a community member’s experience with ThingWorx—how they’re using it, what their favorite part about ThingWorx is, and any tips or tricks they may have to share with the PTC Community.   For the first installment, I spoke with @nmilleson of EAC. Check out our conversation below. Our first PTC Community Spotlight Speaker -- Nick Milleson of EAC Product Development Systems. @Kaya: Hi, @nmilleson, welcome! Thank you for taking the time to meet with me and volunteering to be our first ThingWorx Community spotlight!   @nmilleson: Of course, @Kaya. Happy to be here.   @Kaya: To start, can you tell me a little about yourself?   @nmilleson: Absolutely. My name is Nick Milleson.  I work as an IoT Solution Architect at EAC Product Development Systems (a PTC Partner). I’m located in Apple Valley, Minnesota, which is a suburb of the Twin Cities.   @Kaya: Nice! We always love hearing from our partners about the awesome work they do. As a PTC Partner, what industries do you typically work in?   @nmilleson: I consult for many, many different industries, including defense, transportation, medical devices, construction & aerospace.   @Kaya: Wow, so what PTC products are you most familiar with?   @nmilleson:  My schooling is in mechanical engineering, so I’ve also used Creo, Windchill, and MathCAD.  I have been working with the ThingWorx application and helping clients get the most out of ThingWorx for approximately 7 years.   @Kaya:  Seven years—that’s a while! Do you have any “ThingWorx” stories from over the years you can share with your community peers?   @nmilleson:  Sure thing. I think the coolest thing that I’ve done with ThingWorx was create a custom SVG infographic that featured animations, click events, zoom-ins, and heatmaps based on temperature deltas.  It was a custom widget and it worked really well in ThingWorx.  When I first started learning to use ThingWorx, I took apart an old RC car and hooked up an Arduino to the motors and steering.  I was then able to control it using a ThingWorx mashup.  Pretty fun! I’ll be sure to share a visual so people can check it out.   Nick's awesome custom SVG infographic featuring a ton of neat functionality like zoom-ins & heatmaps. @Kaya:  That’s awesome! Sounds like a fun time indeed. I saw that one of your first publications about ThingWorx for EAC was from 2015 and titled “Updating ThingWorx Using an Arduino Uno and a Serial Connection.”  The ThingWorx platform has certainly evolved since then.  What would you say is your favorite thing about ThingWorx today?   @nmilleson:  It sure has evolved. I would say my favorite thing is that it’s flexible enough to allow you the freedom to design all sorts of applications, while also providing you with all these great tools that make it easy to use as well.   @Kaya:  Thanks for that. I can see that you have been a member of the PTC Community for five years.  Thank you for providing such great contributions.  What do you enjoy most about the PTC Community?   @nmilleson:  I enjoy this Community because everyone seems very willing to help each other out, regardless of the complexity of the issue.  I stick mostly with the IoT Developers section, but I’ll meander into the Manufacturing Apps and ThingWorx Ideas once in a while as well.   @Kaya:  Love to hear it. Now, so the PTC Community can learn a little more about you, how do you spend your time when you aren’t playing with ThingWorx or engaging on the PTC Community?   @nmilleson: Great question. I have been a professional piano player for almost 20 years, so I’m often at a piano bar making music when I’m not doing software development with EAC.   @Kaya: Awesome. Well those are all the questions I have for today. Thank you for sharing your experience with ThingWorx! Truly appreciate it.   @nmilleson: Of course. Happy to be a part of it!   Kaya, here. We love hearing from community members like @nmilleson about how ThingWorx creates value for them amongst a variety of use cases. If you’re active on the community and interested in being featured on the PTC Community Spotlight series, send me a direct message and we’ll get the ball rollin’.   For now, we’ll let Nick “play us” out. Until next time, stay connected!   -Kaya
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  Sunshine, beach chairs & ThingWorx 9.2. What more could you need for your summer essentials?   Targeted for June 2021, our next release features intelligent one-click deploy with Solution Central*, new web components, and an enhanced IAM integration!   Let’s dive deeper into each.   