LinkedIn Learning - Achieving Low - Latency Data with Edge Computing

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LinkedIn Learning - Achieving Low-Latency Data with Edge Computing
Language: English | Size:182.17 MB
Genre:eLearning
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Files Included :

Spoiler

01 - Introduction.mp4 (6.54 MB)
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02 - Prerequisites.mp4 (1.41 MB)
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03 - Exercise files.mp4 (1.04 MB)
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01 - What is edge computing.mp4 (10.35 MB)
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02 - Overview of data latency.mp4 (7.15 MB)
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03 - Why is low-latency data with edge computing important.mp4 (21.86 MB)
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01 - Reference architecture.mp4 (5.72 MB)
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02 - Messaging systems.mp4 (5.45 MB)
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03 - Push vs pull.mp4 (7.57 MB)
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04 - In-memory access.mp4 (7.5 MB)
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05 - Scalability.mp4 (13.52 MB)
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01 - Implementation architecture.mp4 (6.9 MB)
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02 - MQTT.mp4 (6.83 MB)
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03 - RabbitMQ.mp4 (9.18 MB)
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04 - Apache Geode.mp4 (9.09 MB)
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05 - Spring.mp4 (8.04 MB)
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01 - Demo example implementation overview.mp4 (7.99 MB)
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02 - Producing at the edge using RabbitMQ.mp4 (18.65 MB)
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03 - Consuming edge data using RabbitMQ.mp4 (21.21 MB)
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04 - Low-latency access using Apache Geode.mp4 (2.39 MB)
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01 - Wrap up.mp4 (3.78 MB)
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