Portfolio — 2026

Ashish Jadhav

0
← Work

DevOps Platform · 2024

An enterprise-grade deployment automation platform leveraging containerization and AWS services for scalable web application deployment with real-time messaging and comprehensive analytics.

Role
DevOps Engineer & Full Stack Developer
Timeline
3 months
Team
Solo Project
Year
2024

Overview

ZERO | DEPLOY transforms the deployment process by providing a unified platform for containerized application deployment on AWS infrastructure. It combines the power of Docker, AWS ECS, and Apache Kafka to create a robust, scalable deployment pipeline with real-time monitoring and analytics.

The problem

Traditional deployment processes are time-consuming, error-prone, and lack real-time monitoring. Teams struggle with container orchestration, scaling decisions, and tracking deployment metrics across multiple environments.

What I built

Developed an automated deployment platform that handles containerization, orchestration, and monitoring in one seamless workflow. Integrated Kafka for real-time messaging and ClickHouse for high-performance analytics, providing instant insights into deployment health and performance.

Features

01

One-Click Deployment

Deploy applications from Git repositories with a single click

02

Container Orchestration

Automated Docker container management with AWS ECS

03

Real-time Monitoring

Live deployment status and performance metrics

04

Auto-scaling

Dynamic resource allocation based on application load

05

Analytics Dashboard

Comprehensive deployment analytics with ClickHouse

06

Log Aggregation

Centralized logging with search and filtering capabilities

Architecture

Microservices architecture with Node.js backend, Next.js frontend, and Docker containerization. AWS ECS handles container orchestration while Kafka manages real-time messaging. ClickHouse provides high-performance analytics storage and PostgreSQL manages application data.

Node.jsNext.jsDockerAWS ECSKafkaPostgreSQLClickHouseNGINX

Results

Reduced deployment time by 70%, eliminated deployment-related downtime, and provided development teams with unprecedented visibility into their application performance and deployment health.

Deployment Time
< 5 min
System Uptime
99.8%
Container Startup
< 30s
Log Processing
1M+ events/min

What I learned

  • Mastered AWS ECS and container orchestration best practices
  • Gained deep understanding of Apache Kafka for event-driven architecture
  • Learned ClickHouse for high-performance analytics and time-series data
  • Developed expertise in microservices communication patterns
  • Understanding of DevOps automation and CI/CD pipeline optimization

What's next

  • Multi-cloud deployment support
  • Advanced security scanning
  • Cost optimization recommendations
  • Integration with popular CI/CD tools
  • Machine learning-based performance predictions
Next project

Kafka Message Pipeline

Data Pipeline · 2024