IoT Tips

  Hello, ThingWorx Users!   As promised, we are back with Episode 02 of ThingWorx on Air. Listen to our PM Milan share the secrets of Operator Advisor and how we built the solution with an eye for IIoT developers.   Learn how Operator Advisor provides you with pre-built snippets of code for widgets, services, etc. targeted specifically for shop floor operators. No more starting from scratch!   Reach out if you have any questions or topic requests!   Stay connected, Kaya   P.S. Keep your ears peeled for the “Wowza Widget of the Week!”

This is a lessons learned write up that I proposed to present at Liveworx but it didn't make the cut, but I did want to share it with all the developer folks. Please note that this is before we added Influx and Micro Services, which help improve the landscape. Oh and it's long 🙂 ------------------------------------------ This is written as of Thingworx 8.2   Different ways to scale Data and Processing with Thingworx Two main issues are targeted Data Storage Platform processing Data Storage in Thingworx Background Issues around storage is that due to the limited indexing in the Persistence Provider with then the actual values according to the datashape being in a JSON Blob So when you look in the Persistence Provider you’ll see Source sourceType Location entityID Datetime Tags ValueJSONBlob   The first six carry an index, the JSON Blob which holds the values according to the datashape is not, that can read something like {value1:firstvalue,value2:secondvalue,value3:[ …. ]} etc. This means that any queries beyond the standard keys – date/time, entityID (name of Stream or DataTable), source, sourcetype, tags, location become very inefficient because it will query the records and then apply the datashape query server side. Potentially this can cause you to pull way more records over from Persistence Provider to Platform than intended. Ie: a Query on Temperature in my data, that should return 25 records for a given month, will perhaps first return 250K records and then filter own to 25. The second issue with storage is that all Streams are stored in one table in the Persistence Provider using entityID as an additional key to figure out which stream the record is for. This means that your record count per table goes up much faster than you’d expect. Ie: If I have defined 5 ValueStreams for 5 different asset types, ultimately all that data is still in one table in the Persistence Provder. So if each has 250K records, a query against the valuestream will then in actuality be a query against 1.25 million records. I think both of these issues are well known and documented? By now and Dev is working on it. Solution approaches So if you are expecting to store a lot of records what can you do? Archive The easiest solution is to keep a limited set and archive off the rest of the data, preferably into a client’s datalake that is not part of the persistence provider, remember archiving from one stream to another stream is not a solution! Unless … you use Multiple Persistence Providers Multiple Persistence Providers Thingworx does support multiple persistence providers for storing data. So you can spin up extra schemas (potentially even in the same DataBase Server) to be the store for additional Persistence Providers which then are mapped to a specific Stream/ValueStream/DataTable/Blog/Wiki. You still have to deal with the query challenge, but you now have less records per data store to query through. Direct queries in the Persistence Provider If you have full access to your persistence provider (NOTE: PTC Cloud Services does NOT provide this right now). You can create an additional JDBC connection to the Persistence Provider and query the stream directly, this allows you to query on the indexed records with in addition a text search through the JSON Blob all server side. With this approach a query that took several minutes at times Platform side using QueryStreamEntries took only a few seconds. Biggest savings was the fact that you didn’t have to transfer so many records back to the Platform server. Additional Schemas You can create your own schema (either within the persistence provider DB – again not supported by PTC Cloud Services) in a Database Server of your choice and connect to it with JDBC/REST. (NOTE: I believe PTC Cloud Service may/might offer a standalone server with actual root access) This does mean you have to create your own Getter/Setter services to retrieve and store information, plus you’ll need some event to store (like DataChange). This approach right now is probably a common if not best practice recommendation if historical information is required for the solution and the record count looks to go over 1 million records and can’t just be queried based on timestamp. Thingworx Event Processing Background Thingworx will consistently deal with many Things that have many Properties, and often times there will be Alerts/Rules that need to run based on value changes. When you are using straight up Alerts based on a limit value, this isn’t such a challenge, but what if you need to add some latch/lock/debounce logic or need to check against historical values or check multiple conditions? How can you design something that can handle evaluating these complex rules, holds some historical or derived values and avoid race conditions and be responsive? Potential Problems Race conditions Multiple Events may need to update the same Permanent or Temporary store for the determination of a condition. Duplicates If you don’t have some ‘central’ tracker, you may possibly trigger the same rule multiple times. Slow response You are potentially triggering thousands or more events at the same time, depending on how you’ve set up your logic, your response could become so slow that the next event will be firing before finish and you’ll overload the system. System