About Yash Mishra
Yash Mishra is studying for a Masters in Computer Science at Clemson University. Yash is a member of Dr Amy Apon's research team which carries out research on Big Data systems, focusing on optimizations and improvements at both the data and network layers. Yash was introduced to HPCC Systems as a result of attending the Cloud Computing Architecture class at Clemson University.
Deployment of HPCC Systems to commercial clouds can be done in multiple ways depending on various business needs. While lift-and-shift is one way to go which involves moving of unchanged application infrastructure from on-prem to the cloud based on virtual machine approach, containerization of the application with the aim to go cloud-native is another approach. The recent push of HPCC Systems to go cloud-native involves containerization strategy which provides a logical packaging mechanism in which HPCC resources are abstracted from the environment in which they run, with multiple containers running on top of the OS kernel directly.
This project leverages the new Kubernetes version of HPCC Systems for the cloud by targeting Microsoft Azure and provides steps to provision and deploy custom HPCC Systems cluster using Kubernetes and helm charts, based on the initial guidance on setting up a containerized version of HPCC Systems in Azure . Examining architectural differences between Kubernetes and Virtual Machine environments for HPCC Systems, evaluating performance of running jobs in the Kubernetes environment with multiple cloud configuration options and performing cost analysis to deploy containerized HPCC Systems are also an added effort in this project to understand how HPCC runs on the cloud and to identify existing or potential challenges along with potential solutions. With containerizing applications, the underlying storage also changes, and it becomes important to assess how HPCC handles storage and persists data in the Kubernetes environment . To achieve this, two storage options in Azure are examined along with tradeoffs and challenges with each option. The outcome of this project would also provide developers and users of HPCC Systems as an added building-block to leverage the cloud-native approach for faster deployment and a clean separation of concerns.
 Setting up a Default HPCC Systems Cluster on Microsoft Azure Cloud Using HPCC Systems 7.8.x and Kubernetes, Jake Smith | HPCC Systems. https://hpccsystems.com/blog/default-azure-setup.
 Persisting Data in an HPCC Systems Cloud Native Environment, Gavin Halliday | HPCC Systems. https://hpccsystems.com/blog/persisting-data-cloud.
In this Video Recording, Yash provides a tour and explanation of his poster content. ADD WHEN AVAILABLE
Poster Title: Using HPCC Systems GNN Bundle with TensorFlow to Train a Model to Find Known Faces Leveraging the Robotics API
Click on the poster for a larger image. The original PDF version can be found here. (Available for download). ADD WHEN AVAILABLE