Results-driven DevOps Engineer with expertise in developing and deploying microservices-based applications. Proficient in Java EE and experienced in leveraging cloud technologies such as Docker, Kubernetes, and Amazon EKS. Skilled in automating processes and monitoring systems using Splunk ITSI and Python. Well-versed in AWS services, AppDynamics, Grafana, and the ELK Stack. Certified in AZ-900, demonstrating a strong understanding of CI/CD practices through the utilization of Jenkins. Trained in infrastructure as code with Terraform.
Automated Service Onboarding in Splunk ITSI
Automated the onboarding process for services in Splunk ITSI, capturing all necessary dependencies for effective monitoring. Utilizing Python, I developed scripts that streamlined data ingestion and service integration, significantly reducing manual effort and improving overall service reliability.
Key Contributions:
Microservices Development (Proof of Concept)
Developed a proof of concept for a microservices architecture using Java EE, focusing on scalable and maintainable service design.
Key Contributions:
Developed an online quiz application using Spring Boot and React JS, successfully hosted on AWS. This project enhanced my skills in full-stack development and cloud deployment.
Trained in Agile methodologies and gained a comprehensive understanding of software development lifecycles, enabling effective collaboration and iterative project management.
Developed a Deep Convolution Neural Net for emotion recognition using facial expressions and classified emotions in 7 different classes (Neutral, Happy, Sad, Disgust, Surprise, Sad and Fear) with commendable accuracy on FER2013 dataset
Developed a NLP model on Google collaboratory using Sentiment140 dataset. Implemented hate speech detection using tensorflow and keras libraries of python.