ThingsBoard is an open-source IoT platform for monitoring, data processing, visualization of data along with device management.

Why Thingsboard?

It supports industry-standard IoT protocols – MQTT, CoAP, and HTTP.  ThingsBoard combines scalability, fault-tolerance, and performance to capture the device data for processing and monitoring. It provides its gateway server that can communicate with the attached devices. 

Build around Netty Framework due to which it provides support for many protocols and applications. New Hardware protocols can be added by just adding Inbound and Outbound channel handlers for new protocols with the netty framework.  

Thingsboard features

1) Security  

Support for provisioning and management of devices with credentials management. Custom security rules for each protocol can be applied.

2) Dashboard and Data Visualization

Built-in support for 100+ widgets components. Collect and visualize data from devices and assets in Dashboard with widgets.

3) Telemetry 

Analyze incoming telemetry and trigger alarms with complex event processing. Support event storage Api to capture Telemetry metrics.  

4) Rest API and RPC Support

Data workflow can be designed using Rest API and RPC Requests.

5) Push Device Data

Support to push Device data to other systems in real-time. 

6) Integration with Different Message Queues

Different connectors are available to connect with different implementations of message queues. The multiple message queue implementations: Kafka, RabbitMQ, AWS SQS, Azure Service Bus, and Google Pub/Sub are supported.

7) Hybrid Database support

Stores all entities in SQL databases and telemetry data in the NoSQL database. 

8) Rule Engine 

In-built rule engine, to configure rules for device state and different notifications or alarms can be generated based on the telemetry of the device. Data processing rules can be changed at runtime based on the device state.

9) Deployment, Standard and Cluster mode

On-premise and cloud deployments are supported along with Standard and Cluster mode are supported

10) Alarms Management

Create and Manage alarms related to devices, assets, and customers, etc. Rule policy can be applied to raise alarms for device state changes.

Use Cases:

Thingsboard IoT platform supports broad use cases specifically in fields of Fleet tracking, Smart Farming, Smart Metering, Smart Energy, Smart City, and Commercial Home Automation Solution. 

1) Smart Farming

Smart farming is a combination of hardware (IoT) and software (SaaS) to capture the data and use data to manage all the operations on the farm, both pre and post-harvest. 

2) Smart Metering

Smart Metering solutions are used to study consumption patterns. 

Alarms are integrated with smart metering with rules to identify any abnormalities or energy offenders

3) Smart Energy

Smart Energy is syncing different energy producers with energy consumers to optimize energy consumption based on data points.

4) Fleet management

Different types of fleet management solutions can be derived

1. Vehicle leasing, financing, maintenance, licensing, tracking, and diagnostics. 
2. Supply chain management.
3. Driver management, Speed management, Fuel management

Workflow :

Conclusion :

Thingsboard is a good choice to develop IoT Solutions. Its source code is available with Apache License. 

Security of IoT environment is the need of time to identify unauthorized access and reconfiguration of IoT devices. IoT networks required logging to analyze the data flow and allow different tools to do forensic analysis of logs in-case of security breaches.

We are now living in a world of IoT devices. Many IoT Platforms are developed in current years to support different IoT devices. Each IoT platform needs a logging mechanism to inform the user about the state of the system in case of high availability.
We have recently moved one of the customer’s ( IoT platform) sync log4j logging to async log4j logging mechanism.

We have decided on the following points for log4j to analyze the behavior of the system along with performance:

1) System throughput performance
2) Configuration of Log4j
3) Support to add logs in different storage e.g Files, Database asynchronously.
4) Support to add for Custom level. Need to add a new log level Audit.

Log4j supports async mode by the in-built async plugin. To enable it we need to add either existing and new appenders/loggers inside that async tag in log4j.xml
We have created Async appenders and added in appenders list inside log4j2.xml  

<Async name="asyncAppender" level="info">
<AppenderRef ref="fileAppender"/>
</Async>

As an async log4j implementation using lock-free structures, we have seen system performance increased to 25% in async with file appender only.
Testing system running 20 threads simultaneously creating different log level log-events at speed of 400 logs per second. Each log message size is around 4KB.

We have created two async appenders – One for file appender and one for console appender.
As the console is very slow in response, a console logger or appender should be run in an independent async mode without another appender, so that its slowness doesn’t impact other appenders.

No much change needed in the existing configuration of log4j to enable async mode.

We have also added a Custom level “AUDIT” and for enabling custom level in log4j2.xml we have added the following lines in log4j2.

<CustomLevels>
<CustomLevel name="AUDIT" intLevel="150" />
</CustomLevels>

Level of the custom level set’s between error and fatal level.
To add custom ( AUDIT) log in code, we have used the following method
LOGGER.log(Level.getLevel(“AUDIT”), “Audit Message {}”, log);

To add error level logs in the database, we have again added async appender along with JDBC appender with a connection pooling system.
It is also running in different async threads.

Log4j documentation provides a detailed explanation of configuration parameters.  
As the Log4j community added many improvements in recent years to increase the handling of logs, we have used log4j library version 2.13.1, 

Conclusion

By using async mode log4j, we have improved the performance and throughput of an IoT platform.