queue overrun If your events trigger faster than you can handle the events, you will slowly build up and finally overrun the event queue. System Thread count overrun Based on the number of cores in your system, you can overrun the number of threads that can be handled. Connection Pool overrun Each read/write to a stream/datatable but also Property Persist is a usage of the connection pool to your persistence provider. If you fire a lot at once, you can stack up requests and cause deadlocks System out of memory Potentially in handling the events you are depending on in memory information, if that is something that grows over time, you could hit an ‘Out of Memory’ issue. Solution Approaches Batch processing Especially with Agents/Sources that write a set of property updates, you potentially trigger multiple threads that all may need the same source information or update the same target information. If you are able to process this as a batch, you can take all values in account and only process this as a single event and have just a single read from source or single write to target. This will be difficult to achieve when using something like Kepserver, unless it is transferring as something non-standard like MQTT. But if you can have the data come in as a single REST POST this approach becomes possible. In Memory vs. Table/Stream Storage To speed up response time, you can put necessary information into Memory vs. in a DataTable or Stream. For example, if you need the most current received record together with some historical values, you could: Use a Stream but carry the current value because the stream updates async. (ie adding the current value to the stream doesn’t guarantee that when you read from the stream it has already been committed) Use a DataTable because they are synchronous but it can make the execution slow, especially if you are reaching 100K records or more Use an InfoTable or JSON Property, now this information is in memory and runs the fastest and is synchronous. Note that in some speed testing JSON object was faster than InfoTable and way faster than DataTable. One challenge is that you would have to do a full overwrite if you need to persist this information. Doing a full write does open up the danger of a race condition, if this information is being updated by multiple threads at the same time. If it is ok to keep the information in memory than an InfoTable is nice because you can just add/delete rows in memory. I sadly haven’t figured out yet how to directly do this to a JSON object property :(. It is important to consider disaster recovery scenarios if you are only using this in memory Centralized Processing vs. Distributed Processing Think about how you can possibly execute some logic within the context of the Entity itself (logic within the ThingShape/ThingTemplate) vs. having it fire into a centralized Service (sync or async) on a separate Entity. Scheduler or Timer As much as Schedulers and Timers are often the culprit of too many threads at the same time, a well setup piece of logic that is triggered by a Scheduler or Timer can be the solution to avoid race conditions If you are working with multiple timers, you may want to consider multiple schedulers which will trigger at a specific time, which means you can eliminate concurrence (several timers firing at the same time) Think about staggering execution if necessary, by using the hated, looked down upon … but oft necessary … pause() function !!!! Synchronous vs. Asynchronous Asynchronous execution can give great savings on the processing speed of a thread, since it will kick off the asynch parts and continue on. The terrible draw back, you can’t tell when it is finished nor what the resulting output is. As you mix and match synch/asynch vs processing speed, you may need to consider other ways to pick up when an asynch process finishes, some Property elsewhere that will trigger into a DataChange for example. Interesting examples Batch Process With one client there was a batch process that would post several hundred results at once that all had to be evaluated. The evaluation also relied on historical information. So with some logic these properties were processed as a batch, related to each other and also compared to information held in memory besides historically storing the information that came in. This utilized several in memory objects and ultimately also an eval() statement to have the greatest flexibility and performance. Mix and Match With another client, they had a requirement to have logic to do latch/lock and escalation. This means that some information needs to be persisted, however because all the several hundred properties per asset are coming in through Kepware once a second, it also had to be very fast. The approach here was to have the DataChange place information into an in memory infotable that then was picked up by a separate latch/lock/escalation timer to move it over to the persistent side. This allowed for the instantaneous processing of DataChange and Alerts, but also a more persistent processing of latch/lock/escalation logic. In Conclusion Remember that PTC created its software for specific purposes. I don’t think there ever will be a perfect magical platform that will do everything we need and want. Thingworx started out on a specific path which was very high speed data ingest and event platform with agnostic all around connectivity, that provided a very nice holistic modeling approach and a simple way to build UI/UX. Our use cases will sometimes go right past everything and at times to the final frontier aka the bleeding edge and few are a carbon copy of another. This means we need to be innovative and creative. Hopefully all of you can use the expert knowledge you have about our products to create those, but then also be proactive and please share with everyone else!  

