We are excited to announce the release of the latest version of ThingsBoard Edge! This release brings most of the updates from ThingsBoard 3.9.0 Release and also enhances the ability of ThingsBoard Edge to ingest larger volumes of data with greater efficiency. Let’s explore these powerful new features!
The ‘Why’ Behind This Release
Imagine a small manufacturing plant: how many devices and sensors can you install? A single plant can manage hundreds of devices, and ThingsBoard Edge, using the PostgreSQL database, was designed to meet the needs of such operations.
But what happens when your production site is no longer small? The number of devices increases proportionally with its size.
Some of our customers manage more than 10,000 devices per Edge, collecting data from multiple large production sites and delivering it to the cloud. The system was unable to handle the growing load, leading to performance degradation and slower query responses. The massive volumes of data transmitted per second overwhelm a single PostgreSQL table. The system required another database and queuing solution.
Under demanding workloads, the SQL database for event persistence does not align with best practices. Kafka, on the other hand, is a more suitable option for this task because it was designed to handle high-throughput data streams.
What Can New Implementations Do for Edge?
- Improved Speed: Faster reading and writing of cloud events, regardless of the size of events already stored in Kafka.
- Horizontal Scalability: Scale Kafka and Cassandra to store and process even larger volumes of data.
- Enhanced Performance: Cassandra’s high read and write throughput ensures superior performance under demanding workloads.
Now, let’s dive into the details of this release!
Apache Kafka for Cloud Events
First, we significantly enhanced cloud event processing in ThingsBoard Edge.
In the traditional setup, PostgreSQL was used for queuing and processing cloud events. However, as the number of events grows, the risk of performance degradation increases. To address this, we’ve introduced Apache Kafka as an alternative to PostgreSQL.
Why Kafka?
If your Edge sends millions of event messages to ThingsBoard Cloud daily, Kafka can handle them effortlessly by scaling and distributing the load across multiple brokers.
With Apache Kafka as the queue type, ThingsBoard Edge performs consistently under substantial loads over time. Kafka ensures efficiency with constant time complexity (O(1)) for retrieving data, regardless of the volume, ensuring reliability and speed.
Even peak load periods do not affect system performance. The balance is achieved through a partitioning mechanism that allows the overall load to be distributed across the clusters.
Apache Cassandra Support
To enhance performance when managing time-series data, we’ve also added support for Apache Cassandra database as part of our hybrid database approach.
Cassandra is ideal for high-volume time-series data ingestion, while PostgreSQL excels at relational queries and complex data management.
Cassandra enables high-speed read/write performance for real-time time-series data processing. The processed result is then stored in PostgreSQL for reporting.
By enabling this hybrid database approach for ThingsBoard Edge, we ensure that each Edge instance can handle increasing data volumes, providing operational continuity and availability under all circumstances.
The integration of Apache Kafka and Cassandra introduces unparalleled performance, reliability, and scalability, ensuring smooth operations even under the most demanding workloads.
Install now for Ubuntu, CentOS/RHEL Server , or using Docker (Linux or Mac OS).
Dynamic Edge Attributes
From release 3.9.0 onward, you can also easily fetch Edge Attributes, such as configurations, access tokens, or metadata, and use them as placeholders in the Rule Chains.
Key Benefits of Dynamic Edge Attributes:
- Make more accurate business decisions based on retrieved attributes.
- Integrate seamlessly with external servers.
- Use a single Edge Rule Chain template to serve hundreds or thousands of Edge instances.
Each unique Edge instance dynamically substitutes placeholders with its specific attributes in real time, eliminating the need to create separate Rule Chain templates for every instance.
Use Case Scenario:
Imagine managing one hundred Edges. They all require the same business logic (Rule Chain), and it would be nearly impossible to distinguish between them during data transmission. With dynamic attributes, you can assign a unique access token to each Edge, making it easy to identify and label each one distinctly.
This feature greatly simplifies Edge management, reducing complexity and enabling efficient, scalable operations.
Why Update to ThingsBoard Edge 3.9.0?
With the release of ThingsBoard Edge 3.9.0, we are empowering organizations to scale their IoT ecosystems with confidence and precision. The dynamic Edge attributes and hybrid database capabilities, unlock new possibilities for processing and analyzing IoT data at the edge while maintaining seamless cloud synchronization.
Now is the perfect time to embrace these powerful updates and take your IoT solutions to the next level. Update to ThingsBoard Edge 3.9.0 today and experience the difference—where innovation meets efficiency to drive your success forward.
Uncover the newly enhanced power of ThingsBoard Edge!
