Dhruvin is a DevOps Engineer with 5+ years of experience in multi-cloud deployments and CI/CD pipeline management. He has a strong focus on automation and infrastructure as code, leveraging tools like Terraform and Kubernetes.
Implemented CI/CD pipelines using GitHub Actions, enhancing deployment efficiency.
Designed cloud architectures for AI/ML projects, ensuring robust performance.
Leveraged Terraform for infrastructure as code, enabling reproducible deployments.
Established monitoring solutions with Prometheus and Grafana for Kubernetes environments.
Managed Splunk Cloud operations, providing direct customer support and troubleshooting.
Successfully implemented multiple CI/CD pipelines, streamlining deployment processes.
Designed and deployed robust cloud architectures on GCP for AI/ML projects.
Leveraged Terraform extensively for infrastructure as code, enabling scalable deployments.
Implemented Argo Workflows on Kubernetes, enhancing workflow management efficiency.
Established comprehensive monitoring solutions using Prometheus and Grafana.
Overview: Open Metadata is an open-source data catalog platform offered as a free-trial and SaaS product with paid features. Responsibilities: Created multiple CI/CD pipelines using Github Actions for Java-based applications to smooth deployment. Developed Terraform scripts to deploy resources, including creating and managing EKS clusters and deploying Helm Charts. Implemented Argo Workflows on Kubernetes to enhance workflow management, replacing Airflow. Set up Prometheus and Grafana for monitoring EKS using various metrics.
Key outcomes:
Smoothed out the deployment process with multiple CI/CD pipelines.
Enhanced workflow management efficiency by implementing Argo workflows.
Set up comprehensive monitoring for EKS with Prometheus and Grafana.
Overview: This project aimed to develop a bi-directional machine translation solution between Turkish and English, rendering on-screen or offline output based on user preferences. Responsibilities: Created the GCP architecture and environment, including IAM roles with restricted policies. Implemented a CI/CD pipeline using Cloud Build for storing Angular code artifacts in buckets. Set up a source code repository with CI/CD to facilitate efficient developer commits. Deployed the machine translation application into a Kubernetes Cluster on GKE with CI/CD.
Key outcomes:
Developed an ideal solution for bi-directional machine translation.
Facilitated efficient developer commits through CI/CD implementation.
Successfully deployed the machine translation application on GKE.
Overview: An AI/ML project to develop a unified system for ingesting label design images and returning the closest matches based on visual requirements and user-entered metadata. Responsibilities: Set up the GCP architecture and environment, including IAM roles, AI Notebooks, and enabling Vision API and AutoML. Created cloud storage, worked with BigQuery and Datastore for data management. Used Terraform to create VM instances for Machine Learning engineers. Designed the data schema to store extracted key marker coordinates into BigQuery using a Python script.
Key outcomes:
Set up a comprehensive GCP environment for AI/ML projects.
Enabled efficient data transfer between AWS and GCP buckets.
Designed and implemented data schema for BigQuery using Python.
Overview: Managed Splunk Cloud and fulfilled client requirements as an SRE, focusing on searching, monitoring, and analyzing machine-generated data. Responsibilities: Configured various applications, added, updated, and deleted Splunk configurations. Gained hands-on experience with AWS services including EC2, S3, ELB, IAM, and VPC. Created and reviewed run-books on Confluence to streamline team processes. Utilized version control systems like Git, GitHub, and GitLab for source code management and used Nagios for infrastructure monitoring.
Key outcomes:
Managed Splunk Cloud and fulfilled diverse client requirements.
Streamlined team processes by creating and reviewing run-books on Confluence.
Gained hands-on experience with various AWS services.
Overview: Provided technical adoption assistance for Splunk deployments as part of the Admin On-Demand team, helping customers with predefined tasks. Responsibilities: Worked directly with Splunk customers to troubleshoot problems and queries. Created multiple dashboards and alerts in Splunk. Optimized Splunk queries and suggested best practices for Splunk usage.
Key outcomes:
Resolved customer problems and queries through direct interaction.
Improved monitoring capabilities by creating multiple Splunk dashboards and alerts.
Optimized Splunk queries and provided best practice recommendations to customers.
Dhruvin
Lead DevOps Engineer