  Some call him JB. Some call him Joe. Others call him @bironology. I call him an awesome guy—he’s our CTO of IoT here at PTC—Joe Biron!   Joe’s an architect at heart, a developer, an avid gamer and a technologist (check him out on Twitter @bironology).   Watch as he guest stars in the Microsoft Channel 9 “IoT Deep Dive Live” show! Listen to him explain how you can build end-to-end industrial solutions with ThingWorx and Azure. ­­ And, guess who’s running the demo behind the scenes: our Global ThingWorx COE Lead, Neal Hagermoser, who you may recognize from a previous Ask Kaya post where I interviewed him on why we chose to partner with Azure.   Enjoy the show and stay connected! Kaya

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

Objective Use Influx as a database to store data coming from Kepware ThingWorx Industrial Connectivity server   Prerequisite Configure ThingWorx connection to Kepware’s KEPServerEX  and bind tags that exist in KEPServerEX to things in the ThingWorx model as referenced in Industrial Connections Example   Configuration Steps 1. Create database in Influx for ThingWorx: Connect:    influx -precision rfc3339 > SHOW DATABASES > CREATE DATABASE thingworx   2. Create Influx Persistence Provider     and configure   3. In the Industrial Thing where the Remote Properties are bounded define Value Stream     and make sure to have Persistence Provider set to Influx and is set to Active     4. In the Value Stream Properties and Alerts define the mappings using Manage Bindings to specify what properties are to be stored in this value stream     5. Save it and test it to make sure properties are stored in Influx: > use thingworx > show measurements   name   ----   Channel1.Device1 > show field keys on thingworx from "Channel1.Device1" > select Channel1_Device1_Tag2 from "Channel1.Device1"   name: Channel1.Device1   fieldKey fieldType   -------- ---------   Channel1_Device1_Tag10 integer   Channel1_Device1_Tag11 integer   Channel1_Device1_Tag12 integer   Channel1_Device1_Tag13 integer   Channel1_Device1_Tag14 integer   Channel1_Device1_Tag15 integer   Channel1_Device1_Tag16 integer   Channel1_Device1_Tag17 integer   Channel1_Device1_Tag18 integer   Channel1_Device1_Tag19 integer   Channel1_Device1_Tag2 integer   Channel1_Device1_Tag20 integer   Channel1_Device1_Tag21 integer   Channel1_Device1_Tag3 integer   Channel1_Device1_Tag4 integer   Channel1_Device1_Tag5 integer   Channel1_Device1_Tag6 integer   Channel1_Device1_Tag7 integer   Channel1_Device1_Tag8 integer   Channel1_Device1_Tag9 integer   shows data stored in Channel1_Device1_Tag2: >select Channel1_Device1_Tag2 from "Channel1.Device1"   2019-02-20T16:26:13.699Z 8043   2019-02-20T16:26:14.715Z 8044   2019-02-20T16:26:15.728Z 8045   2019-02-20T16:26:16.728Z 8046   2019-02-20T16:26:17.727Z 8047   2019-02-20T16:26:18.725Z 8048   2019-02-20T16:26:19.724Z 8049   2019-02-20T16:26:20.722Z 8050   2019-02-20T16:26:21.723Z 8051   2019-02-20T16:26:22.722Z 8052

