IoT Tips

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

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.

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

Hi all, Here is the recording of the expert session hosted in September 3rd. For full-sized viewing, click on the YouTube link in the player controls Your feedback is very important to us! After watching the recording, please take 2 min to complete this survey  

Applicable Releases: ThingWorx Platform 8.0 to 8.5; ThingWorx Navigate 1.5.0 to 8.5.0   Description:   Definition and concepts of Single Sign On (SSO), terminologies, components and architecture, as well as configuration prerequisites and high level steps to configure using PingFederation with Windchill and Navigate and main troubleshooting techniques    

When predicting a Boolean goal such as Failure in the next hour or any other goal that has a yes or no answer, Thingworx Analytics(TWXA) models will output a 'risk' of the event occurring. TWXA will intelligently pick a threshold beyond which that risk warrants attention. 1. In Analytics Builder, click on the export button 2. This will export a PMML model and download it for you 3. Open up the PMML model, in the output section, you will find a condition that explains the threshold that was selected by TWX Analytics.   In this example case, TWXA chose 0.5 as the best Threshold.   Note: The export button will only be available in Builder for TWXA 8.4+.

Contents: Introduction Prerequisites Installing Java Installing PostgreSQL Running the Installer Post Installation Steps Troubleshooting tips   Introduction:   Starting with ThingWorx 8.4, PTC released a new way to install a fresh ThingWorx environment.  This installer takes care of all the permissions, database scripts, credential encryption, and tomcat options that previously needed to be done manually.  More information on the installer can be found in the ThingWorx Help Center   NOTE: This is different than the Docker installer we have available in earlier releases.   As of right now, the installation guide has very basic instructions for the installer.  The purpose of this post is to show you from start to finish what the process looks like.  For this example, I chose to deploy PostgreSQL 10 on the local system to keep things simple.   Prerequisites:   Download the latest Java 8 SE JDK RPM for RHEL Get your database ready: If you're accessing a remote PostgreSQL instance, make sure PSQL is installed and working on your ThingWorx Server Download the appropriate installer from support.ptc.com Ensure the RHEL user that will be executing the installer has SUDO privileges   NOTE: There are pieces of the manual installation guide that I had to reference in order to get JAVA and PostgreSQL properly configured.   Installing Java:   Per Page 83, I downloaded the latest Linux x64 RPM for Java 8 SE JDK (201) and followed steps 2-8 to configure Java. For step 5, I needed to use the -f parameter listed in the guide under NOTE Step 7 make sure you don't accidentally select OpenJDK if it was preinstalled   Installing PostgreSQL:   I'm following along with the Version 10 download instructions found on https://www.postgresql.org/download/linux/redhat/ NOTE: this needs root access, so run all the commands with SUDO Install the client packages Postgresql10 I will Install the optional server packages postgresql10-server since this is a local PostgreSQL instance Complete step 7 to enable automatic start.  We need to set the postgres password so our ThingWorx installer is able to create our thingworx user and the database.  This can be done with the following command: NOTE: Since this is the master user for your database, it is highly recommended to use a password that has a combination of case, numbers, letters, and symbols Sudo passwd postgres Although, this may be redundant, I also run the following command to update the password used in PostgreSQL : sudo -u postgres psql -c "ALTER ROLE postgres WITH password '<password from above>'" Navigate to /var/lib/pgsql/10/data and open pg_hba.conf for editing Review page 91 of the Installation guide to determine which setting best applies to your business needs In the same directory open postgresql.conf Scroll down to "listen_addresses" line and un-comment it.  This would  be the place to make changes if you expect remote connections to access the database.  If it is local, then the default of localhost is fine Restart PostgreSQL to apply these changes: Sudo service postgresql-10 restart   Running the Installer:   Everything should be in place now to run our installer.  Extract the ThingWorxFoundationPostgres-1.2.0-SNAPSHOT.run file to the ~ (home) directory Execute the .run file: NOTE: If it doesn't let you execute the file, it may not have extracted as an executable.  Run the below command to make it executable then try again: Chmod -x ThingWorxFoundationPostgres-1.2.0-SNAPSHOT.run Sudo ./ThingWorxFoundationPostgres-1.2.0-SNAPSHOT.run   At this point you'll be going through text to setup your installation settings.  I'll briefly list out the order you'll see them below: Terms and conditions and whether you agree Where you want ThingWorx deployed (/opt by default) NOTE: this folder will contain ThingworxStorage/ ThingworxPlatform/ tomcat/ etc… Installation Configuration user (twxfoundation by default).  This step creates a user in RHEL that will have ownership of Tomcat, various ThingWorx directory's, etc ThingWorx Administrator Password.  Used to login to ThingWorx Composer. WRITE THIS DOWN SOMEWHERE!  