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9.0 Sneak Peek: ThingWorx Architecture for Active-Active Clustering

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Hi everyone,

 

In anticipation of ThingWorx 9.0’s biggest feature, active-active clustering, we’d like to provide an architectural overview of a sample active-active configuration and its underlying components. If you haven’t already seen it, we invite you to read our previous Community tech tip, where we introduce the concept of active-active clustering for ThingWorx Foundation, which enables you to:

  • significantly reduce unplanned downtime for your mission-critical services and apps
  • support horizontal scalability of the ThingWorx Server where you can scale your services up and down based on your requirements
  • easily run, package, deploy, and operate advanced apps and services with the help of intuitive browser-based navigation, interactive monitoring and debugging tools, and more
  • deploy anywhere - public cloud, private datacenter, on-premise, hybrid, or even locally on your laptop with deep optimizations for Azure

Now, before we go too deep, we’d like to let you know that you can continue to seamlessly upgrade from previous versions of ThingWorx releases to upcoming ThingWorx 9.0  releases. Previously, you could deploy ThingWorx Foundation in a “single server” mode, and, for a high availability in “active-passive cluster” mode (see here for details). In the ThingWorx 9.0 release and onwards, you’ll be able to continue to deploy ThingWorx Foundation in a “single server” mode and for high availability scenarios via our new “active-active cluster” mode. Please note that active-passive clustering configuration will no longer be supported in ThingWorx 9.0 or onwards.

 

Let’s start with a quick recap on how the ThingWorx Foundation 9.0 release would look like in single server deployment.

 

ThingWorx 9.0 Deployed in a "Single-Server" Architecture

Below is a high-level diagram depicting the main architectural layers and components of ThingWorx Foundation deployed in a single server mode.

 

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Deployment Components

Below is a brief summary of all major architectural components and their purpose in the deployment architecture:

 

The Client Layer

This layer is comprised of everything that connects with, sends data to, and receives content from the ThingWorx platform. It be broken down into two groups:

  • Devices/Things: Things, devices, agents, and other assets.
  • Users/Clients: People and the respective products (primarily web browsers) they use to access ThingWorx.

 

The Application Layer

This layer is where ThingWorx Foundation and other applications deployed with ThingWorx Foundation reside, such as ThingWorx Analytics, ThingWorx Connection Server, ThingWorx Azure IoT Hub Connector and others. This layer provides connectivity to the client layer, performs authentication and authorization checks, ingests/processes/analyzes content, and reacts to conditions by sending alerts. For a specific ThingWorx Foundation deployment that needs basic device data ingestion, processing and storage, you can setup only ThingWorx Foundation server. In some cases, with large number of device connections, you may want to setup ThingWorx Connection Server with ThingWorx Foundation in a single server for further scalable connectivity.

  • ThingWorx Foundation: ThingWorx Foundation is a java-based application that serves as a rapid, model-based application development platform.
  • Shared File Storage: Shared Disk space to contain ThingWorx Storage repositories, store and archive log files accessed by all ThingWorx Foundation servers. A NAS file storage, AWS Elastic File System, or Azure Files and others could be used for this purpose.

 

The Data Layer

ThingWorx Foundation includes several persistence provider implementations that enable you to choose a database option that best fits your use case. A persistence provider enables the connection to a data store and the ability to perform a CRUD operation on that data. See here for more information. Currently, there are two basic variations of persistence providers:

  • Model Provider – Responsible for ThingWorx model metadata and system data.
  • Data Provider – Responsible for runtime data ingested against the model elements, including streams, value streams, data tables, etc.

ThingWorx supports H2 (in-memory Database), PostgreSQL, MS SQL Server and AzureSQL as both model and data providers, and InfluxDB as only a data provider. Please see here for model and data best practices.

 

ThingWorx 9.0 Deployed in an Active-Active Clustering Reference Architecture

Below is a reference architecture diagram for ThingWorx 9.0 with multiple ThingWorx Foundation servers configured in an active-active cluster deployment. Please note that this is only one reference example of how ThingWorx 9.0 can be deployed in an active-active clustered environment. There could be other architectural configurations dependent upon the needs of the specific deployment.

