Ramit Bansal
DevOps Engineer | Terraform | Kubernetes | AWS
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Item 4: AI-Powered DevOps Support Automation
Project Title: AI-Assisted Incident Triage and Support Automation Platform
Role: DevOps / AI Engineering / Automation Engineer
Description
Overview Built an AI-powered internal platform to automate incident triage, accelerate root-cause analysis, and improve support response time for complex infrastructure and application issues.
The Challenge Support engineers were spending too much time manually reviewing logs, support bundles, and system health data across multiple services before they could identify the issue.
The Solution
Developed an automation workflow using Python and AI models to analyze logs, support bundles, and error patterns.
Connected the system with monitoring, incident data, and knowledge base content to suggest likely causes and next steps.
Containerized the application and deployed it through a CI/CD pipeline for repeatable releases.
Added secure secret management, scheduled jobs, and observability for production readiness.
The Results
Reduced manual triage effort and faster issue identification.
Improved support efficiency and consistency in troubleshooting.
Enabled quicker response to infrastructure incidents through automation.
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Item 3: Terraform Enterprise Platform Modernization
Project Title: Terraform Enterprise Platform Migration & Operations Automation
Role: DevOps / Platform Engineer
Description
Overview Designed and executed a full Terraform Enterprise platform modernization initiative to improve reliability, scalability, and operational control for enterprise infrastructure teams.
The Challenge The existing Terraform Enterprise environment had inconsistent deployment patterns, slow recovery during failures, and limited automation around upgrades, backups, and support operations.
The Solution
Automated Terraform Enterprise deployment and lifecycle operations across containerized and cloud-native environments.
Standardized environment setup using Terraform, Kubernetes, Helm, and Vault for secure infrastructure provisioning.
Implemented backup, restore, upgrade, and health-check workflows to reduce manual intervention.
Added observability using centralized logging, metrics, and alerting to detect issues early.
The Results
Reduced platform maintenance effort significantly.
Improved recovery time during incidents and upgrades.
Increased reliability and consistency across environments.
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tem 2: Enterprise CI/CD Pipeline Automation
Project Title: End-to-End AWS Automation via GitHub Actions
Role: DevOps / CI/CD Engineer
Description
Overview
Architected and implemented a secure, automated end-to-end CI/CD pipeline to accelerate feature delivery and ensure total Infrastructure as Code (IaC) consistency for AWS cloud native applications.
The Challenge
Deployment workflows were highly fragmented and heavily reliant on manual validation steps. This friction delayed critical AWS infrastructure changes, creating a massive delivery backlog.
The Solution
Built a fully automated containerization pipeline utilizing Docker for build isolation.
Integrated automated unit/integration testing alongside SAST & DAST security scanning directly into the workflow runner.
Leveraged GitHub Actions to automatically test, validate, and deploy verified Terraform manifests straight to AWS, backed by real-time logging via AWS CloudWatch.
The Results
Slashed AWS infrastructure deployment times from several days to under 30 minutes.
Achieved 100% IaC consistency, completely removing manual hotfixes in production.
Shifted security left by catching vulnerabilities before they reached staging environments.
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Item 1: Multi-Region Kubernetes Deployment Automation
Project Title: Multi-Region Kubernetes Deployment & IaC Automation
Role: DevOps / Cloud Infrastructure Engineer
Description
Overview
Designed and deployed a highly available, multi-region Kubernetes infrastructure across AWS (EKS) and Azure (AKS) using an Infrastructure as Code (IaC) methodology to eliminate manual configuration errors and deployment bottlenecks.
The Challenge
The client was struggling with a manual, error-prone deployment process for their multi-region clusters. Configuration drift across AWS and Azure environments was causing unpredictable downtime and hindering engineering velocity.
The Solution
Developed a unified IaC framework utilizing Terraform Enterprise to provision networking (VPCs/VNs), databases (RDS), and security groups consistently.
Implemented ArgoCD to handle declarative GitOps deployments, enabling seamless blue/green deployment strategies.
Established robust cross-region replication to guarantee data persistence and high availability.
The Results
85% reduction in total environment deployment time.
Achieved 99.99% infrastructure uptime by eliminating configuration drift.
Standardized cloud configurations across multiple cloud vendors
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