You cannot retrieve this password, and most likely will require you to do a fresh installation if you forget it Tomcat Port http (8080) Tomcat SSL port (8443) Use SSL For simplicity, I chose not to use it for this exercise PostgreSQL information Host Name : mine is local, so localhost Port (5432) Administrator Username (Administrator) : use postgres here, since that's the DB user password we updated above Admin password : use the postgres password ThingWorx Database login username (twadmin).  This user will be created in PostgreSQL and be tied to our ThingWorx database ThingWorx database login password: NOTE There's no place to re-enter your password, so make sure you write this down.   Unexpected issue:   For this particular install, I kept running into a failure saying "Warning: Failed to validate the PostgreSQL connection.  Check the information you entered".  I opened another putty connection and, as root, navigated to /var/lib/pgsql/10/data/log and opened the postgresql log to find the following:   2019-02-28 17:10:30.678 UTC [93377] LOG:  could not connect to Ident server at address "::1", port 113: Connection refused 2019-02-28 17:10:30.678 UTC [93377] FATAL:  Ident authentication failed for user "postgres" 2019-02-28 17:10:30.678 UTC [93377] DETAIL:  Connection matched pg_hba.conf line 84: "host    all             all             ::1/128                 ident"     The solution for me was to go into the pg_hba.conf and change the IPv6 local connections from ident to md5.  Again, make sure you are reading through the PostgreSQL documentation and adjusting these properties in a way that meets both your security and business needs.   Once the change was made, I restarted postgresql, and switched back over to my Putty instance that had the installer going.     A summary pops up for a few items, and then it asks if you're ready to continue NOTE: The progress bar goes to 100% pretty quickly, and doesn't appear to move.  Just let it sit for a few minutes while it finishes up Copy the Thingworx Device ID for future reference To check if ThingWorx is running, run 'sudo service Thingworx-Foundation status' in your command line If it is active (running) try to access it with a remote browser: More information around the command Firewalld can be found here  http://<thingworxurl>:<tomcatport>/Thingworx NOTE: If it just hangs, check your firewall to make sure the port is open for external communication   Post Installation Steps:   Licensing: Navigate to /opt/ThingWorxPostgres-1.2.0-SNAPSHOT/licensingconfigurator and run the twx-licensing-configurator.run as SUDO Choose whether or not you want PTC to store your credentials and download the license for you, or if you want to manually download the license yourself from http://support.ptc.com -> Manage Licenses (bottom right) For this example, I manually downloaded the license Move the license file over to the ThingWorx Server Since you're running the licensingconfigurator as SUDO, don't put this file into your user's home directory.  Instead, put it into /tmp NOTE: Change the downloaded filename to license_capability_response.bin.  Otherwise the file will not be recognized Then it will ask for your ThingWorx Administrator password This appears to be used for verification after the license is in place, and it sees if it can successfully log into your system Once it has completed, and assuming it says "Setup has finished configuration licensing for ThingWorx", open up a web browser and login as Administrator -> Monitor -> Subsystems -> Licensing Subsystem and verify that your licensing information looks correct on the system   Extensions: Extra security has been added as of 8.4 around importing Extensions.  More details can be found in the Help Center In short, adding extensions is disabled by default, and you need to add some lines into your /ThingworxPlatform/platform-settings.json under the "PlatformSettingsConfig" section. For example, here is what I added:    "PlatformSettingsConfig": {                 "BasicSettings": {                         "BackupStorage": "/opt/ThingWorxPostgres-1.2.0-SNAPSHOT/ThingworxBackupStorage",                         "DatabaseLogRetentionPolicy": 7,                         "EnableBackup": true,                         "EnableHA": false,                         "EnableSystemLogging": true,                         "HTTPRequestHeaderMaxLength": 2000,                         "HTTPRequestParameterMaxLength": 2000,                         "InternalAesCryptographicKeyLength": 128,                         "Storage": "/opt/ThingWorxPostgres-1.2.0-SNAPSHOT/ThingworxStorage"                 },                 "ExtensionPackageImportPolicy": {                        "importEnabled": true,                        "allowJarResources": true,                        "allowJavascriptResources": false,                        "allowCSSResources": false,                        "allowJSONResources": false,                        "allowWebAppResources": false,                        "allowEntities": true,                        "allowExtensibleEntities": false       }           }   Make sure you set the appropriate items above to true based on what your extensions require   Troubleshooting:   If things backfire, depending on where you are in the setup process, the following logs should be looked at for clues on the failure:   Installation: /tmp/bitrock_installer.logs I believe the installation directory (default /opt/ThingWorxPostgres-1.2.0-SNAPSHOT) will contain a log file if the installer fails /opt/ThingWorxPostgres-1.2.0-SNAPSHOT/ThingworxStorage/logs/ (need root access) /opt/ThingWorxPostgres-1.2.0-SNAPSHOT/tomcat/apache-tomcat-<version>/logs PostgreSQL (requires root): /var/lib/pgsql/10/data/log LicensingConfigurator : /opt/ThingWorxPostgres-1.2.0-SNAPSHOT/licensingconfigurator