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Deployment Components

Once you have developed an understanding of the basic architectural components in a single server mode, below are the additional components required to run ThingWorx in active-active cluster mode.

 

The Client Layer

This will be similar to what has been mentioned in the above single server configuration.

 

The Application Layer

In this layer, if you’re familiar with ThingWorx active-passive cluster configuration, then you may be aware of most of the components used below—with the exception of a new component: Apache Ignite that provides Distributed Caching for the horizontally scalable ThingWorx Foundation servers.

  • Load Balancer: A third-party device that receives network traffic and distributes requests among available servers. In active-active cluster configuration, the load balancer is used to direct WebSocket-based traffic to the ThingWorx Connection Servers while user requests (http/https) traffic is directly distributed to the ThingWorx Foundation servers. Users can continue to use a load balancer with ThingWorx 9.0 that they might already be using for their existing active-passive or single server deployments with ThingWorx 8.X or previous releases.  Some example load balancers include, but are not limited to: HAProxy, Azure Application Gateway, and AWS Application Load Balancer.
  • ThingWorx Connection ServicesThese services handle all messages routing to and from devices, providing scalable connectivity to the ThingWorx Foundation Server. With the ThingWorx 9.0 release, ThingWorx Connection Services have been upgraded with many additional features to support active-active clustering of the ThingWorx Foundation servers, where now they route all WebSocket traffic in a round robin fashion to the connected ThingWorx Foundation servers. Depending upon the various use cases, one could use multiple ThingWorx Connection Services available, such as ThingWorx Connection Server, ThingWorx Azure IoT Hub Connector, and ThingWorx Protocol Adapter Toolkit. Please see here for further details.
    • Please note that for ThingWorx 9.0 releases, ThingWorx Connection Server would be required in an active-active configuration to support all the WebSocket-based traffic routing, including egress of files and device messages from multiple ThingWorx Foundation servers back to the devices, and it would also serve as WebSocket communication from ThingWorx Mashup-based applications to ThingWorx Composer.
  • ThingWorx Foundation: With ThingWorx 9.0 and onwards, you can set up ThingWorx Foundation servers in an N-active-active cluster model to provide higher availability to your applications and horizontally scale the Foundation server nodes up and down based on your scalability needs.
  • Apache Zookeeper: Apache ZooKeeper is a centralized service for maintaining configuration information and naming as well as providing distributed synchronization and group services. It is a coordination service for distributed applications that enables synchronization across a cluster. Specific to ThingWorx, ZooKeeper is used for distributed locking, selecting a singleton server during the server initialization, service discovery for Apache Ignite, allowing it to find instances of ThingWorx Foundation servers.
  • Apache Ignite: This offers a distributed cache for the active-active cluster setup. It is used by ThingWorx Foundation Servers to share state. It may be embedded with each ThingWorx instance or can be run as a standalone cluster for larger scale. In this configuration, Ignite is set up in a standalone cluster but can be run embedded within the ThingWorx Foundation. Running Ignite in a standalone cluster is more ideal for larger scale, as it supports higher vertical scale of memory in the deployment setup.

 

The Data Layer

ThingWorx is largely database agnostic. You can continue to use officially supported persistence providers that you may already be using in your existing deployments based off of ThingWorx 8.X or previous releases. Please look out for an upcoming ThingWorx update as well as enhanced installation documents to help with your upgrade and migration questions with the general availability of ThingWorx 9.0.


Please note that this diagram does not make the distinction between model and data providers; depending on your data ingestion needs, separate model and data providers can be used. As a reminder, all databases should be deployed in a high-availability configuration to help eliminate any single point of failure.

 

In closing, we can't wait to launch active-active clustering in 9.0 to help you:

  • dramatically further reduce application downtime
  • scale your deployments
  • and more efficiently manage your apps, regardless of where they’re deployed

 

If you have any questions about active-active clustering or its architecture, please do not hesitate to reach out!

 

Stay connected!

Kaya

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