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Ram Bitra
Verified Expert in Engineering
DevOps and DevSecOps Developer
Maple Shade Township, NJ, United States
Toptal member since November 27, 2024
Bio
Ram is a site reliability engineer (SRE) with over 10 years of experience in automating, deploying, and managing scalable infrastructure across cloud and on-premise environments. Skilled in CI/CD pipelines, cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes, Docker), and configuration management (Ansible, Terraform, Chef), he enhances system reliability, performance, and scalability. Ram is also experienced in monitoring tools, including Splunk, DataDog, and Dynatrace.
Portfolio
TD Bank Group
Jenkins, Spinnaker, Troubleshooting, Monitoring, Splunk, Grafana...
Elevance Health
Automation, CI/CD Pipelines, Jenkins, GitHub, Nexus, Apache Maven, Ansible...
Cox Automotive
CI/CD Pipelines, Apache Maven, Jenkins, ANTs, TFS, Docker, Kubernetes...
Experience
- Python - 8 years
- CI/CD Pipelines - 8 years
- Amazon Web Services (AWS) - 7 years
- Kubernetes - 7 years
- Crossplane - 6 years
- Terraform - 6 years
- Argo CD - 6 years
- Grafana - 6 years
Preferred Environment
Linux, Windows, PyCharm, Visual Studio Code (VS Code), Jira, Amazon Web Services (AWS), Google Cloud Platform (GCP), Azure, Argo CD, Crossplane
The most amazing...
...project I've undertaken reduced infrastructure costs by 30% and deployment time by 40%, allowing the team to roll out new features faster.
Work Experience
Senior Site Reliability Engineer
2022 - PRESENT
TD Bank Group
- Managed weekly deployments using Jenkins and Spinnaker while leveraging Splunk and Grafana for real-time monitoring and troubleshooting of Kubernetes environments.
- Designed and implemented dynamic scaling strategies across AWS, GCP, and Azure, ensuring optimal resource utilization and system performance.
- Defined and managed SLOs and automated recovery processes using Go, enhancing system resilience and minimizing downtime.
- Developed automation tools and processes to manage incidents, ensuring rapid recovery and minimizing system downtime using Dynatrace and Datadog for proactive performance monitoring.
- Deployed machine learning models using Vertex AI for predictive analytics and anomaly detection, integrating real-time data processing with Dataflow to optimize business decisions.
- Leveraged Terraform and AWS CloudFormation to automate the provisioning and management of cloud infrastructure, ensuring consistency and scalability across environments.
- Conducted in-depth analysis and optimization of system performance metrics, including CPU, memory, and network usage, to ensure efficient resource allocation and application stability.
- Integrated Crossplane and Argo CD to achieve GitOps-driven infrastructure provisioning and application deployment.
- Automated the creation of Crossplane providers, composites, and CRDs using GitOps pipelines. Used Crossplane composition revisions to version and update resources automatically whenever there was a change in the underlying definitions.
- Used Argo CD to manage Helm-based deployments and Kustomize overlays for environment-specific configurations. Developed developer self-service for infrastructure provisioning using Crossplane.
Technologies: Jenkins, Spinnaker, Troubleshooting, Monitoring, Splunk, Grafana, Amazon Web Services (AWS), Google Cloud Platform (GCP), Azure, SAP System Landscape Optimization (SLO), Go, Prometheus, Azure Monitor, New Relic, Kubernetes, WildFly, SQL, Dynatrace, Datadog, AWS Lambda, Google Cloud Dataflow, .NET, Vertex AI, Slack, IntelliJ IDEA, Visual Studio Code (VS Code), Windows, Linux, Amazon EKS, DevOps, DevSecOps, GitHub Actions, Policy as code (PaC), Security, Crossplane, Large Language Model Operations (LLMOps), APIs, Asynchronous I/O, Asyncio, Scalable Architecture, AI Voice Agents, Artificial Intelligence (AI), DSP, Large Language Models (LLMs), Scalable Platforms
Site Reliability and DevOps Engineer
2017 - 2021
Elevance Health
- Built and maintained CI/CD pipelines using Jenkins, GitHub, and Ansible to streamline deployment processes.
- Designed and deployed scalable cloud infrastructure on AWS, GCP, and Azure with Terraform and ARM templates.