Deploy an entire solution in one click with Solution Central’s intelligent one-click deploy. Good news: you followed a modular design pattern and broke up your application into smaller libraries and components. You can now enjoy easier maintenance and re-use of your app. Bad news: your app now has 10 different dependencies, with differing versions, each with a required order to import into ThingWorx. Now, try to share these modules with colleagues, or use them on environments where code may already exist. Not exactly a day at the beach, right? Fear not, one-click deploy has you covered. You click the button, we spin through and find the right dependencies, the right versions, the right order and load them all into the target platform upon a deploy request. Solution Central  one-click deploy means more sun and sand for you! Check out this post to learn more about what’s available in Solution Central 3.0! Intelligent One-Click Deploy with Solution Central Enhance your solutions with our latest web components! Imagine this: you’re a systems developer at a large parts manufacturer and your boss has asked for a detailed analysis of downtime over the last six months. Not to worry! ThingWorx 9.2 features a new waterfall chart that can be leveraged to understand dynamics in defect counts, loss reasons, time bottlenecks and other conditions. Be sure to try it out! And, while you’re at it, try out our new web components that are available now as preview: a toolbar to add key like filtering at the top of your screen or data intensive widgets (e.g., grids), a more flexible grid and a fancy new paradigm for interface developers. These three preview widgets are fully functional and tested in 9.2. Preview widgets will graduate in a future release when we add all planned functionality or address any perceived usability feedback.​ Don’t be afraid—it just means more good things are coming. Surf’s up, you can use these widgets safely now!​ New Waterfall Widget Coming in ThingWorx 9.2 Leverage new integrations with Azure Active Directory for more seamless user management. In prior releases we have offered integration to Azure Active Directory and SSO through Central Authorization Service type products or through custom authenticator extensions to ThingWorx.  With our new Azure AD integration, you can cut the custom extensions and additional software out of the picture.  We now accept direct SAML assertions from Azure AD directly to ThingWorx platform, which makes it that much easier to deploy your app in your organization’s SSO flow.  It’s as smooth as that frosty tropical drink when the sun goes down.   Like what you see? Want to try it out for yourself? ThingWorx 9.2 is targeted for June 2021, so be sure to keep a lookout on the horizon. Bump, set, spike!   Stay cool & connected, Kaya
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Hi everyone,   We’re back! And we’ve got exciting news about Solution Central! As tempted as I am to share the news myself, I thought it only fitting to have Janie Pascoe, Product Manager of Solution Central, share the news with you. You may remember Janie from this post on ThingWorx's OPCUA functionality or this one on what it’s like to transition from a ThingWorx developer to a ThingWorx product manager. Janie, welcome back! The floor is yours.   Janie, PM of Solution Central: Thank you so much Kaija. I wanted to bring your readers up to speed on some of the latest and greatest in Solution Central. If you haven’t logged in to the Solution Central portal in a while, I highly recommend you do so because you will immediately be notified of what’s new in the application as you can see here due to our newly added what’s new popup blurb!     But in the spirit of giving you even more detail, let me tell you a bit more about what is new in Solution Central 3.0. This release is full of more intelligence than ever before! You can now not only deploy the solutions themselves from Solution Central but deploy all of a solution’s dependencies with the single click of a button. So, instead of having to deploy each dependency separately and in a specific order, Solution Central is now smart enough to understand the dependencies and deploy them for you. We have also added enhancements to our Solution Detail panel to make it even more intuitive and easy find what you’re looking for. And when it comes to clean up activities, we have you covered. Solution Central can now forget an instance when it’s no longer needed—no more questioning whether an instance is in active use or not.   Kaya: Thanks, Janie. Exciting stuff! Readers, you can learn all about these new features and more in our Release Notes and Help Center documentation. Be sure to try out the latest functionality!   Any questions, comments, or ideas for enhancements to Solution Central can be sent directly to jpascoe@ptc.com.   Stay on the lookout for our next release!   As always, stay connected, Kaya
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Check our expert session recorded library! The recordings will also be published in our Customer events library, posted on each event. Stay tunned!   Your feedback is very important to us! After watching the recordings, please take 2 min to complete this survey   Thingworx Foundation Session Name Link Duration Thingworx Mashup 101 - Do's and Don'ts Recording link 00:33:41 Thingworx Active Active Clustering (High Availability Recording link 00:26:24 Upgrade to Thingworx 9 – How to Plan / Evaluate Impacts Recording link 00:27:02 Thingworx Flow Overview Recording link 00:43:40 Top 5 items to check for Thingworx Performance Troubleshooting Recording link 00:26:55 ThingWorx DEVOPS QuickStart Guide Recording link 00:45:05 ThingWorx Backup And Recovery Recording Link 00:20:14 Expert Session - Designing your Data Model in Thingworx Recording link 00:26:45 ThingWorx Installation Recording link 00:15:07 Expert Session - Introduction To Edge Connectivity Recording link 00:15:56 Expert Session - Basic Mashup Design in Thingworx Recording link 