Hi everyone,   Maybe you got my email, I just wanted to post this also here.   I built a CSS generator for a few widgets, 8 at the moment. This is on a cloud instance accessible by anyone.   Advantages:      - don't have to style buttons and apply style definitions over and over again      - greater flexibility in styling the widget      - you don't have to write any CSS code   The way this works: you use the configurator to style the widget as you want. Use also a class to define what that widget is, or how it's styled. For example "primary-btn", "secondary-btn", etc. Copy the generated CSS code into the CustomCSS tab in ThingWorx and on the widget, put the CustomClass specified in the configurator.   As a best practice, I'd recommend placing all your CSS code into the Master mashup. And then all your mashups that use that master will also get the CustomCSS. So the only thing you have to do to your widgets in the mashups, is fill the CustomClass property with the desired generated style. Also, comment your differently styled widgets by separating them with /* My red button */ for example.   The mashups for this won't be released, this will only be offered as a service. As you'll see in the configurator, they are not that pretty, the main goal was functionality.   Here is the link to the configurator: https://pp-18121912279c.portal.ptc.io/Thingworx/Runtime/index.html#master=CSSMaster&mashup=ButtonVariables User: guest Password: guest123123   Give it a go and have fun! 🙂   NOTE: I will add more widgets to this in the future and will not take any requests in making it for a specific widget, I make these based on usage and styling capabilities.    

Question: Is there a Security log entry added when a user is refused access to Composer? Answer:The Security log is mainly for user login and authentication items; since this is not authentication per se, we don't log any messages there. The Application log should have log entries noting any errors. Question:  Do the gauges and graphs now behave more reactive without reloads of massive data. just easy show "realtime" data? Answer: The Custom Charts we have on the Market place should alleviate some of that - depending on how the data refresh is set up, that should redraw. The changes we have done on the layout side won't have any impacts there, unless the browser window is resized. Question:Will we offer a library of "Design themes"?  Answer:We are working on adding prebuilt themes for a future release. Question: Does the new Mashup builder store Mashups in the same way? Are these new Mashups taking into account a runtime separated from the platform? Answer: It should be the same - the runtime instance is still separated. Question:What about inheritance with themes? Answer: The support inheritance - if you have a Contained Mashup without a Theme set, they should be inheriting the parent's Theme. Question: Is it posible to duplicate an expression / validator? are there plans to include the event router there? Answer: We don't have duplication support in the current release . Yes, we have plans to add more 'non-visual' widgets to the list, that includes Event Router and Status Message. Question: Is it planned to generate the preview images dynamically based on mashup contents? Answer: We are looking into dynamic updates for images - it might get expensive to generate images based on the volume of data that is bound to the widgets, so we're exploring different ways to resolve this. Question: Will these new BETA widgets be forward compatible? Answer:Correct, and we are working on adding more widgets! The property definitions within them shouldn't undergo any changes (as in properties won't get removed). We're always looking to enhance these further, so they might get additional features/ properties. Question: Any guide available for custom widget development? Answer: We are working on adding development guides for Web Components, and working with the respective SDKs.

Why? Reduce or eliminate hardware costs Get database portability across on-premise and cloud compatible virtualization High speed and minimum downtime Optimize performance Three deployment options: Single: best for apps requiring resource guarantee at database level Elastic pool: SAAS apps with multiple databases achieving better cost efficiency Managed instance: best for modernization at scale MS SQL Improvements: Ingest millions of data items/day with imrpoved MS SQL 150% improvement  ingestion throughput with MS SQL persistence provider Optimized indexing to achieve better peformance for the same compute at the same price ThingWorx with Microsoft database solution: Azure SQL logical server (single instance and elastic pool) v12 Azure SQL managed server v12 MS SQL sever 2016 Azure PostgreSQL 9.6 and 10 Q: What is the rate as compared to PostgreSQL? A: We are in process launching new sizing guide that will be out in a few weeks. MS SQL is around 15-22K writes per sec. Comparable to Postgres.

