🌐 Site Reliability Engineer with over 3 years of experience in designing and optimizing reliable, scalable, and cost-efficient cloud systems. I specialize in enhancing CI/CD pipelines, minimizing downtime, and implementing Infrastructure as Code (IaC) solutions. My expertise spans Docker, AWS, Kubernetes, and Terraform, with a proven track record of automating processes to improve operational efficiency and system reliability.

🛠️ I have successfully architected and managed high-availability, fault-tolerant cloud infrastructures, primarily on AWS. I’ve implemented Terraform for cloud resource provisioning, enabling scalable and efficient management across various engineering teams. My focus on Automation and Best Practices ensures that complex systems operate with minimal manual intervention, enhancing both reliability and performance.

📈 As a strong advocate for DevOps and GitOps principles, I’ve utilized ArgoCD to enable continuous deployment workflows and automated monitoring using tools like Prometheus, Grafana, and Datadog. I’m also experienced in enhancing system observability through centralized logging and proactive monitoring to ensure that systems meet SLA requirements and operational targets.

🚀 In my previous roles at Ineuron.ai and alpha.ai, I led the migration from legacy infrastructure to cloud-native solutions, improving resource utilization, cost efficiency, and deployment speed. I also contributed to the optimization of MLOps workflows, facilitating seamless and automated ML model deployments using AWS EKS, Helm, and GitHub Actions.

💬 I believe in a collaborative approach to solving complex problems and have mentored cross-functional teams to drive operational excellence. With my focus on automation and continuous improvement, I am passionate about creating systems that are both reliable and efficient.