I always find it difficult to remember which version of software is supported with which version of ThingWorx, so I created a table for my reference. I hope this is also helpful to other people.   　 Oracle JDK Tomcat Database Options Memo PostgreSQL Neo4J H2 Microsoft SQLServer SAP HANA DetaStax Enterprise Edition ThingWorx 6.5 1.8.0(64-bit) 8.0.23(64-bit) 9.4.4 embedded N/A N/A N/A N/A IE 10 ThingWorx 6.6 1.8.0(64-bit) 8.0.23(64-bit) 9.4.4 embedded N/A N/A N/A N/A 　 ThingWorx 7.0 1.8.0(64-bit) 8.0.23(64-bit) 9.4.? embedded N/A N/A N/A N/A 　 ThingWorx 7.1 1.8.0_92-b14(64-bit) 8.0.33(64-bit) 9.4.5 embedded N/A N/A N/A 4.6.3 　 ThingWorx 7.2 1.8.0_92-b14(64-bit) 8.0.33(64-bit) 9.4.5 embedded embedded N/A N/A 4.6.3 IE 11 and later ThingWorx 7.3 1.8.0_92-b14(64-bit) 8.0.38(64-bit) 9.4.5 embedded embedded N/A SPS 11, 12 4.6.3, 5 　 ThingWorx 7.4 1.8.0_92-b14(64-bit) 8.0.38(64-bit) 9.4.5 embedded embedded 2014 and later SPS 11, 12 4.6.3, 5 　 ThingWorx 8.0 1.8.0_92-b14(64-bit) 8.0.44(64-bit), 8.5.13(64-bit) 9.4.5 embedded embedded 2014 and later SPS 11, 12 4.6.3, 5 　 ThingWorx 8.1 1.8.0_92-b14(64-bit) 8.0.44(64-bit), 8.5.13(64-bit) 9.4.5 embedded embedded 2014 and later SPS 11, 12 4.6.3, 5 　 ThingWorx 8.2 1.8.0_92-b14(64-bit) 8.0.47(64-bit), 8.5.23(64-bit) 9.4.5 embedded embedded 2014 and later SPS 11, 12 4.6.3, 5 　 ThingWorx 8.3 　 　 　 　 　 　 　 　 　

Large files could cause slow response times. In some cases large queries might cause extensively large response files, e.g. calling a ThingWorx service that returns an extensively large result set as JSON file.   Those massive files have to be transferred over the network and require additional bandwidth - for each and every call. The more bandwidth is used, the more time is taken on the network, the more the impact on performance could be. Imagine transferring tens or hundreds of MB for service calls for each and every call - over and over again.   To reduce the bandwidth compression can be activated. Instead of transferring MBs per service call, the server only has to transfer a couple of KB per call (best case scenario). This needs to be configured on Tomcat level. There is some information availabe in the offical Tomcat documation at https://tomcat.apache.org/tomcat-8.5-doc/config/http.html Search for the "compression" attribute.   Gzip compression   Usually Tomcat is compressing content in gzip. To verify if a certain response is in fact compressed or not, the Development Tools or Fiddler can be used. The Response Headers usually mention the compression type if the content is compressed:     Left: no compression Right: compression on Tomcat level   Not so straight forward - network vs. compression time trade-off   There's however a pitfall with compression on Tomcat side. Each response will add additional strain on time and resources (like CPU) to compress on the server and decompress the content on the client. Especially for small files this might be an unnecessary overhead as the time and resources to compress might take longer than just transferring a couple of uncompressed KB.   In the end it's a trade-off between network speed and the speed of compressing, decompressing response files on server and client. With the compressionMinSize attribute a compromise size can be set to find the best balance between compression and bandwith.   This trade-off can be clearly seen (for small content) here:     While the Size of the content shrinks, the Time increases. For larger content files however the Time will slightly increase as well due to the compression overhead, whereas the Size can be potentially dropped by a massive factor - especially for text based files.   Above test has been performed on a local virtual machine which basically neglegts most of the network related traffic problems resulting in performance issues - therefore the overhead in Time are a couple of milliseconds for the compression / decompression.   The default for the compressionMinSize is 2048 byte.   High potential performance improvement   Looking at the Combined.js the content size can be reduced significantly from 4.3 MB to only 886 KB. For my simple Mashup showing a chart with Temperature and Humidity this also decreases total load time from 32 to 2 seconds - also decreasing the content size from 6.1 MB to 1.2 MB!     This decreases load time and size by a factor of 16x and 5x - the total time until finished rendering the page has been decreased by a factor of almost 22x! (for this particular use case)   Configuration   To configure compression, open Tomcat's server.xml   In the <Connector> definitions add the following:   compression="on" compressibleMimeType="text/html,text/xml,text/plain,text/css,text/javascript,application/javascript,application/json"     This will use the default compressionMinSize of 2048 bytes. In addition to the default Mime Types I've also added application/json to compress ThingWorx service call results.   This needs to be configured for all Connectors that users should access - e.g. for HTTP and HTTPS connectors. For testing purposes I have a HTTPS connector with compression while HTTP is running without it.   Conclusion   If possible, enable compression to speed up content download for the client.   However there are some scenarios where compression is actually not a good idea - e.g. when using a WAN Accelerator or other network components that usually bring their own content compression. This not only adds unnecessary overhead but is compressing twice which might lead to errors on client side when decompressing the content.   Especially dealing with large responses can help decreasing impact on performance. As compressing and decompressing adds some overhead, the min size limit can be experimented with to find the optimal compromise between a network and compression time trade-off.

