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Experienced AWS Cloud Engineer adept at crafting, deploying, and managing AWS infrastructures. Skilled in EC2, S3, RDS, Lambda, automation, and DevOps methodologies.
Machine learning and data science engineering
I successfully migrated SVN branches to AWS CodeCommit, built applications including Skyrelo, Outlook plugin, and Onboarding, generating WAR files and artifacts stored in S3. Utilizing an appspech.yaml and buildspech, I orchestrated deployments via AWS Deploy, employing both in-place and blue-green strategies. Additionally, I engineered an AWS CodePipeline for CI/CD, integrating stages for post-deployment tasks, such as invoking Lambda functions to halt services like Tomcat, and capturing the latest green environment server as an AMI, ensuring seamless success.
I successfully deployed the Docker image to AWS ECR and subsequently launched the microservice application on EKS using AWS Fargate. I created the deployment.yaml, PV, and PVC files, and established EFS for persistent data storage. Additionally, I configured a service for ALB ingress to facilitate external access
AWS Redshift- Glue & Quick-sight, 11/2023, 12/2023, The project involves studying Apache logs stored in Amazon S3. To process the data, I utilized AWS Glue to crawl and transform the data, sending it to Amazon Redshift. Subsequently, I created a QuickSight dashboard for visualisation and reporting.
Aws EMR and PowerBI Dashboard, 01/2023, 01/2023, Successfully Delivered project in which AWS services like EMR, EC2, S3, LAMBDA, RDS, VPC, VPN included apart from it 3rd party tools MYSQL and Microsoft PowerBI is included.
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