Muhammad Awad

I worked with Afcon to establish a SAAS and DATA product in Azure. It was necessary at the beginning to understand Afcon's KPIs and requirements. The existing product that they decided to expand to the cloud was software that Afcon's customers installed on their customer's sites. It received information from the sensors in many places on the site and saved it to the SQL server.

My main task was to build the infrastructure in Azure (first in a batch process), transfer all the data that sits in the sites inside the servers, manipulate it, and transfer it in ETL processes using ADF to the data store (Azure Synapse). The algorithm installed in the cloud enabled them to make decisions regarding the work of the censors, thus saving electricity and energy costs and giving a snapshot of the capacity within the clients' sites. It was also necessary to transfer all development from TFS to Azure DevOps and build the SAAS on top of Kubernetes.

As a result of my work, they built these products in the cloud and recruited many more customers interested in their new forms.

This project involved creating an automation app for running test cases from validation teams. These teams used my automation infrastructure for running test suites against Intel's 3D IVCAM. This infrastructure creates test environments in the lab and connects test outputs and camera metrics to TFS pipelines before release. It also runs integration, E2E, and load tests on IVCAM.

Intel had a requirement to develop a SAAS product that would enable their customers to manage and observe Intel products and to build and manage high-performance storage and compute clusters. The client required to turn their demo environment into a production environment and create QA and development environments for the SAAS product.

I built the architecture, designed documents, methods, and goals, and presented them to Intel. After receiving the approval from the client, I started implementing the plan. In the beginning, all the infrastructure of the new architecture had to be built by CDK, and this is only considered a POC. The POC included building EKS, API Gateway, AWS Cognito, Lambda, Amazon Aurora RDS, and more. I moved to the phase of building the architecture in production, which was highly available, DR, and fault tolerant. I built all the CI/CD processes, including a production environment and QA and development environments, using GitHub Actions and GitLab pipelines. Cortex also had to be built to withstand many clients, and Kubernetes would be scalable.