YOGESH n p

DevOps Engineer | Terraform | Amazon Web Services | Kubernetes | Linux | Docker | Prometheus & Grafana | OpenSource Enthusiast

"Throughout my career, I have consistently driven excellence and innovation in key areas, delivering impactful solutions to enhance performance, scalability, and efficiency."

Improved Efficiency

Enhancing Efficiency Through Automation Python

  • Automated lifecycle policies for S3 buckets using Python, optimizing storage costs by moving data to Glacier or deleting obsolete objects.

  • Created reusable Terraform modules for scalable infrastructure, boosting team efficiency by 35%.

  • Streamlined CI/CD workflows with Jenkins, GitHub Actions, and ArgoCD, optimizing deployment processes.

Faster Delivery

Enhanced faster workflow in event-driven architectures by deploying Lambda functions

  • Implemented automated pipelines for testing and deploying ReactJS applications.

  • Streamlined continuous deployment workflows using ArgoCD, enabling automated and efficient delivery of applications to K8's environments.

  • Designed Python scripts to schedule and manage backups for DynamoDB tables, ensuring data integrity and availability.

Reliability

System Reliability with Proactive Monitoring and Automation using Prometheus, Grafana and CloudWatch

  • Configured Prometheus and Grafana for real-time monitoring of infrastructure and application metrics, ensuring uptime and reliability.

  • Automated the setup of CloudWatch alarms using Python to enable real-time monitoring and proactive issue detection.

  • Configured alarms for DynamoDB, tracking metrics such as read/write capacity utilization, throttled requests, and latency to ensure optimal performance and availability while preventing overprovisioning or underprovisioning of resources.

Scalability

Ensuring Scalable Operations

  • Secured DevOps tools credentials by automating their Management and Encryption in AWS Secrets Manager using Terraform scripts

  • Configured SSL using AWS ACM

  • Deployed containerized applications seamlessly using Kubernetes and automated continuous deployments with ArgoCD

  • Managed DNS using Ingress

  • Provisioned DynamoDB tables using Terraform

  • Automated IAM user management with Terraform

Cost Optimization

Achieving Cost Optimization through Automation and Resource Management

  • Configured GitHub Actions and Jenkins Pipelines to automate deployments, reducing the need for CodeDeploy and CodeCommit resulting in cost savings.

  • Implemented Batch writes and compressed large API responses to minimize throughput and storage costs for DynamoDB with Large Data Dumps

  • Reduced monitoring tool costs by migrating from Splunk to Grafana and Prometheus, optimizing resource allocation