My toolbox of handy (and occassionally rebellious) tools.

Though most of these are reliable, they sometimes surprise me with quirky errors or unexpected behavior. These are the moments when technology tests me—and I skillfully bring it back in line.

AI Tools

  • GitHub Copilot

    100 developers waiting to build your next BIG idea! How cool is that!

IDEs

  • VS Code

    VS Code receives a lot of attention from Microsoft in terms of updates and ecosystem support. When paired with GitHub Copilot, it truly feels like a next-generation development environment. I particularly enjoy using VS Code for front-end development.

  • Visual Studio 2022

    One of Microsoft's long-standing IDEs. In my experience, it is particularly well suited for developing backend services with .NET.

Databases

  • MongoDB

    MongoDB was my gateway into the NOSQL universe, where I first explored flexible, document-based data.

  • Opensearch

    OpenSearch is an extremely fast distributed search and analytics system that handles NoSQL-style document data. I have worked with OpenSearch dashboards, which is based on Kibana.

  • PostgreSQL

    Postgres is the modern RDBMS I prefer to work with, combining reliability with the features I need.

  • MSSQL

    In 2005, MS SQL was the very first database I ever worked with, where I was introduced into the world of relational databases.

  • Redis

    Redis is my preferred caching database. I have used tools like Redis Insight and RedisDesktopManager to explore and manage my data effectively.

  • Snowflake

    I have used Snowflake as a cloud database platform. I understand how Snowflake supports downstream analytics via business intelligence tools.

  • Oracle

    Oracle is one of the best databases I've worked with for handling extremely complex business logic, especially through its robust stored procedures. I have worked with Oracle, including writing stored procedures, though not at the highest complexity. PL/SQL Developer is the IDE that helped me work with Oracle database.

API Testing tools

  • Postman

    In my experience, Postman's rich and intuitive feature set keeps me coming back to it, even after experimenting with other API testing tools.

Cloud

  • AWS

    I use AWS across a wide range of use cases, including frontend hosting, backend services, and database management. Recently, I have been exploring agentic AI use cases with Amazon Bedrock.

  • Firebase

    I use Firebase for hosting the websites I build.

Containerization

  • Docker Desktop

    Creating learning environments in Windows 11 for new technologies is a lot easier with Docker Desktop.

  • Docker / CentOS 7

    Spin up Docker containers—whether it's .NET Core, PostgreSQL, or any service you need with simple docker commands.

Design

  • Figma

    I use Figma to bring my ideas to life through intuitive UI designs and prototypes. When I need to communicate ideas on the fly, I sketch diagrams right in Figma to share with stakeholders.

Source Control

  • Bitbucket

    Bitbucket is a good choice if you are using the Atlassian ecosystem like Jira

  • GitHub

    I love using GitHub to manage my Git repositories

CI/CD

  • Bamboo

    Bamboo helps with the automation of building the source code, running unit tests, and keep everything else ready for deployment.

  • Octopus

    Octopus takes the binaries from Bamboo and deploys them to various environments including variable substitution, configuration transforms, and other deployment tasks.

Monitoring

  • Splunk

    Using Splunk Processing Languafe (SPL) to understand the logs and metrics from our applications.

  • New Relic

    Helps you track throughput, error rates and slow queries—essentially any bottlenecks in your application.