Sai Kamal
Open to work0 years experienceDevOps Engineer
DevOps Engineer | Cloud & Platform Engineering
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Skills & Technologies
25 skillsWork Experience
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Projects
DevOps Monitoring & Alerting Stack (Homelab)
- Designed and deployed a multi-tier observability stack using Prometheus, Grafana, and Alertmanager for a Dockerized frontend – backend–PostgreSQL application.
- Instrumented infrastructure and database metrics collection using Node Exporter and postgres_exporter for full -stack visibility.
- Wrote PromQL-based alert rules with tiered warning/critical thresholds and configured Alertmanager to group and route alerts by service and severity to Slack — cutting dozens of individual notifications down to one grouped alert per incident.
- Built Grafana dashboards for infrastructure, database, and application health, and documented the architecture and alert -routing strategy for reproducibility.
Terraform Automation — Secure Container Deployment on AWS
- Designed and provisioned end-to-end AWS infrastructure as code using Terraform — including ECR, ECS Fargate, ALB, VPC, CloudWatch, and IAM — eliminating manual provisioning in favor of reproducible, version-controlled environments.
- Engineered a secure, multi-tier VPC architecture with public/private subnets, NAT Gateway, and security groups to enforce network segmentation and least-privilege access for containerized workloads.
- Automated Docker image build-and-push workflows to Amazon ECR via Git-triggered pipelines, establishing a consistent container lifecycle management process across development and production.
- Integrated AWS CloudWatch for real-time monitoring and alerting, and implemented rollback strategies and HA configurations to support zero-downtime deployments.
DevSecOps Implementation — Secure CI/CD Pipeline for Netflix Clone
- Built a CI/CD pipeline with security gates enforced before every deployment — integrating SonarQube static analysis and Trivy container scanning to block vulnerable builds from reaching production.
- Containerized the application and orchestrated deployment on AWS EKS using Kubernetes, ArgoCD (GitOps), and an Ingress Controller, cutting deployment cycle time by 10%.
- Set up a full observability layer (Prometheus, Grafana, Alertmanager, ELK) to track deployment health and reduce MTTR by 25%.
- Stored application credentials using Kubernetes Secrets and implemented a manual rotation process — updating Secret resources and reloading pods to apply new credential values; enforced least-privilege access via AWS IAM policies and Kubernetes RBAC.
- Automated recurring operational tasks using Bash scripting and Linux administration to reduce manual intervention.
Leaderboard Standings
Leaderboard Position Pending
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Assessment Highlights
Assessments Not Completed
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AI Collaboration Score
AI Collaboration Score Pending
Developer coding behavior, assistant cooperation, and AI pair-programming indicators are evaluated during live coding sessions.
Role Compatibility Profile
Role Compatibility Analysis Pending
Custom matching reports, candidate role compatibility percentiles, and core engineer strength profiles are processed once conceptual code screenings are complete.
Achievements
Performance Improvements
Up to 40% faster deployments and 50% improved reliability.
About Details
Professional Bio
DevOps Engineer with hands-on experience designing and deploying cloud-native, containerized applications. Proficient in CI/CD automation, Kubernetes orchestration on AWS EKS, Infrastructure as Code, and production-grade observability. Demonstrates measurable impact.
Bachelor of Engineering in Electronics and Communication Engineering
Sri Venkateshwara College of Engineering (2022 - 2026)