- Automated data ingestion and transformation pipelines using BigQuery, Google Cloud Dataflow, and Google Cloud Functions.
- Deployed ML models using Vertex AI for predictive analytics and anomaly detection.
- Leveraged Dynatrace, Datadog, and Google Cloud Monitoring for proactive system performance management.
- Managed Kubernetes clusters for scalable and reliable application deployments.
- Implemented GitOps workflows using Argo CD to manage Kubernetes manifests and ensure continuous reconciliation of cluster state.
- Configured Crossplane to provision cloud infrastructure (AWS, GCP, Azure) as declarative YAML manifests. Automated the end-to-end lifecycle of cloud resources with a CI/CD pipeline using GitHub Actions, Jenkins, and GitLab CI to update Crossplane.
- Used Crossplane to automatically provision environments for development, QA, and production as part of a continuous delivery pipeline. Monitored Crossplane controllers and resource provisioning workflows using Argo CD dashboards and Prometheus.
- Troubleshot provider connectivity issues, failed resource creation, and drift detection errors in Crossplane using Crossplane logs and Kubernetes events.
Technologies: Automation, CI/CD Pipelines, Jenkins, GitHub, Nexus, Apache Maven, Ansible, Amazon Web Services (AWS), Google Cloud Platform (GCP), Azure, Terraform, ARM, BigQuery, Google Compute Engine (GCE), Dynatrace, Datadog, GCM, Looker, Vertex AI, Kubernetes, Docker, Python, Shell Scripting, Slack, IntelliJ IDEA, Visual Studio Code (VS Code), PyCharm, Windows, Linux, Amazon EKS, DevOps, DevSecOps, GitHub Actions, Policy as code (PaC), Security, Crossplane, Argo CD, Large Language Model Operations (LLMOps), APIs, Asynchronous I/O, Asyncio, Scalable Architecture, AI Voice Agents, Artificial Intelligence (AI), Large Language Models (LLMs), Scalable Platforms
Site Reliability and DevOps Engineer
2015 - 2017
Cox Automotive
- Designed and automated CI/CD pipelines using Jenkins, Git, Maven, and Ant for continuous integration and deployment.
- Managed containerized applications with Docker and Kubernetes, ensuring efficient scaling and high availability.
- Configured and maintained AWS and GCP resources like Amazon EC2, Amazon S3 (AWS S3), and Amazon RDS using Terraform.
- Implemented monitoring with Splunk, Dynatrace, and Datadog to track system health and automated incident response.
- Leveraged ELK (Elastic Stack) for centralized log management and real-time analysis.
- Automated server provisioning and application deployments with Ansible and Chef for streamlined operations.
- Deployed and optimized Java applications on JBoss and Apache Tomcat servers, integrating REST APIs for seamless back-end communication.
- Monitored the state of Argo CD syncs and Crossplane-managed infrastructure to ensure alignment with the desired state. Set up Argo CD and Crossplane from scratch in a production environment, enabling GitOps-driven control for Kubernetes and cloud.
- Configured Crossplane to provision cloud infrastructure (AWS, GCP, Azure) as declarative YAML manifests. Monitored sync status and health checks using Argo CD UI and Grafana dashboards.
- Used Crossplane Composition (XRDs and XRCs) to define infrastructure as blueprints, enabling on-demand provisioning of complete cloud environments.
Technologies: CI/CD Pipelines, Apache Maven, Jenkins, ANTs, TFS, Docker, Kubernetes, Amazon Web Services (AWS), Google Cloud Platform (GCP), Amazon EC2, Amazon S3 (AWS S3), Amazon RDS, Terraform, Virtual Private Cloud (VPC), Splunk, Dynatrace, Datadog, ELK (Elastic Stack), Ansible, Chef, AWS IAM, JBoss, RHEL, Slack, IntelliJ IDEA, Visual Studio Code (VS Code), PyCharm, Windows, Linux, Amazon EKS, DevOps, DevSecOps, GitHub Actions, Security, Crossplane, Argo CD, APIs, Asynchronous I/O, AI Voice Agents, Large Language Models (LLMs)
DevOps Engineer and Linux Engineer
2013 - 2015
HCL
- Developed and managed CI/CD pipelines using Jenkins, Git, and Maven, automating build, test, and deployment processes.
