Sridhar Reddy

Sridhar Reddy

Cloud/Dev Ops Engineer @ Fannie Mae

About Sridhar Reddy

Sridhar Reddy is a Cloud/DevOps Engineer at Fannie Mae with extensive experience in cloud automation, CI/CD, and infrastructure management.

Current Position at Fannie Mae

Sridhar Reddy is currently working as a Cloud/DevOps Engineer at Fannie Mae in Reston, Virginia. His work involves implementing cloud automation solutions using AWS. He is skilled in deploying Docker images with Ansible Tower onto Docker Swarm, and utilizes various logging and monitoring tools such as ELK, Dynatrace, Splunk, Monit, and Tivoli.

Previous Experience at Anthem, Inc.

From 2018 to 2020, Sridhar Reddy served as an AWS/DevOps Engineer at Anthem, Inc. in Richmond, Virginia. During his tenure, he contributed significantly to the cloud infrastructure and DevOps operations, enhancing the deployment processes and implementing efficient cloud solutions.

Educational Background

Sridhar Reddy holds a Master’s degree in Computer Science from Texas A&M University-Kingsville, obtained between 2015 and 2016. Prior to that, he earned a Bachelor of Engineering in Electrical, Electronics, and Communications Engineering from Hindustan University, completed from 2008 to 2012.

Certifications and Technical Skills

Sridhar Reddy is equipped with AWS Certified Developer and Certified Solutions Architect certifications. His technical expertise extends to managing cloud infrastructure using AWS, version control systems like GitHub, SVN, and BitBucket, and using tools like Jenkins and Bamboo for CI/CD pipelines. Additionally, he has experience with virtualization and cloud infrastructure management through VMware.

Professional Experience and Tools

Throughout his career, Sridhar Reddy has utilized an array of professional tools and platforms. He has collaborated using Confluence and Slack, managed change and incident processes with ServiceNow, and handled data center management and networking. He gained hands-on experience with Docker, integrating with systems for effective deployment and monitoring.

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