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Visualizing IoT Data With MQTT, QuestDB, and Grafana

DZone

Monitoring Time-Series IoT Device Data Time-series data is crucial for IoT device monitoring and data visualization in industries such as agriculture, renewable energy, and meteorology. In this tutorial, we will guide you through the process of setting up a monitoring system for IoT device data.

IoT 241
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What Is RabbitMQ: Key Features and Uses

Scalegrid

It employs the Advanced Message Queuing Protocol (AMQP) to provide reliable, scalable message passing, crucial for modern applications dealing with large-scale, complex data flows. This makes it suitable for various industries and applications, including IoT, finance, and e-commerce.

IoT 130
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Scaling for Success: Why Scalability Is the Forefront of Modern Applications

DZone

In short, it is the ability to handle more data, more users, and more demand without sacrificing performance, reliability, or security. The reason is straightforward, today, applications generate enormous amounts of data. It is not uncommon to question why scalability has grabbed the attention of the masses these days.

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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes.

Big Data 321
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Best practices for Fluent Bit 3.0

Dynatrace

Fluent Bit is a telemetry agent designed to receive data (logs, traces, and metrics), process or modify it, and export it to a destination. Fluent Bit can serve as a proxy before you send data to Dynatrace or similar. However, you can also use Fluent Bit as a processor because you can perform various actions on the data.

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Transforming Telecom With AI/ML: A Deep Dive Into Smart Networks

DZone

The telecommunications industry has become an indispensable part of our interconnected society, fueling various functions ranging from traditional calls to lightning-fast Internet and the ever-expanding Internet of Things ( IoT ). Here's an example of how machine learning can optimize network performance:

Network 173
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Adding New Capabilities for Real-Time Analytics to Azure IoT

ScaleOut Software

The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.

IoT 52