About Me

Innovative DevOps Engineer with 6+ years of Experience in IT industry in Automation with MLOps and Software development involving cloud computing platforms like Amazon Web Services (AWS)Microsoft Azure Google Cloud Platform(GCP) . Implemented AWS Cl...forms like Amazon Web Services (AWS)Microsoft Azure Google Cloud Platform(GCP) . Implemented AWS Cloud platform and its features which includes EC2 VPC SNS RDS CloudWatch Cloud Trail Cloudfront Lambda S3 Route53 AWS Control Tower AWS Organizations AWS inspector OpenSearch RedShift AWS Application Migration Service Database Migration Service Elastic Beanstalk API Gateway WAF Shield ECS Athena AWS Backup Amazon Sagemaker Kinesis AWS Secrets Manager Worked on Azure DevOps Microsoft Entra AZURE Nginx Ingress LB My SQLVnet Azure Web App Azure Load Balancer Azure Network Watcher Azure Storage Key Vault. Traffic manager Azure Functions Azure Container Registry AKS Azure Dedicated Host Azure VM Scale SetsAzure Bastion Azure DNS Azure Front Door DDoS Protection Azure Monitor CDN Azure Scheduler Building Scalable XGBoost models in Databricks with Mlflow and Implemented PySpark Pipelines for Data Processing Building Image Classification models Use SageMaker to preprocess and augment image data and build a convolutional neural network (CNN) using a deep learning framework TensorFlow. Building Scalable and Deep Learning and Large Language Model Projects using MLFlow with Databricks Trained Leverage SageMakers distributed training capabilities to efficiently train the image classification model on a large dataset and deployed the trained model as an endpoint allowing real-time predictions on new images. Using generative AI models by automating the MLOps training and deployment process to accelerate the innovation process and improve performance and AutomatML model retraining and deployment with MLflow in Databricks Implemented MLflow API Gateway feature for managing LLMs at their configurations at one single place Deep working knowledge with Machine learning libraries and frameworks (scikit-learn keras tensorflow etc).AWS-Sagemaker. Knowledge on python data manipulation for loading and extraction as well as with python libraries such as NumPy SciPy and Pandas for data analysis and numerical computations. Written Python boto3 Script with AWS Lambda function to stop running instances on weekends. Extensively worked ON JENKINS and Team city for continuous integration and for the end to end automation for all build and deployments including setting up pipeline jobs and upstream/downstream job configurations in Jenkins Good Knowledge onAzure Active Directory and RBAC.Automate cloud-based deployments using Azure DevOps Assigning the Azure services on locations specific to integrate with web apps and key-vaults Experience in designing a Terraform and deploying it in cloud deployment manager to spin up resources like cloud virtual networks GKE clusters create service accounts STORAGE FIREWALL SETUP COMPUTE Engines in public and private subnets along with Auto scaler in Google Cloud Platform. Implemented ARC42 Documentation for project strategy Involved scrum ceremonies (grooming sprint planning retrospectives daily stand-ups Experienced Atlassian products like JIRA CONFLUENCE Bitbucket Create clusters in Google Cloud and manage the clusters using Kubernetes(k8s). Using Jenkins to deploy code to Google Cloud create new namespaces creating docker images and pushing them to the container registry of Google Cloud. Expertise in creating Kubernetes clusters with terraform templates and deploying them in AWS environment and monitoring the health of pods using Helm Charts. Expertise in setting up Kubernetes (k8s) clusters for running microservices and pushed microservices into production with Kubernetes backed Infrastructure. Development of automation of Kubernetes clusters via playbooks in Ansible. Experience in keeping up and looking at app logs resource metrics log archives using monitoring tools CloudWatch EFK Stack PrometheusGrafana Grfana loki Can manage AWS cost cutting by writing the Ansible playbook for auto start/stop of AWS resources at time of the day by triggering it from Jenkins. Managing 24x7 support for clients on AWS Cloud across various regions