
EMQX Cloud Serverless provides users with the blazing-fast deployment of MQTT services in just 5 seconds without concerns about server infrastructure management or resource allocation when service scales.
EMQX Cloud Serverless provides users with the blazing-fast deployment of MQTT services in just 5 seconds without concerns about server infrastructure management or resource allocation when service scales.
Migrate from Google Cloud IoT Core to EMQX Today! It might be the perfect alternative to Google IoT Core for your organization.
This article will explain MQTT over QUIC in detail to show the advantages and value of this leading technology implementation for IoT scenarios.
EMQX v5.0 has been verified in test scenarios to scale to 100 million concurrent device connections, which is a critically important milestone for IoT designers.
Combines Node Evacuation with simulated blue-green deployment, effectively addressing common issues such as multiple disconnections, potential service overload, and load imbalance during upgrades.
As we kick off the new year, the XMeter team is putting all our efforts towards developing the latest version of XMeter Cloud.
Development work on v1.9.0, has already begun, which aims to facilitate the connection of the industrial protocol gateway Neuron with multiple instances.
In February, the Neuron team devoted its efforts to developing new drivers. We added southbound drivers, including IEC61850 driver, Allen-Bradley DF1, and Profinet driver.
EMQX 5.0.16, 5.0.17, and 5.0.18 have recently been released, introducing multistream support for MQTT over QUIC.
The new version provides a new plugin designed for real-time AI inference on data streams such as video streaming. This is a generic AI function that is compatible with most pre-trained Tensor Flow Lite models.
MQTT X 1.9.1 has significantly reduced CPU and memory usage by 80% compared to the previous version, resulting in greatly optimized overall performance and reduced risk of system crashes.
We will first explain why this buffer is needed, then we will take the Kafka integration as an example, to introduce the high-level design, then drill down for more details to understand better how replayq works.