00:36:31 Expert Session - Extensions101 Recording Link 00:30:08 Expert Session – Developing your Data Model in Thingworx Recording link 00:39:19 Thingworx Scalability Recording link 00:09:18 Expert Sessions - ThingWorx Patch Upgrade Recording link 00:03:19   Thingworx Navigate Session Name Link Duration Understanding license requirements for Thingworx Navigate Recording link 00:32:40 Navigate SSL and Authentication Recording Link 00:34:30 Navigate 3D Viewer Recording Link 00:43:25 Component Based App Development Recording Link 00:24:07 Navigate 9.0 – What’s new Recording link 00:27:07 Overview of SSO Implementation for ThingWorx Navigate and Windchill with PingFederate Recording link 00:18:36 Identifying the right SSO mix for Navigate 1 6 Recording link 00:57:56 Navigate Configuration - PingFederate Automation Script Recording link 00:51:07 Expert Session - Navigate Configuration/Windchill Authentication Recording link 00:23:07 What’s new with Navigate 1.8 and the new Navigate 1.8 installer Recording link 01:05:26 Creating an I*E task for use in Navigate Recording link 00:05:36   Vuforia Expert Capture Session Name Link Duration VEC In a Nutshell Video Link 00:31:39
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We will host a live Expert Session: "Top 5 Thingworx environment monitoring best practices" on March 25th, 10h00 EST.   Please find below the description of the expert session and the registration link.   Expert Session: Top 5 Thingworx environment monitoring best practices Date and Time: March 25th, 10h00 EST Duration: 1 hour Host: Tori Firewind, Tim Atwood and Dave Bernbeck from Enterprise Deployment Center Registration Here: https://www.ptc.com/en/resources/iiot/webcast/top-5-thingworx-monitoring-best-practices    In this session, we will be reviewing the main monitoring practices to keep a heathy environment and discuss the main issues from the audience. Bring your questions!.   Existing Recorded sessions can be found on support portal using the keyword ‘Expert Sessions’. You can also suggest topics for upcoming sessions using this small form.   Here are some recorded sessions that might be of your interest. You can find recordings for the full library of webinars using the keyword ‘Expert Sessions’ in PTC support portal search   Thingworx Active Active Clustering This session will cover the main aspects of the High Availability Clustering feature launched with the ThingWorx 9.0 release.   Recoding Link Upgrade to Thingworx 9 – How to Plan / Evaluate Impacts This session highlights the key points you should evaluate to properly plan your upgrade to Thingworx 9. Recording Link Top 5 items to check for Thingworx Performance Troubleshooting How to troubleshoot performance issues in a Thingworx Environment? Here we cover the top 5 investigation steps that will help you understand the source of your environment issues and allow better communication with PTC Technical Support     Recording Link
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We will host a live Expert Session: "Top 5 Thingworx environment monitoring best practices" on March 25th, 10h00 EST.   Please find below the description of the expert session and the registration link.   Expert Session: Top 5 Thingworx environment monitoring best practices Date and Time: March 25th, 10h00 EST Duration: 1 hour Host: Tori Firewind, Tim Atwood and Dave Bernbeck from Enterprise Deployment Center - Enterprise Deployment Center Registration Here: https://www.ptc.com/en/resources/iiot/webcast/top-5-thingworx-monitoring-best-practices    In this session, we will be reviewing the main monitoring practices to keep a heathy environment and discuss the main issues from the audience. Bring your questions!.   Existing Recorded sessions can be found on support portal using the keyword ‘Expert Sessions’. You can also suggest topics for upcoming sessions using this small form.   Here are some recorded sessions that might be of your interest. You can find recordings for the full library of webinars using the keyword ‘Expert Sessions’ in PTC support portal search   Thingworx Active Active Clustering This session will cover the main aspects of the High Availability Clustering feature launched with the ThingWorx 9.0 release.   Recoding Link Upgrade to Thingworx 9 – How to Plan / Evaluate Impacts This session highlights the key points you should evaluate to properly plan your upgrade to Thingworx 9. Recording Link Top 5 items to check for Thingworx Performance Troubleshooting How to troubleshoot performance issues in a Thingworx Environment? Here we cover the top 5 investigation steps that will help you understand the source of your environment issues and allow better communication with PTC Technical Support     Recording Link