There are many choices in life and ThingWorx offers some persistence provider options as well. As of ThingWorx release 8.2, five Database options are provided. 1 PostgreSQL  9.4.5 minimum 2 DataStax Enterprise Edition 4.6.3,5 3 SAP HANA  SPS 11, 12 4 Microsoft SQL Server 2014 and later 5 H2 (version info is not available, maybe because it's an embedded?) H2 is for small scale, mainly for testing purpose, PostgreSQL and Microsoft SQL Server are for middle scale and finally DataStax Enterprise Edition is for big scale. I don't have enough information about SAP HANA so would like to leave it untouched in my comment... I don't have a number as to how many customers are using which database but my gut feeling tells me that PostgreSQL is a popular option, especially cost-wise. PostgreSQL offers powerful tools, such as logging and utilities, to troubleshoot issues.   In this post I would like to cover some useful information you can retrieve by using pgstattuple and pgstatindex of contrib module. By default, PostgreSQL takes a good care of fragmentation and reindex by itself. But in some cases, there's a situation that you want to review status of the database to narrow down the cause of your troubleshooting issue. There are many ways to achieve it but contrib module is provided to review stats of tables and indexes. As explained in this article, it is recommended to keep the number of records in value_stream and stream less than 100,000. That means you'll insert and delete many records when running ThingWorx. What happens then? If you delete(/update) a record in a table, PostgreSQL keeps the previous record in a page but mark it as deleted(and inserts a new record when it's update operation) If the number of those logically deleted records increases, PostgreSQL needs to access many pages of the table to obtain records which meets the criteria user might experience slow performance because of this Those logically deleted records will be ultimately removed from pages when vacuum is run   If you have installed contrib module and enabled it, you can review stats of tables by command below; select * from pgstattuple('stream');                             //This returns the stats of stream table select * from pgstatindex('stream_id_time_index');    //This returns the stats of an index on stream table   pgstattuple returns information below (I modified the format to make it more readable in this post) and meaning of each items are explained in the document .   table_len tuple_count tuple_len tuple_percent dead_tuple_count dead_tuple_len dead_tuple_percent free_space free_percent  8192 1 33 0.4 3  97 1.18 8004 97.71   Before obtaining the stat, I Inserted 4 records and Deleted 3 records and therefore it shows that tuple_count (the active record is 1) and dead_tuple_count (the logically deleted records are 3) and dead_tuple_percent is 1.18. If dead_tuple_percent is high, that means the table is not vacuumed or many DML were executed after the last vacuum operation and this could be the cause of the slow ststem performance.   * IMPORTANT: pgstattuple, pgstatindex consumes resources so it's recommended to run them during the maintenance window.   Takaaki

