Projects
Apache Server Deployment Via CloudFormation
Deployed a web application on an
Apache web server running on EC2 instances via the AWS CloudFormation IaC model.
Servers are deployed in auto-scaling groups to ensure service availability as well
as cost optimization.
Deployed a web application on an Apache
web server running on EC2 instances via the AWS CloudFormation IaC model. Servers
are deployed in auto-scaling groups to ensure service availability as well as cost
optimization. A design pattern that ensures internet traffic aiming for the VPC hits
the Internet Gateway and is further load-balanced by the Application Load Balancer
to ensure the even distribution of the traffic on the Servers via the Public Subnet
and the use of NAT for address translation. While a Route Table is used to enforce
the routing of specific traffic within the network and the Servers in the
auto-scaling group as desired, additionally, Listeners are configured for health
checks and load balancing.
Employer App CI/CD Deployment
Using the Blue-Green deployment
strategy here, I have developed
a complete CI/CD pipeline to operationalize and monitor a robust
TypeScript-developed
Employee/Employer Management app. The pipeline uses CircleCi to build, test, and
scan the frontend
and backend of the app.
Using the Blue-Green deployment strategy here,
I have developed
a complete CI/CD pipeline to operationalize and monitor a robust
TypeScript-developed
Employee/Employer Management app. The pipeline uses CircleCi to build, test, and
scan the frontend
and backend of the app. The infrastructure is further deployed using AWS
CloudFormation and
configured using Ansible. A migration is run with its test results sent to kvdb. The
frontend and backend are further deployed to the provisioned infrastructure, a smoke
test is
performed, and old infrastructure gets cleaned up after the CloudFront is updated.
Prometheus is also used for centralized server error logging, with the Alert Manager
configured to send email alerts when a server goes down.
Machine Learning Housing App Orchestration
In this project, I
used a pre-trained, sklearn model that has been trained to predict housing prices in
Boston according to several features, such as average rooms in a home and data about
highway access, teacher-to-pupil ratios, and so on.
In this project, I used a pre-trained,
sklearn model that has been trained to predict housing prices in Boston according to
several features, such as average rooms in a home and data about highway access,
teacher-to-pupil ratios, and so on. The aim of this project, however, is to
operationalize the Python flask app by means of containerization with Docker and
further orchestrated on Kubernetes, such that GitOps best practices are used to
continuously lint, test, and deliver code alongside its infrastructure
specifications using CircleCi. Furthermore, this project could be extended to any
pre-trained machine learning model, such as those for image recognition and data
labeling.
Azure DevOps & Terraform Weather API Deployment
For this project, the
Azure DevOps suite was used to build a containerized Weather API application
developed in .Net Core 3.1 and deployed to Azure using Terraform.
For this project, the Azure DevOps suite was
used to build a containerized Weather API application developed in .Net Core 3.1 and
deployed to Azure using Terraform. Service Connections were added to Docker Hub and
the Azure Resource Manager using Azure DevOps, and Azure Pipeline was configured to
watch GitHub as SCM and pull images from the hub for successive deployments.
Automated Kubernetes Web App Deployment
This project involved
automating the containerization and image deployment of a .Net web app that presents
a simple landing page to the Azure Container Registry for deployments to Azure
Kubernetes service.
This project involved automating the
containerization and image deployment of a .Net web app that presents a simple
landing page to the Azure Container Registry for deployments to Azure Kubernetes
service. The Azure DevOps Pipeline was used for build and deploy operations, and the
"Replace Tokens" marketplace extension was used as a task in the Azure pipelines to
automate the number of replicas in the Kubernetes deployment.yml file when specified
in the azure-pipelines.yml file.
Publications
Terraform Resource Provisioning Actions
In very easy steps, we demonstrated deploying a Resource Group alongside a Windows Server 2016, a VNET, a Subnet, NIC, and a Public IP resource; all of which were deployed into the Resource Group. Our overall aim in all of its simplicity is diagrammatically captured below.
Read MoreBackup and Restore Azure API Management service
Production resources may get deleted in error and most times even when they are restored, their previous configurations may not be completely regained. Here, I simplified the PowerShell scripts for backing up and restoring of an Azure API Management Service.
Read MoreThe Fundermentals and benefits of CI/CD
In a bid to achieve build and deploy automation for cloud-based software products, I have made a presentation to surface the fundamentals and benefits of CI/CD in every software development lifecycle.
Read More