Bunnyshell Project

• Streamlined development, testing, and staging environments during the Bunnyshell Hackathon.
• Recognized and addressed issues related to fragmented environments causing delays in development and testing.
• Provisioned resources and established networking to create consistent frontend and backend development environments.
• Utilized Bunnyshell's Environment as a Service platform to deploy Terraform infrastructure, ensuring code-defined environments for consistency and repeatability.
• Leveraged Bunnyshell's automation capabilities to reduce manual effort and minimize human errors in environment setup.
• Enabled parallel development of frontend and backend components by setting up separate developer environments.
• Facilitated collaboration and testing by allowing developers to experiment with code changes in controlled environments.
• Improved infrastructure deployment efficiency and ensured a more controlled deployment process.

Online Safety App

• Identified the need to optimize deployment procedures for frontend and backend components.
• Integrated CircleCI into the workflow to automate deployment tasks, resulting in increased efficiency and reliability.
• Defined and implemented the "deploy-infrastructure" job using AWS CloudFormation templates.
• Ensured consistent and reproducible infrastructure deployments, addressing previous inconsistencies.
• Developed the "destroy-environment" job to handle rollbacks in case of deployment failures.
• Implemented a robust rollback mechanism, maintaining a clean environment upon errors.
• Orchestrated automation of the entire CI/CD process using CircleCI.
• Ensured code commits triggered builds, testing, and deployments to the designated environment, promoting agility.
• Introduced the "acceptance-test" job to facilitate quick feedback.
• Conducted smoke tests on the frontend site's title to verify basic functionality, enhancing reliability.

Autodeploy

• Implemented comprehensive unit tests for both frontend and backend components, providing early feedback on code correctness and proactively identifying and resolving issues.
• Enhanced team collaboration and issue resolution by integrating CircleCI with communication tools such as Slack and email for immediate alerts on job failures.
• Automated cloud infrastructure provisioning using CloudFormation and Ansible, ensuring consistent and error-free setup of CloudFront distributions and storage buckets.
• Implemented smoke tests as a critical component of the pipeline, validating essential functionality to ensure deployed applications were operational and responsive.
• Established rollback and cleanup phases within the pipeline to minimize downtime and potential customer impact in the event of deployment failures or issues.
• Integrated Prometheus for server monitoring, enabling proactive error diagnosis and resolution to reduce system downtime and enhance system reliability.

Iglumtech Site Migration

• Successfully migrated the website from Google Cloud Platform to an AWS S3 bucket, leveraging Amazon Web Services to enhance scalability, performance, and cost-efficiency.
• Implemented Amazon CloudFront as a Content Delivery Network (CDN) to optimize content delivery, boost site performance, and reduce latency for users across diverse geographical locations.
• Enhanced website security by deploying an AWS-signed certificate, enabling secure HTTPS connections and providing users with top-tier cloud security features.

Sought to fortify Azure-based systems, protect sensitive data, and ensure compliance. As a core team member, I contributed by applying Azure cloud security best practices.

• Configured IAM policies to enforce least privilege access.
• Implemented conditional access and multi-factor authentication (MFA) for enhanced security.
• Integrated secure key management for data encryption at rest and in transit.
• Collaborated on encryption mechanisms to safeguard sensitive data.
• Designed network infrastructure based on the Zero Trust model.
• Proposed and implemented firewalls, Azure Bastion, and Just in Time access to minimize exposure to threats.

Transforming a machine learning model into a production-ready microservice to handle API requests, automate Kubernetes deployment, and ensure continuous integration.

• Conducted comprehensive testing of project code using hadolint linting tool.
• Developed and completed the Dockerfile to containerize the machine learning application.
• Enabled the microservice to provide housing price predictions via API calls.
• Enhanced log statements within the source code to improve visibility into application behavior and performance.

Developed and deployed a serverless "TODO" application using AWS Lambda and the Serverless framework.

• Implemented core functionality for creating, updating, deleting, and fetching TODO items.
• Enabled users to upload attachments with pre-signed URLs for secure file uploads.
• Created an efficient DynamoDB table for storing TODO items using a composite key.
• Structured the codebase into layers (Business Logic, Data Layer, File Storage) following the separation of concerns principle.

Developed and deployed the "Neighborly" web application, utilizing Python Flask for seamless neighbor connectivity through service and product advertisements.

• Streamlined deployment using Azure services, including Azure Function App, Cosmos DB, Azure Registry, Kubernetes, Event Hubs, and Logic App.
• Created an Azure Registry and Dockerized the Azure Functions for streamlined deployment.
• Developed a Logic App that monitored HTTP triggers and initiated email notifications in response.
• Established an Event Hub namespace for effective event stream management.