This Best Practices document should offer some guidelines and tips & tricks on how to work with Timers and Schedulers in ThingWorx. After exploring the configuration and creation of Timers and Schedulers via the UI or JavaScript Services, this document will also highlight some of the most common performance issues and troubleshooting techniques.   Timers and Schedulers can be used to run jobs or fire events on a regular basis. Both are implemented as Thing Templates in ThingWorx. New Timer and Scheduler Things can be created based on these Templates to introduce time based actions. Timers can be used to fire events in a certain interval, defined in the Timer's Update Rate (default is 60000 milliseconds = 1 minute). Schedulers can be used to run jobs based on a cron pattern (such as once a day or once an hour). Schedulers will also allow for a more detailed time based setup, e.g. based on seconds, hours, days of week or days months etc. Events fired by both Timers and Schedulers can be subscribed to with Subscriptions which can be utilized to execute custom service scripts, e.g. to generate "fake" or random demo data to update Remote Things in a test environment. In general subscriptions and scripts can be used to e.g. run regular maintenance tasks or periodically required functions (e.g. for data aggregation) For more information about setting up Timers and Schedulers it's recommended to also have a look at the following content:   How to set up and configure Timers How to set up and configure Schedulers How to create and configure Timers and Schedulers via JavaScript Services Events and Subscriptions for Timers and Schedulers   Example   The following example will illustrate on how to create a Timer Thing updating a Remote Thing using random values. To avoid any conflicts with permissions and visibility, use the Administrator user to create Things.   Remote Thing   Create a new Thing based on the Remote Thing Template, called myRemoteThing. Add two properties, numberA and numberB - both Integers and marked as persistent. Save myRemoteThing. Timer Thing   Create a new Thing based on the Timer Template, called myTimerThing. In the Configuration, change the Update Rate to 5000, to fire the Event every 5 seconds. User Context to Administrator. This will run the related services with the Administrator's user visibility and permissions. Save myTimerThing. Subscriptions   To update the myRemoteThing properties when the Timer Event fires, there are two options: Configure a Subscription on myRemoteThing and listen to Timer Events on the myTimerThing. Configure a Subscription on myTimerThing and listen to Timer Events on itself as a source. In this example, let's go with the first option and Edit myRemoteThing. Create a new Subscription pointing to myTimerThing as a Source. Select the Timer Event Note that if no source is selected, the Timer Event is not availabe, as myRemoteThing is based on the Remote Thing Template and not the Timer Template Enable the Subscription. In the Script area use the following code to assign two random numbers to the Thing's custom properties: me.numberA = Math.floor(Math.random() * 100); me.numberB = Math.floor(Math.random() * 100); Save myRemoteThing. Validation   The Subscription will be enabled and active on saving it. Switch to the myRemoteThing Properties Refreshing the Values will show updates with random numbers between 0 and 99 every 5 seconds (Timer Update Rate).   Performance considerations   Timers and Schedulers are handled via the Event Processing Subsystem. Metrics that impact current performance can be seen in Monitoring > Subsystems > Event Processing Implementing Timers and Schedulers on a Thing Template level might flood the system with services executions originating from Subscriptions to Timer / Scheduler triggered Events. Subscribing to another Thing's Events will be handled via the Event Processing Subsystem. Subscribing to an Event on the same Thing will not be handled via the Event Processing Subsystem, but rather execute on the already open in memory Thing. If Timers and Schedulers are not necessarily needed, the Services can be triggered e.g. via Data Change Events, UI Interactions etc. Recursion can be a hidden performance contributer where a Subscription to a certain Event executes a service, triggering another Event with recursive dependencies. Ensure there are no circular dependencies and service calls across Entities. If possible, reads for each and every action from disk should be avoided. Performance can be increased by storing relevant information in memory and using Streams or Datatables or for persistence. If possible, call other Services from within the Subscription instead of handling all code within the Subscription itself. For full details, see also Timers and Schedulers - Best Practice   How to identify and troubleshoot technical issues   Check the Event Processing Subsystem for any spikes in queued Events (tasks submitted) while the total number of tasks completed is not or only slowly increasing. For a historical overview, search the ApplicationLog for "Thingworx System Metrics" to get system metrics since the server has been (re-) started. In the ApplicationLog the message "Subsystem EventProcessingSubsystem is started" indicates that the Subsystem is indeed started and available. Use custom loggers in Services to get more context around errors and execution in the ScriptLog Custom Loggers can be used to identify if Events have fired and Subscriptions are actually triggered Example: logger.debug("myThing: executing subscribed service") For issues with Service execution, see also CS268218 Infinite loops in Services could render the server unresponsive and might flood the system with various Events To change the timing for a Timer, restarting the Thing is not enough. The Timer must be disabled and enabled at the desired start time. Schedulers will allow for a much more flexible timing and setting / changing execution times in advance. For further analysis it's recommended to generate Thread Dumps to get more information about the current state of Threads in the JVM. The ThingWorx Support Tools Extension can help in generating those. See also CS245547 for more information and usage.

Sometimes the following error is seen filling up the application log: "HTTP header: referrer". It does not cause noticeable issues, but does fill up the log. This article has been updated to reflect the workaround: https://www.ptc.com/en/support/article?n=CS223714 To clear the error, locate the validation.properties ​inside the ThingworxStorage\esapi directory. Then  change the values of both Validator.HTTPHeaderValue_cookie and Validator.HTTPHeaderValue_referer to: Validator.HTTPHeaderValue_cookie= ^.*$ Validator.HTTPHeaderValue_referer= ^.*$

This is a basic troubleshooting guide for ThingWorx. It goes over the importance, types and levels of logs, getting started on troubleshooting the Composer, Mashup and Remote Connectivity.     For full-sized viewing, click on the YouTube link in the player controls.   Visit the Online Success Guide to access our Expert Session videos at any time as well as additional information about ThingWorx training and services.

Preface   In this blog post, we will discuss how to Start and Stop ThingWorx Analytics, as well as some other useful triaging/troubleshooting commands. This applies to all flavors of the native Linux installation of the Application.   In order to perform these steps, you will have to have sudo or ROOT access on the host machine; as you will have to execute a shell script and be able to view the outputs.   The example screenshots below were taken on a virtual CentOS 7 Server with a GUI as ROOT user.     Checking ThingWorx Analytics Server Application Status   1. Change directory to the installation destination of the ThingWorx Analytics (TWA) Application. In the screenshot below, the application is installed to the /opt/ThingWorxAnalyticsServer directory   2. In the install directory, there are a series of folders and files. You can use the ​ls​ command to see a list of files and folders in the installation directory.     a. You will need to go navigate one more level down into the ./ThingWorxAnalyticsServer/bin​ ​directory by using command ​cd ./bin​     b. As you can see above, we used the ​pwd​ command to verify that we are in the correct directory.   3. In the ./ThingWorxAnalyticsServer/bin directory, there should be three shell files: configure-apirouter.sh, configure-user.sh, and twas.sh     a. To run a status check of the application, use the command ./twas.sh status           i. This will provide a list of outputs, and a few warning messages. This is normal, see screenshot below:      b. You will have a series of services, which will have a green active (running) or red not active (stopped).           i. List of services: twas-results-ms.service - ThingWorx Analytics - Results Microservice twas-data-ms.service - ThingWorx Analytics - Data Microservice twas-analytics-ms.service - ThingWorx Analytics - Analytics Microservice twas-profiling-ms.service - ThingWorx Analytics - Profiling Microservice twas-clustering-ms.service - ThingWorx Analytics - Clustering Microservice twas-prediction-ms.service - ThingWorx Analytics - PredictionMicroservice twas-training-ms.service - ThingWorx Analytics - Training Microservice twas-validation-ms.service - ThingWorx Analytics - Validation Microservice twas-apirouter.service - ThingWorx Analytics - API Router twas-edge-ms.service - ThingWorx Analytics - Edge Microservice   Starting and Stopping ThingWorx Analytics   If you encounter any errors or stopped services in the above, a good solution would be to restart the TWA Server application.   There are two methods to restart the application, one being the restart ​command, the other would be using the stop​ and ​start​ commands.   Method 1 - Restart Command:   1. In the same ./ThingWorxAnalyticsServer/bin​ ​directory, run the following command: ./twas.sh restart     a. The output of a successful restart will look like the following: 2. The restart should only take a few seconds to complete   Method 2 - Stop / Start Commands:   1. In the same ./ThingWorxAnalyticsServer/bin​ ​directory, run the following command: ./twas.sh stop 2. After the application stops, run the following command: ./twas.sh start   Note: You can confirm the status of the TWA Server application by following the steps in the "Checking ThingWorx Analytics Server Application Status" section above.