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We will host a live Expert Session: "Thingworx Mashup 101 - Do's and Don'ts" on February 24th, 13h30 EST.   Please find below the description of the expert session and the registration link.   Expert Session: Thingworx Mashup 101 - Do's and Don'ts Date and Time: February 24th, 13h30 EST Duration: 1 hour Host: Aanjan Ravi - Technical Product Manager Registration Here: https://www.ptc.com/en/events/thingworx-mashup-101   Description: This session covers the most common and useful tips about how to correctly use Mashup builder, Widgets and Layouts – and what to avoid -  to create applications with good principles of UI/UX and easier to maintain.   Existing Recorded sessions can be found on support portal using the keyword ‘Expert Sessions’. You can also suggest topics for upcoming sessions using this small form.   Here are some recorded sessions that might be of your interest. You can find recordings for the full library of webinars using the keyword ‘Expert Sessions’ in PTC support portal search Thingworx Active Active Clustering This session will cover the main aspects of the High Availability Clustering feature launched with the ThingWorx 9.0 release.   Recoding Link Upgrade to Thingworx 9 – How to Plan / Evaluate Impacts This session highlights the key points you should evaluate to properly plan your upgrade to Thingworx 9. Recording Link Top 5 items to check for Thingworx Performance Troubleshooting How to troubleshoot performance issues in a Thingworx Environment? Here we cover the top 5 investigation steps that will help you understand the source of your environment issues and allow better communication with PTC Technical Support     Recording Link
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Hello!   We will host a live Expert Session: "Understanding ThingWorx Navigate Licensing" on February 11th, 10h EST.   Please find below the description of the expert session and the registration link.   Expert Session: Understanding ThingWorx Navigate Licensing Date and Time: February 11th, 10h EST Duration: 1 hour Host: Christoph Braeuchle, Emily Larkin and Steve Scheib - ThingWorx Navigate PM team Registration Here: https://www.ptc.com/en/resources/plm/webcast/understanding-thingworx-navigate-licensing     Description: ThingWorx Navigate licensing opens many users a way to access PLM data and functionality at an attractive price tag when they don’t need to use the full power of Windchill functionality. This licensing and packaging have changed over the past 1.5 years and this is the perfect time to share an update on available license types and answer essential questions like... Which license types do my end-users really need? What capabilities are provided by each license type? What are the best ways to understand and control license usage in my company? Don’t miss this session if you want to understand how ThingWorx Navigate licensing works and which options are available.   Existing Recorded sessions can be found on support portal using the keyword ‘Expert Sessions’. You can also suggest topics for upcoming sessions using this small form.   Here are some recorded sessions that might be of your interest. You can find recordings for the full library of webinars using the keyword ‘Expert Sessions’ in PTC support portal search Navigate - SSL & Windchill Authentication This in Expert Session will take you through a step-by-step approach for configuring authentication between Windchill and Navigate with SSL.   Recoding Link Top 5 items to check for Thingworx Performance Troubleshooting How to troubleshoot performance issues in a Thingworx Environment? Here we cover the top 5 investigation steps that will help you understand the source of your environment issues and allow better communication with PTC Technical Support   Recording Link Thingworx 9.0 Component Based App Development Following the series of new capabilities released with Navigate 9.0, this session will focus in the details of Navigate Component Based app development and how to leverage this to your use cases Recording Link
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Hi All,   We will host a live Expert Session: "Thignworx Active Active Clustering" on January 21th 8h00 EST. Please find below the description of the expert session and the registration link.   Expert Session: Thignworx Active Active Clustering Date and Time: January 21th 8h00 EST Duration: 1 hour Host: Ayush Tiwari - IoT Product Manager Registration Here: https://www.ptc.com/en/customer-success/expert-sessions-for-thingworx-foundation-webcasts (scroll down, the session is in the bottom of the page)   Description: This session will cover the main aspects of the High Availability Clustering feature for High Availability configuration launched with the ThingWorx 9.0 release. Join us and bring your questions with you!    Existing Recorded sessions can be found on support portal using the keyword ‘Expert Sessions’. You can also suggest topics for upcoming sessions using this small form.   Here are some recorded sessions that might be of your interest. You can find recordings for the full library of webinars using the keyword ‘Expert Sessions’ in PTC support portal search Upgrade to Thingworx 9 – How to Plan / Evaluate Impacts This session highlights the key points you should evaluate to properly plan your upgrade to Thingworx 9   Recording Link Thingworx Flow Overview Flow is a powerful component of the ThingWorx platform.  This session will take the Flow discussion beyond basic applications and into more customized and complex solutions.​ This will focus on use cases, main features such as triggers, connector options, main enhancements for Thingworx 9.0 and a short demonstration   Recoding Link
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