Tejash M

DevOps Engineer with 4+ years of IT experience specializing in DevOps, CI/CD automation, Release Management, cloud infrastructure, and production support for enterprise applications. Experienced in designing, implementing, and maintaining automated deployment pipelines using Jenkins, Git, Apache Ant, and JFrog Artifactory across cloud and on-premises environments. Strong expertise in Release Management processes, build automation, version control, deployment orchestration, and environment management.

Proven ability to collaborate with Developers, Solution Architects, QA teams, and business stakeholders to deliver reliable software releases with minimal downtime. Hands-on experience supporting AWS, Azure, and hybrid cloud platforms, automating infrastructure using Terraform and scripting with Python and Bash. Adept at troubleshooting deployment issues, improving CI/CD efficiency, and ensuring secure, scalable, and high-availability application delivery in Agile environments.

DevOps Engineer / SRE - State of Florida - Tallahassee, FL

(2024-07)

Stack: GCP· Azure · AWS · Kubernetes (EKS/AKS/GKE) · Terraform · GitLab CI · Jenkins · Prometheus/Grafana · Istio · Python · Go · Java

• Improved Kubernetes platform reliability to 99.9%+ availability by implementing PodDisruptionBudgets, readiness/liveness probes, resource limits, and rolling deployment strategies across production EKS environments.
• Reduced production deployment failures by 35% by implementing automated pre-deployment validation, Helm linting, security checks, smoke tests, and rollback mechanisms within Jenkins CI/CD pipelines.
• Cut AWS infrastructure provisioning time by 75% by developing reusable Terraform modules for VPC, IAM, EKS, EC2, security groups, load balancers, and supporting cloud services across multiple environments.
• Reduced configuration drift by 50% by standardizing Linux and Kubernetes configurations through Ansible automation, Git-based version control, and automated compliance validation.
• Improved CI/CD deployment frequency by 40% by integrating Jenkins with Git, Docker, Nexus, SonarQube, and Kubernetes, enabling automated build, test, artifact promotion, and production deployment workflows.
• Reduced container image vulnerabilities by 45% by integrating automated image scanning, dependency validation, and security gates into CI/CD pipelines before deployment to EKS.
• Improved incident detection by 30% by creating Prometheus and Grafana dashboards, alert rules, and service-level metrics covering Kubernetes clusters, Kafka, application health, CPU, memory, and network utilization.
• Reduced mean time to recovery (MTTR) by 25% by implementing centralized ELK logging, New Relic monitoring, automated alerting, and standardized troubleshooting runbooks for critical production services.
• Improved Kafka cluster stability by 35% by tuning partition distribution, replication factors, producer/consumer configurations, JVM parameters, and broker resource utilization across multi-AZ environments.
• Automated 70%+ of recurring operational tasks using Python and Bash scripts for health checks, log analysis, deployment validation, infrastructure monitoring, and incident remediation.
• Strengthened production security by implementing IAM least-privilege policies, Kubernetes RBAC, secrets management, network policies, and automated compliance checks across AWS and Kubernetes environments.
• Reduced application release downtime by 80% by implementing Kubernetes rolling deployments, Helm-based release management, automated health checks, and zero/minimal-downtime deployment strategies.
• Improved infrastructure consistency across Dev, QA, and Production by standardizing Terraform modules, Ansible roles, Helm charts, environment configurations, and CI/CD workflows.
• Increased platform scalability by implementing HPA, Cluster Autoscaler, resource requests/limits, and workload optimization, allowing Kubernetes environments to dynamically handle traffic spikes without manual intervention.
• Improved software quality by integrating SonarQube code-quality gates, Maven testing, dependency checks, and automated validation into Jenkins pipelines, preventing high-risk changes from reaching production.
• Reduced dependency download time and build failures by optimizing Maven repositories, Nexus caching, Docker layer caching, and Jenkins workspace management across large-scale microservice builds.
• Reduced Jenkins pipeline build time by 30% (from ~22 min to ~15 min) by refactoring parallel-stage execution, Maven dependency caching, and Nexus artifact proxying across Java and .NET microservices serving 5M+ telecom subscribers.
• Eliminated 40% of manual infrastructure provisioning effort by developing 25+ Ansible playbooks and Chef cookbooks for EKS cluster bootstrapping, configuration management, and compliance remediation integrated with Jenkins CD gates.
• Enabled high-throughput, fault-tolerant data streaming for real-time billing and network-event processing at 500K+ messages/sec by deploying and tuning Kafka and RabbitMQ clusters across 3 availability zones.
• Improved auto-scaling responsiveness for stateful Kafka workloads by implementing custom HPA metrics on EKS, reducing consumer lag spikes by 60% during peak network-event bursts.
• Enhanced application performance visibility for Java, .NET, and Python services by integrating New Relic APM with centralized ELK logging, enabling proactive latency triage and reducing P2 incident resolution time by 20%.
• Enabled containerized deployment at scale for 12 microservices by provisioning EKS clusters with Helm charts and Kubernetes manifests, reducing environment spin-up time from 4 hours to 20 minutes.

Linux Administrator - Virtusa - Hyderabad, India

(2022-03 - 2023-12)

Stack: Linux (Ubuntu/CentOS/RHEL) · Bash · Nagios · ip tables · LVM · MySQL · PostgreSQL · Nagios · Git · WebLogic · WebSphere · DNS/NTP

• Improved operational efficiency by 30% by developing 15+ Bash automation scripts for backup scheduling, log rotation, health-check reporting, and service recovery — eliminating manual overnight monitoring shifts.
• Hardened multi-user Linux server security by configuring iptables/firewalld, SSH access controls, and CIS-benchmark system hardening, reducing vulnerability surface area across 50+ production servers.
• Ensured zero unplanned storage failures by managing LVM partitioning, mount configurations, and proactive capacity planning for production Linux environments supporting insurance policy processing workloads.
• Improved database reliability and backup recovery confidence by designing and implementing a structured backup-and-restore strategy for MySQL and PostgreSQL, validating RTO targets and ensuring business-continuity compliance for 3 banking applications.
• Maintained 99%+ server uptime for Linux-based banking infrastructure by implementing Nagios proactive monitoring, configuring alerting thresholds, and executing preventive maintenance cadences that reduced unplanned outages by 15%.
• Reduced PostgreSQL deployment cycle time from days to hours by scripting automated install, compile, and startup sequences in Bash for SuSE Enterprise Linux on dedicated lab, app, and QA environments.

Bachelor of Engineering - RMK College of Engineering and Technology, India (2023)

Master - Information Technology - Florida State University, USA (2025)