Licensing summary, installing 8.1: - Now instance specific license used which prevents license sharing and protects our intellectual property further - 2 paths for getting up and running with a license:          -Connected: platform-settings configuration only          -Disconnected: text file generated, self-serve creation from PTC support portal, license_capability_response.bin generated to be placed in platform folder   Connected / Disconnected mode LicensingSubsystem::GetLicenseState returns : UNINITIALIZED in disconnected mode LICENSE_EXISTS in connected mode   User Journey Refer to Licensing ThingWorx 8.1 and Later for specific instructions for generating a license for your instance   NOTE: Each instance needs a valid license file to be running.   Troubleshooting: - If any misconfiguration or connection failures occur, error messages will be thrown to Application log Example: unable to fetch license file with device id; Unable to connect to the PTC license server. Please make sure the LicensingConnectionSettings settings... - Connection attempt will occur upon ThingWorx startup. If connection can't be made, instance will be following disconnected scenario  -Make sure Pop Up Blockers are turned off     Platform Settings - Licensing License Connection Settings (in platform-settings.json - plain text sample) -new section for licensing connection strings: -user name - used to connect to ptc support portal -password - encrypted (recommended) or plain text password used to connect to ptc support portal   "LicensingConnectionSettings": { "username":"<PTC_support_portal_username>", "password":"<PTC_support_portal_password>" }    New Services on Licensing Subsystem - GetInstanceID - returns instance/device ID which is created at startup - WriteLicenseUsageData - writes encrypted license usage (same as system data table) to ThingworxStorage\reports\LicenseUsageReport folder   Instance ID The license file is now bound to the platform Instance ID aka Device ID - (unlike most other PTC products where the license is bound to the hardware : CPUID, MAC, ...) This Instance ID is generated during first startup and stored in the database Instance ID is accessible in composer with LicensingSubsystem::GetInstanceID   Q: What happens when license files are bad or missing? A: If there is an invalid license file, with 8.0 valid license.bin needs to be in the folder before starting up; tomcat will crash. In 8.1 no need for license file as long as connected (platform-settings.json), no need to take an extra step, dynamic connection.  In disconnected scenario, ThingWorx will run for 30 days in limited mode with monitoring mashup accessible to check logs.   Q: Where is the InstanceID stored ? A: It's stored in the database   Q: Will the instanceID change during updates (minor 8.1.0 to 8.1.1) A: Device id's don't change.   Q: What will happen in disconnected scenario if there is no valid license after 30 days? The application will not start anymore or user is not able to login? A:  It shuts down, so there is no more "limited" mode. However, a user can come along on day 55 (for example) and can drop in a valid license and start the web app to get it fully running.   Q: What happens if the customer has to reinstall the platform after the license has been fetched ? Is it possible to "return" the license ? A: Reinstalling the platform results in the generation of a new Device ID, therefore a new license file will need to be generated.  

How to enable ThingWorx Performance Advisor Applies To ThingWorx 7.2+ Description How to enable ThingWorx Performance Advisor Resolution In the ThingWorx Composer, go to Systems > Subsystems, select the PlatformSubsystem and choose Configuration In the Metrics Reporting Service Configuration Select the "Enable Metrics Reporting" checkbox to activate Performance Advisor reporting Enter your current PTC credentials (username and password) for either the customer support portal or the developer portal After providing those details, use the Request button to request an Authorization Key. Customer Number and Name will be filled automatically and an Authorization Key is generated which allows the server identifying itself to the PTC environment. Those fields are read-only. ThingWorx is now ready to send Performance Advisor data and metrics to PTC Related FAQ - Performance Advisor for ThingWorx | PTC https://community.thingworx.com/community/developers/blog/2017/05/22/performance-advisor-for-thingworx-explore-configure…