- Provisioned and optimized cloud resources on AWS and Azure using Terraform and AWS CloudFormation.
- Leveraged Docker for containerization and Kubernetes for orchestrating scalable, resilient infrastructure.
- Automated infrastructure configurations using Puppet and Chef, creating and maintaining cookbooks and modules.
- Implemented Nagios, Splunk, and Amazon CloudWatch for proactive monitoring, alerting, and incident management.
- Leveraged ELK (Elastic Stack) for log aggregation and performance troubleshooting.
- Implemented AWS IAM roles and security best practices, ensuring compliance and secure cloud access.
- Wrote Shell, Python, and Windows PowerShell scripts to automate operational tasks, system configurations, and cloud management.
Technologies: Jenkins, Git, Apache Maven, ANTs, Amazon Web Services (AWS), Azure, Terraform, AWS CloudFormation, Puppet, Chef, Docker, Kubernetes, OpenShift, Nagios, Splunk, Amazon CloudWatch, ELK (Elastic Stack), Shell, Python, Windows PowerShell, AWS IAM, Slack, Visual Studio Code (VS Code), PyCharm, Windows, Linux, Amazon EKS, DevOps, GitHub Actions, Security, Large Language Models (LLMs)
Experience
Site Reliability Engineering for Cloud Infrastructure at TD Bank
As a senior site reliability engineer (SRE) at TD Bank, I ensured the reliability, scalability, and performance of cloud infrastructure supporting critical banking applications. This involved automating deployments, monitoring system health, optimizing resources, and ensuring high availability across multiple cloud environments.
Cloud Infrastructure Optimization and ML Deployment for Elevance Health
This project involved leading efforts to ensure the reliability, scalability, and performance of Elevance Health's cloud infrastructure. I implemented automated CI/CD pipelines, optimized resource utilization, and deployed machine learning models to improve predictive analytics and operational efficiency.
GitOps-driven Multi-cloud Infrastructure Management with Argo CD and Crossplane
In my recent project, I implemented a GitOps-driven solution using Argo CD and Crossplane to automate and manage cloud infrastructure provisioning and Kubernetes application deployments. The project aimed to streamline infrastructure management across multiple cloud providers (AWS, GCP, Azure) while ensuring that application deployments were consistent, secure, and reproducible.
Education
2021 - 2023
Master's Degree in Computer Science
Wilmington University - Wilmington, DE, USA
Skills
Libraries/APIs
GCM, Asyncio
Tools
Terraform, PyCharm, IntelliJ IDEA, Slack, Amazon EKS, Jira, Git, Grafana, Ansible, Jenkins, Splunk, Azure Monitor, WildFly, Dynatrace, GitHub, Apache Maven, BigQuery, ANTs, TFS, ELK (Elastic Stack), Chef, AWS IAM, AWS CloudFormation, Puppet, Nagios, Amazon CloudWatch, Shell, Cloud Dataflow, Google Compute Engine (GCE), Looker, Helm, GitLab CI/CD, HashiCorp, HashiCorp Vault
Languages
Python, Bash, SQL, Go
Frameworks
Crossplane, .NET, Windows PowerShell
Paradigms
DevOps, DevSecOps, Automation
Platforms
Google Cloud Platform (GCP), Amazon Web Services (AWS), Azure, Kubernetes, Docker, Linux, Windows, Spinnaker, New Relic, AWS Lambda, Nexus, Vertex AI, Amazon EC2, JBoss, OpenShift, Visual Studio Code (VS Code)
Storage
Datadog, Amazon S3 (AWS S3)
Other
CI/CD Pipelines, GitHub Actions, Security, Argo CD, Asynchronous I/O, Scalable Architecture, AI Voice Agents, Artificial Intelligence (AI), Large Language Models (LLMs), Debugging, Troubleshooting, Prometheus, Monitoring, SAP System Landscape Optimization (SLO), Google Cloud Dataflow, Shell Scripting, Amazon RDS, Azure Resource Manager (ARM), Policy as code (PaC), Large Language Model Operations (LLMOps), APIs, DSP, Scalable Platforms, ARM, Virtual Private Cloud (VPC), RHEL, Computer Science
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