diff --git a/blogs-news/dynamically-scaling-video-inference-edge.html b/blogs-news/dynamically-scaling-video-inference-edge.html
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 <h2>Introduction</h2>
 
 <p dir="ltr">This case study describes how to redesign a traditional video inference pipeline with a monolithic architecture into a cloud-native architecture. Our use case combines edge computing and video inference. We explore how the new cloud-native architecture allows us use Kubernetes* pod scaling for a complex edge inference solution. <br /><br />
-The demo source code is published on <a href="https://github.com/clearlinux/cloud-native-demos">GitHub</a>. The software uses the <a href="https://software.intel.com/en-us/openvino-toolkit">Intel® Distribution of OpenVINO™</a> and <a href="https://hub.docker.com/u/clearlinux">container images based on Clear Linux* OS</a>.</p>
+The demo source code is published on <a href="https://github.com/kenplusplus/cloud-native-demos">GitHub</a>. The software uses the <a href="https://software.intel.com/en-us/openvino-toolkit">Intel® Distribution of OpenVINO™</a> and <a href="https://hub.docker.com/u/clearlinux">container images based on Clear Linux* OS</a>.</p>
 
 <h2><br />
 Background</h2>