A common issue that is seen when trying to deploy, design or scale up a ThingWorx application is performance.  Slow response, delayed data and the application stopping have all been seen when a performance problems either slowly grows or suddenly pops up.  There are some common themes that are seen when these occur typically around application model or design.  Here are a few of the common problems and some thoughts on what to do about them or how to avoid them. Service Execution This covers a wide range of possibilities and is most commonly seen when trying to scale an application.  Data access within a loop is one particular thing to avoid.  Accessing data from a Thing, other service or query may be fast when only testing it on 100 loops, but when the application grows and you have 1000 suddenly it's slow.  Access all data in one query and use that as an in memory reference.  Writing data to a data store (Stream, Datatable or ValueStream) then querying that same data in one service can cause problems as well.  Run the query first then use all the data you have in the service variables.   To troubleshoot service executions there are a few methods that can be used.  Some for will not be practical for a production system since it is not always advisable to change code without testing first. Used browser development tools to see the execution time of a service.  This is especially helpful when a mashup is slow to load or respond.  It will allow quickly identifying which of multiple services may be the issue. Addition of logging in a service.  Once a service is identified adding simple logging points in the service can narrow what code in the service cases the slow down (it may be another service call).  These logging statements show up in the script logs with time stamps ( you can also log the current time with the logging statements). Use the test button in Composer.  This is a simple on but if the service does not have many parameters (or has defaults) it's a fast and easy way to see how long a service takes to return,' When all else fails you can get thread dumps from the JVM.  ThingWorx Support created an extension that assists with this.  You can find it on the Marketplace with instructions on how to use it.  You can manually examine the output files or open a ticket with support to allow them to assist.  Just be careful of doing memory dumps, there are much larger, hard to analyse and take a lot of memory.  https://marketplace.thingworx.com/tools/thingworx-support-tools Queries ​These of course are services too but a specific type.  Accessing data in ThingWorx storage structures or from external sources seems fairly straight forward but can be tricky when dealing with large data sets.  When designing and dealing with internal platform storage refer to this guide as a baseline to decide where to store data...  Where Should I Store My Thingworx Data?   NEVER store historical data in infotable properties.  These are held in memory (even if they are persistent) and as they grow so will the JVM memory use until the application runs out of it.  We all know what happens then.  Finally one other note that has causes occasional confusion.  The setting on a query service or standard ThingWorx query service that limits the number of records returned.  This is how many records are returned to from the service at the end of processing, not how many are processed or loaded in memory.  That number may be much higher and could cause the same types of issues. Subscriptions and Events ​This is similar to service however there is an added element frequency.  Typical events are data change and timers/schedulers.  This again is often an issue only when scaling up the number of Things or amount of data that need to be referenced.  A general reference on timers and schedulers can be found here.  This also describes some of the event processing that takes place on the platform.  Timers and Schedulers - Best Practice For data change events be very cautions about adding these to very rapidly changing property values.  When a property is updating very quickly, for example two times each second, the subscription to that event must be able to complete in under 0.5 seconds to stay ahead of processing.  Again this may work for 5-10 Things with properties but will not work with 500 due to resources, speed and need to briefly lock the value to get an accurate current read.  In these cases any data processing should be done at the edge when possible (or in the originating system) and pushed to the platform in a separate property or service call.  This allows for more parallel processing since it is de-centralized. A good practice for allowing easier testing of these types of subscription code is to take all of the script/logic and move it to a service call.  Then pass any of the needed event data to parameters in the service.  This allows for easier debug since the event does not need to fire to make the logic execute.  In fact it can essentially be stand alone by the test button in Composer. Mashup Performance This​ one can be very tricky since additional browser elements and rendering can come into play. Sometimes service execution is the root of the issue and reviewed above, other times it is UI elements and design that cause slow down. The Repeater widget is a common culprit. The biggest thing to note here is that each repeater will need to render every element that is repeated and all of the data and formatting for each of those widgets in the repeated mashup. So any complex mashup that is repeated many times may become slow to load. You can minimize this to a degree based on the Load/Unload setting of the widget and when the slowness is more acceptable (when loading or when scrolling). When a mashup is launched from Composer it comes with some debugging tools built in to see errors and execution. Using these with browser debug tools can be very helpful. Scaling an Application When initially modeling an application scale must be considered from the start. It is a challenge (but not impossible) to modify an application after deployment or design to be very efficient. Many times new developers on the ThingWorx platform fall into what I call the .Net trap. Back when .Net was released one of the quote I recall hearing about it's inefficiencies was "memory is cheap". It was more cost efficient to purchase and install more memory than to take extra development time to optimize memory use. This was absolutely true for installed applications where all of the code was complied and stored on every system. Web based applications are not quite a forgiving since most processing and execution is done on the single central web server. Keep this in mind especially when creating Shapes, Templates and Subscriptions. While you may be writing one piece of code when this code is repeated on 1,000 Things they will all be in memory and all be executing this code in parallel. You can quickly see how competition for resources, locks on databases and clean access to in memory structures can slow everything down (and just think when there are 10,000 pieces of that same code!!). Two specific things around this must be stated again (though they were covered in the above sections). Data held in properties has fast access since it is in JVM memory. But this is held in memory for each individual Thing, so hold 5 MB of information in one Thing seems small, loading 10,000 Thing mean instant use of 50 GB of memory!! Next execution of a service. When 10 things are running a service execution takes 2 seconds. Slow but not too bad and may not be too noticeable in the UI. Now 10,000 Things competing for the same data structure and resources. I have seen execution time jump to 2 minutes or more. Aside from design the best thing you can do is TEST on a scaled up structure. If you will have 1,000 Things next year test your application early at that level of deployment to help identify any potential bottlenecks early. Never assume more memory will alleviate the issue. Also do NOT test scale on your development system. This introduces edits changes and other variables which can affect actual real world results. Have a QA system setup that mirrors a production environment and simulate data and execution load. Additional suggestions are welcome in comments and will likely update this as additional tool and platform updates change.