In this video we show the setup for anomaly detection (ThingWatcher) in release 8.4. We also show how to create an anomaly alert.  

In this video we show a simple use case on how to setup a transformed property to collect statistical values  

In this video we cover the installation of the platform analytics services which include: Descriptive services and property transform services.  

In this video we introduce the Descriptive Services and property transform services that are found on the platform analytics media  

This video shows the steps to install ThingWorx Analytics Server 8.4 as well as the ThingWorx Analytics Extension.

We are excited to announce ThingWorx 8.4 is now available for download!    Key functional highlights ThingWorx 8.4 covers the following areas of the product portfolio: ThingWorx Analytics and ThingWorx Foundation which includes Connection Server and Edge capabilities.   ThingWorx Foundation Next Generation Composer: File Repository Editor added for application file management New entity Config Table Editor to enable application configurability and customization Localization support fornew languages: Italian, Japanese, Korean, Spanish, Russian, Chinese/Taiwan, Chinese/Simplified Mashup Builder: Responsive Layout with new Layout Editor 13 new and updated widgets (beta) Theming Editor (beta) New Functions Editor New Personalized Workspace Platform: Added support for AzureSQL, a relational database-as-a-service (DBaaS) as the new persistence provider A PaaS database that is always running on the latest stable version of SQL Server Database Engine and  patched OS with 99.99% availability.   Added support for InfluxData, a leading time series storage platform as the new ThingWorx persistence provider Supports ingesting large amounts of IoT data and offers high availability with clustering setup New extension for Remote Access and Control Supports VNC, RDP desktop sharing for any remote device HTTP and SSH connectivity supported An optional microservice to offload the ThingWorx server by allowing query execution to occur in a separate process on the same or on a different physical machine. Installers for Postgres versions of ThingWorx running on Windows or RHEL AzureSQL InfluxDB Thing Presence feature introduced which indicates whether the connection of a thing is “normal” based on the expected behavior of the device. Remote Access Extension Query Microservice: Click and Go Installers for Windows and Linux (RHEL) Security: Major investments include updating 3rd party libraries, handling of data to address cross-site scripting (XSS)  issues and enhancements to the password policy, including a password blacklist. A significant number of security issues have been fixed in this release. It is recommended that customers upgrade as soon as possible to take advantage of these important improvements. Docker Support  Added Dockerfile as a distribution media for ThingWorx Foundation and Analytics Allows building Docker container image that unlocks the potential of Dev and Ops Note:  Legacy Composer has been removed and replaced with the New Composer.   Documentation: ThingWorx 8.4 Reference Documents ThingWorx Platform 8.4 Release Notes ThingWorx Platform Help Center ThingWorx Analytics Help Center ThingWorx Connection Services Help Center  

Beginning with version 8.4.0 ThingWorx Analytics Manager is now able to delete Jobs by filter. Underneath video demonstrates this capability.   

Beginning with version 8.4.0 ThingWorx Analytics Server can now automatically create metadata (Json file) based on the uploaded csv. file. Underneath video demonstrates the steps for automated metadata detection.

Key Points -8.4 installers can be used to install on clean machines and cannot be used for upgrading from previous versions -The current rule for upgrading via installer is that one must start from a clean build using the installer. After our future upgradable installer release, if one wants to upgrade, they must start with a twx installer installed versions. -The Flow only Installer is for Enterprise version customers running 8.4 or previous versions of ThingWorx and want ot add the flow capability. Unified Installer Framework -Common tool set, common UX -Unified product install experience Individual Product Installers -allow one to start using ThingWorx platform and applications faster -installs all components with single button click Improved Download Experience -new portal/wizard/image repository Trial Installers ThingWorx based installers -Navigate installer released in October 2018, installs the base twx (navigate), nav configuration and licensing wizards ThingWorx Flow installer included in pre-release of ThingWorx 8.4 ThingWorx Installer -Full Installers - January-early February rollout SCO/SCP Apps   For more information on installer, please refer to our documentation.