Gandikota Dineshkumar

Results-driven DevOps & Cloud Security Engineer with 3.4+ years of experience building secure, highly available CI/CD pipelines and cloud infrastructure. Improved deployment success rates from 85% to 99.5% and reduced release times by 67% (30 minutes to under 10 minutes). 3.4+ years of hands-on Kubernetes experience in production across Azure Kubernetes Service (AKS) and Amazon EKS. Strong hands-on expertise in Microsoft Azure and AWS.

Experienced in Terraform with custom modules and cloud security hardening using Azure Key Vault, RBAC, and AWS IAM.

Oracle Cloud

DevOps & AI Foundations certified.

Azure DevOps Engineer at Acadhub EduTech Pvt Ltd (2025-12 – 2026-06)

Educational Platform | Cloud-Native Microservices on Azure + Kubernetes

• Lifted deployment success rate from 85% to 99.5% by redesigning CI/CD pipelines with automated rollback strategies in Kubernetes, significantly reducing release failures and improving platform stability.
• Engineered end-to-end Azure DevOps YAML pipelines for microservices, reducing average release cycle from 30+ minutes to under 10 minutes.
• Secured CI/CD pipelines and application secrets by integrating Azure Key Vault, eliminating hardcoded credentials and improving secret management across services.
• Deployed and managed Kubernetes clusters (staging & production) using Helm charts with rolling updates, HPA, ConfigMaps, and zero-downtime release strategies.
• Resolved critical Kubernetes production incidents, including CrashLoopBackOff, ImagePullBackOff, and Ingress failures, using kubectl diagnostics reducing log analysis, and root-cause troubleshooting to restore application availability.
• Implemented GitHub Actions workflows to automate build/deploy pipelines, cutting manual release effort by 60%.
• Integrated SonarQube and Trivy into Azure DevOps pipelines for automated code quality checks and container vulnerability scanning prior to deployment.
• Integrated Azure Active Directory (Azure AD) with RBAC for fine-grained access control across dev, staging, and production environments.
• Migrated domain from GoDaddy to Amazon Route 53, managing subdomain routing and DNS cutover with under 5 minutes of downtime.
• Configured Azure Monitor and Application Insights dashboards enabling proactive alerting and 99.9% platform uptime.
• Developed an AI-powered DevOps Assistant using FastAPI and LLM APIs to analyze Dockerfiles and generate security, optimization, and best-practice recommendations.
• Integrated Large Language Models using REST APIs to automate Dockerfile reviews and infrastructure guidance.

DevOps Engineer at DLV Software Pvt Ltd (2022-06 – 2025-03)

Insurance Claims & Policy Microservices Platform | AWS + Azure + Kubernetes

• Containerized 4 core microservices (policy, claims, payment, underwriting) using Docker multi-stage builds; cut image sizes by 35% through Alpine/slim base optimization.
• Built and maintained declarative Jenkins CI/CD pipelines automating build, test, container image creation, and deployment workflows, integrating Amazon ECR and Amazon EKS for automated image publishing and Kubernetes application rollouts, significantly reducing manual deployment effort.
• Integrated SonarQube and Trivy into Jenkins pipelines for automated code quality analysis and container image vulnerability scanning.
• Deployed microservices on Kubernetes via Helm charts; implemented rolling updates, health checks, and automated rollbacks to maintain 99%+ uptime.
• Troubleshot Kubernetes issues including CrashLoopBackOff, ImagePullBackOff, pod scheduling failures, service/DNS connectivity, and resource constraints using kubectl, logs, events, and Helm.
• Automated AWS and Azure infrastructure provisioning using Terraform and CloudFormation, enabling repeatable, secure multi-environment deployments in under 20 minutes.
• Implemented application and infrastructure monitoring with Prometheus, Grafana, and ELK Stack, creating dashboards and alerting rules to improve observability and accelerate incident response.
• Implemented Docker Compose to standardize and automate multi-container local development environments, enabling reproducible configurations and streamlining developer workflows.
• Automated repetitive operational tasks with Bash, Python, and Shell scripts and improving efficiency and reducing manual effort across routine infrastructure and deployment activities.

B.Tech – R.G.M College of Engineering & Technology