This blog is intended to help diagnose and fix the most common issues that may be encountered when working with ThingWatcher. It cannot be stressed strongly enough that you should be familiar with your data including the average time interval between data points, and the collection duration and certainty threshold you specified. Before you start troubleshooting ThingWatcher, check that result and training microservices is running. For testing result microservices open a web browser and paste result URL; http://<IP of microservices>:<Port of results microservices>/results/models (e.g., http://localhost:8096/results/models) For testing training microservices open a web browser and paste training URL; http://<IP of microservices>:<Port of training microservices>/training (e.g., http://localhost:8091/training) If you see either: {"values":[],"total":0,"next":null,"previous":null} or a list of training jobs in JSON format, this means the result and training microservice service is available. 1. Question. I haven't seen an anomaly but I believe that my 'property' is anomalous?         This can be caused by different reasons, here are the most common causes: The certainty is too high. If the certainty is too high ThingWatcher is conservative in its categorization of "true positives" and therefore may emit more "false negatives". Reducing the certainty will change this behavior but note that ThingWatcher may now categorize too many "false positives" as a result. In other words, ThingWatcher may detect the desired anomalies but also some non-anomalies. The 'property' is anomalous during training data collection. If ThingWatcher creates a predictive model from anomalous data, it may not be able to detect the desired anomalies during MONITORING because the data does not really appear to be anomalous. So ThingWatcher treats this pattern as 'normal'. Therefore, ensure that 'property' values are also non-anomalous during training. There are long time gaps during the monitoring state so ThingWatcher stays in Buffering and categorizes these data points as non-anomalous. 2. Question. ThingWatcher detects an anomaly but my 'property' is non-anomalous? The certainty might be too low. In this case, ThingWatcher reports anomalies when the incoming data pattern looks even slightly different from the expected data pattern. ThingWatcher might need more training data. If the 'property' data has a pattern that occurs over a long time span, ThingWatcher needs to collect multiple cycles of all these patterns in order to detect a true anomaly without emitting too many false positives. 3. Question. ThingWatcher is in FAILED State, why?     There are many possible reasons for a failed state, here are the most likely problems that can cause a failed state. ThingWatcher emits a FAILED ThingWatcher State because the training service has not been setup or is down. similarly, the result service is not available. NotemessageText=Unexpected exception. {Throwable=[ConnectException: Operation timed out}]]messageText=Unexpected exception. {Throwable=[ConnectException: Connection refused}]]. Note that ThingWatcher is still able to collect all training data and you will only begin to see these failed states after ThingWatcher tried to post the training request. ThingWatcher emits a FAILED ThingWatcher State because time gaps prevent the data collection for training.You will see this warning in the log messages : "A long time gap was detected in the data that is greater than the threshold of {n}". This means you have a long gap in the training data and ThingWatcher will recollect the data. If there are more than 3 recollections due to a long time gap, ThingWatcher transitions to a failed state and will not be able to recover. In this case you can either instruct ThingWatcher to retrain and try again or check the data source to make sure it does not have long gaps. 4. Question. Why does ThingWatcher remain in Buffering? There are many possible reasons for ThingWatcher to remain in Buffering, but the most likely issue is time gaps which cause ThingWatcher to remain stuck in Buffering. If the incoming data regularly contains long time gaps, you will notice that ThingWatcher keeps alternating between the monitoring and buffering states. You may need to provide better quality data i.e. more evenly spaced data. Source: Alex Meng, Specialist Software Engineer

An introduction to installing the ThingWorx platform. Information on the environment, prerequisites, and configuration steps when installing ThingWorx. Includes walkthroughs of installing with H2 and PostgreSQL databases, an introduction and demonstration of the Linux installation script, solutions to common installation problems and more.     For full-sized viewing, click on the YouTube link in the player controls.   Visit the Online Success Guide to access our Expert Session videos at any time as well as additional information about ThingWorx training and services.

Error: Failed to load SQL Modules into database Cluster. This error is usually seen during initializing the database cluster phase (in the setup as shown below). To resolve this issue, follow below steps: Create a PostgreSQL data folder before you start the installation (c:\postgres-data) and give full control for the user. Select the newly created data directory during the setup. After the successful installation, you can follow the remaining procedure for configuring it with ThingWorx from the respective installation document.