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Act locally, connect globally with IoT and edge computing

All Things Distributed

There are places so remote, so harsh that humans can't safely explore them (for example, hundreds of miles below the earth, areas that experience extreme temperatures, or on other planets). The answer to this question is actually on your phone, your smartwatch, and billions of other places on earth—it's the Internet of Things (IoT).

IoT 126
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Best practices for Fluent Bit 3.0

Dynatrace

Fluent Bit was created before Kubernetes existed when Internet of Things (IoT) was a new buzzword. Unfortunately, their market prediction wasn’t correct; the cloud became more successful than IOT. See the example below. However, Fluent Bit was designed to be lightweight, multi-threaded, and run on edge devices.

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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
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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 161
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Building A Log Analytics Solution 10 Times More Cost-Effective Than Elasticsearch

DZone

Examples of logs include business logs (such as user activity logs) and Operation and Maintenance logs of servers, databases, and network or IoT devices. Logs often take up the majority of a company's data assets. Logs are the guardian angel of business.

IoT 130
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Partner Summit 2024: Observability for digital transformation success

Dynatrace

Digital transformation – which is necessary for organizations to stay competitive – and the adoption of machine learning, artificial intelligence, IoT, and cloud is completely changing the way organizations work. Examples include streamlined release validation, predictive operations, and significant reductions in security false positives.

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Pipes And Filters Pattern

DZone

Examples of data sources could be home IoT devices, a video feed from roadside cameras, or continuous inventory updates from warehouses. Problem Context Consider a scenario where incoming data triggers a sequence of processing steps, where each step brings data closer to the desired output state.

IoT 136